{"id":6937,"date":"2020-04-03T06:30:00","date_gmt":"2020-04-03T11:30:00","guid":{"rendered":"http:\/\/thesportjournal.org\/?p=6937"},"modified":"2020-06-02T13:42:34","modified_gmt":"2020-06-02T18:42:34","slug":"scientific-epistemology-for-physical-education-fundamental-movement-skills-prerequisites","status":"publish","type":"post","link":"https:\/\/thesportjournal.org\/article\/scientific-epistemology-for-physical-education-fundamental-movement-skills-prerequisites\/","title":{"rendered":"Scientific Epistemology for Physical Education Fundamental Movement Skills Prerequisites"},"content":{"rendered":"\n

Authors: <\/strong>Robert P. Narcessian and Janet M. Leet<\/p>\n\n\n\n

Corresponding Author:<\/strong>
Robert P. Narcessian, EdM
St. Joseph\u2019s Health and Regional Medical Center
Department of Orthopedics
703 Main Street
Paterson, NJ 07503
mapsllc@optonline.net
201-612-0695; 973-754-2950<\/p>\n\n\n\n

Robert P.Narcessian is a faculty member and research\nconsultant in the Department of Orthopedics, and the primary investigator of\nthe study<\/p>\n\n\n\n

Janet M. Leet, President
Sub5, Inc.
508 S. Evanston Avenue
Arlington, IL 60004
janet@runsub5.com<\/a>
847-494-9088<\/p>\n\n\n\n

Janet M. Leet is a coach and the co-investigator of the study at St. Joseph\u2019s Regional Medical Center<\/p>\n\n\n\n

Scientific\nEpistemology for Physical Education Fundamental Movement Skills Prerequisites <\/strong><\/h3>\n\n\n\n

ABSTRACT<\/strong><\/p>\n\n\n\n

A scientific epistemology, using a systems\nthinking qualitative methodology for translating practice into theory,\nintegrates mathematical and dynamical systems concepts with belief systems that\nare presented in this original research of unique prerequisites for fundamental\nmovement skills (FMS) in physical education as illustrated with running. FMS prerequisites demonstrate that FMS are neither fundamental nor reliable\nscreentests conducted on individuals by physical education teachers, coaches,\nand healthcare practitioners for performance readiness evaluations or injury\nrisk assessments. FMS prerequisites\nidentify and assess eliminating the hypothetical set of worst first moves,\nassess the integrity of their respective coordinative structures, and assess\nperformers\u2019 beliefs (i.e., preferred behaviors) with the objective to provide a\nnew direction for researching injury risk and performance readiness. The researchers illustrate this new method with\nparticipants for FMS prerequisites\nin running and squatting to provide insight for the observer-performer\ninteraction. A new observer-performer classification\nand non-epistemic modeling show what is known with self-discovery\nstrategies that detect hidden skills at the observable level using four independent\ntasks. There were 297 participants in kindergarten\nthrough high school (213 females and 84 males; mean 14.5 years; range 5 to 17\nyears) and 21 participants from the community at large (15 females and 6 males;\nmean 31.4 years, range 12 to 94 years). A variety of running strategies of\ndifferent degrees of configured complexity from which to run were self-selected\nand observed as preferred with and without practice or intervention. An\nidealized 2-joint planar multi-joint mechanism (MJM) was used to assess\nindividual skill with respect to adding and removing constraints. Findings are\npresented for strategies, trends, and transitions of preferred behavior including\nobservables that reveal hidden skills including a visual search of a hidden\nskill with world record Olympian sprint performances. FMS\nprerequisites are theorized for future study with an inverted U-model and a\nleading MJM hypothesis; and they provide the rudiments for injury risk\nassessments and performance readiness evaluations approaching optimal health\nbiomechanically in the very early detection of flawed gross motor skill\ndevelopment before manifesting into the signs and symptoms of injury or poor performance.<\/p>\n\n\n\n\n\n\n\n

Key words:<\/strong> dynamical systems, belief systems,\nfundamental movement skills, classification, running, physical education<\/p>\n\n\n\n

INTRODUCTION<\/strong><\/p>\n\n\n\n

The human body is\ncomprised of about 50 trillion cells organized as complex biological systems\n(23) and their many subsystems that act to perform a vast variety of voluntary\nand involuntary functions with the fundamental purpose being to sustain the\nquality of healthy life. A major goal to achieve this basic objective is\ndependent upon fundamental movement skills (FMS).\nAn essential problem to be solved is that children\u2019s FMS\ndevelopment is a nonlinear evolutionary process that neither guarantees\noptimizing FMS nor reveals hidden\nskills underlying that process. For example, an ability to run does not prevent\nfaulty running mechanics, which could lead to misuse, overuse, or abuse of the\nbody reducing the quality of life physically, emotionally, and economically. In\n2013, moving toward optimal health, Faust (8) argued \u201c\u2026we don\u2019t necessarily\nneed to know a cause in order to have a preventive effect\u201d (p.553); and Khushf\n(18) said \u201c\u2026 epistemology is worth the pursuit\u201d (p.483) for such a state of\nwellbeing.<\/p>\n\n\n\n

This paper translates practice into theory\nwith a new scientific epistemology as an alternative to scientific inquiry. It\npresents a different approach to acquire knowledge (43) with FMS prerequisites that uses a qualitative\nmethodology when lacking quantification (4). This includes systems thinking in\nphysical education to reveal (i.e., know) hidden skills towards optimal health\nand enhanced performance through observation of the body and what it senses and\nlearns (22). These FMS\nprerequisites, which are based on 2-joint systems called multi-joint mechanisms\n(MJM), transition from MJM into complex dynamical\n<\/em>Fundamental Movement Skills (d<\/em>FMS)\nthat promote learning through the body\u2019s senses as argued by the constructivism\nviewpoint (22), as well as, a sense of wellbeing as pursued for a better\nquality of life (8,18). MJM is a simple model that provides a scientific basis\nto investigate what the researchers know using d<\/em>FMS about the value judgment of the observer (e.g.; physical\neducation teachers, coaches, athletic trainers, physical therapists, sports\nmedicine doctors) and the perception, motor action, and bodily senses of the\nperformer (e.g., students, athletes, and the community at large). A novel\nObserver\u2014Performer Classification (OPC) by the researchers is explained in\nAppendix A to classify groups and assign\ninterventions for the observer\u2013performer interaction value judgments. An\nepistemological view of decision-making relationship between beliefs and\nbehavior (14) was personalized with the Skill Learning Chain (13) of sports\ncoaching that organizes structured thinking and rationalized decisions by a\ncoach with competing theories; namely, information processing and dynamical\nsystems (1,13). A qualitative modeling strategy for systems thinking in biology\neducation to attain systems learning entails the crucial step from empirically\nobservable phenomena to a systems theoretical conceptualization of such\nphenomena (42). <\/p>\n\n\n\n

Connecting epistemology and research\nmethods<\/em><\/strong><\/p>\n\n\n\n

In this paper, the researchers\nconstruct FMS prerequisites as a\nnew epistemic framework for a qualitative methodology (see Appendix A: Observer\u2014Performer Classification<\/em>) to\nclassify, assess, teach, and research FMS\nwith mathematical concepts (see Appendix A: The\ndynamical systems perspective<\/em>). This methodology is illustrated with running\nor crouching down (i.e., bending down or squatting) to demonstrate these observed\ninsights with highly skilled performances in Olympic sprinting (see Appendix A:\nThe Visual Searc<\/em>h) to foster\nwellbeing (e.g.; optimal health biomechanically) and enhanced performance\n(e.g., optimize momentum). In this epistemic framework, the researchers neither\nsupport nor reject any one specific motor theory but rather question that FMS are neither fundamental (2) nor a reliable and\nvalid screening tool (30,44). The researchers\u2019 observations that will be\ndiscussed later (see Tasks) were not done to support a theory but instead to\nchallenge systems thinking in physical education. These observations are used\nfor a different qualitative methodology (4) to generate hypotheses (see the\ninverted U-model and leading MJM hypothesis discussed later).<\/p>\n\n\n\n

Connecting epistemology\nand practice<\/em><\/strong><\/p>\n\n\n\n

Ab initium (from the\nbeginning) is a fundamental question concerning seeking the most favorable\ninitial configuration for a skilled motion from which to move optimally to a\ntarget with an ultimate\ngoal to predict performance readiness evaluations and injury risk assessments\nusing FMS prerequisites to\nidentify the worst first move. The initial insight of a step-back strategy (19),\nwhich was used by 95% of the runners executing a sprint-start from a\nstance-posture, was thought to be the worst first move. Stepping back for the\nsprint-start produced an effective horizontal force by repositioning the center\nof mass of the body in front of the feet (11). In the initial study, the\nresearchers did not observe a step-back strategy for the stance-posture of the\nrun-start with performers in grades 7-12. Rather, the majority used\nstep-forward and very few used the 2-point crouch-down starting from a simple\nstance-posture, lowering slightly, within its narrow support base of 2 feet\ntogether before running instead of a complex 3-point crouch-down start (36,39).\nThe researchers suspected that step-back (i.e., a motor action) involves hidden\nskills that are self-discovered perceptively derived from bodily senses among elementary\nschool children. Apparently, young children are not well developed with the\n2-point crouch-down strategy from a stance-posture. Lacking quantification\n(e.g., perception, bodily senses), then a qualitative methodology (4) makes\npossible a deeper understanding to develop the what questions<\/em> for these hidden skills and to answer why and how\nknowledge can be created, acquired, and communicated\nwith an epistemological perspective both practically and theoretically (4,43).<\/p>\n\n\n\n

Task 1<\/strong><\/p>\n\n\n\n

Method<\/em><\/strong><\/p>\n\n\n\n

Participants<\/em>. From a sample of 318 participants, a series of\nobservational qualitative studies involving these four tasks were approved by\nthe institutional review board of the St.\n Joseph\u2019s Regional\n Medical Center.\nAdult and parental written consents, child written assents (ages 7-17), and\nchild verbal assents (ages 6 or younger) were obtained prior to their participation\nwith the right to refuse involvement at any time. For the purpose of this\npaper, the participating volunteers are referred to as \u201cperformers\u201d. These\nperformers in the study consisted of an Illinois elementary school with grades\nK-5 (38 females and 35 males; mean 8.2 years; range 5 to 10 years), an Illinois\ngirls running camp of 144 females and two New Jersey high schools of 31 females\nand 49 males comprising grades 7-12 (175 females and 49 males; mean 15.0 years;\nrange 12 to 17 years), and a Chicago area community-at-large X-group (15\nfemales and 6 males; mean 31.4 years, range 12 to 94 years). <\/p>\n\n\n\n

Procedures<\/em>. All performers (N=318) were shown a simple\nrun-start configuration of standing at attention with 2 feet together and from\nthis stance-posture, they were asked to run (not sprint). Three movement\noutcomes (i.e., movement functions that each performer seeks an initial\nconfiguration from which to run) were seen in the sagittal plane and recorded\nas: 1) step-forward, 2) 2-point crouch-down (i.e., lowering slightly in a\nnarrow support base of 2 feet together before running), or 3) step-back. An\nobserver-performer agreement was used for outcomes like a step-forward or\nstep-back. Performers 12 years and older were able to acknowledge their\npreferred behavior was in agreement with the strategy for the run-start that\nthe observer saw within a few attempts without practice or intervention.\nPerformers in grades K-5, observations using the game Simon Says & Shows\nwere made by one author and independently confirmed by the other author to\nobserve self-selected strategies as their preferred behavior and to show\nconfigurations in a playful setting among a set of irrelevant movement tasks,\nwhich disguised those tasks of interest. Task observations were recorded as a\nsimple tally. Proportions were calculated to quantify behavioral preferences\nand fifth order polynomials were generated in Microsoft Excel (2003) charts to\nillustrate trends across age groups. All relevant data are contained in this\nmanuscript; and preferred behaviors can be obtained as percentages of the\nsample populations in the paper.<\/p>\n\n\n\n

Results<\/em><\/strong><\/p>\n\n\n\n

Run-start strategies (Figure 1) were\nassessed as OPC-I (see Appendix A: The\nObserver\u2014Performer Classification<\/em>) for a 2-point crouch-down because it was\nassumed this strategy required a higher level of skill as a prerequisite for a\nrun (i.e., 1-point crouch-down at footstrike); but, step-forward and step-back\nwere assigned OPC-II and assumed not to optimize performance. Grades K-5 (N=73) performer preferences were step-forward,\nstep-back, and 2-point crouch-down at 63%, 35.6%, and 1.4%, respectively; and\nwhere 2-point crouch-down preferences averaged 1.4% for grades K-5 (N=73), 5.8%\nfor grades 7-12 (N=224), and 4.8% for the X-group (N=21). Performers (N=245) in\ngrades 7-12 and the X-group preferred step-forward at 94.3% and 2-point\ncrouch-down at 5.7%. All performers (N=318) averaged 87.1%, 8.2%, and 4.7% for\nstep-forward, step-back, and 2-point crouch-down, respectively. <\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 1. For kindergarteners and second graders,\nstep-forward (triangle) was seen preferred with a decline during third grade.\nAn upward trend dominated thereafter. A transition was seen from step forward\nto step-back (black square) with first graders. A reversal from step-back to\nstep-forward occurred in second grade, which was equally preferred by third\ngraders. The step-back strategy followed a decreasing trend from third grade\nthat flowed into another transition of a preferred 2-point crouch-down (circle)\nstrategy with very few in grades 7-12 and the X-group.<\/p>\n\n\n\n

Discussion<\/em><\/strong><\/p>\n\n\n\n

Step-back was seen with run-start\namong elementary school children. Apparently, elementary school children,\nespecially first graders, solve an initial value problem (IVP: see Appendix A: The dynamical systems perspective<\/em>)\nthrough self-discovery steady states with step-back, which increase the base of\nsupport and rely on the initial conditions of motor system estimates for the\npreplanned inverse kinematics, including the predicted forward dynamics (45) in\norder for the inverse dynamics to produce their preferred behavior in the\nstep-back strategy for run-start. From a dynamical systems perspective, an\ninitial configuration from which to run occurs when the initial conditions of\nan unsteady state with a narrow support base of an existing behavior (e.g., stance-posture) are replaced by those of a\nmore preferable and reliably stable behavior, which increases the base\nof support (e.g., step-forward or step-back) and can be trusted by the\nperformer. Yet, observation alone neither explains the initial conditions for\nthese run-start strategies nor the transitions that occur over time where so\nfew 2-point crouch-down strategies were seen. The researchers are left with a\ndilemma as to which of these strategies is best.<\/p>\n\n\n\n

Running can assume many different\nstarting configurations as force plate studies have revealed that among the\nstanding sprint-starts, step-back is better than step-forward by repositioning\nthe center of mass of the body in front of the feet to generate a horizontal\nforce (11); and a 3-point crouch-down is better than step-back by generating\nthe greatest increase in a backward shift of the center of pressure to produce\nthe most horizontal acceleration of the center of mass of the body (39).\nCombining force plate with kinematic analysis (36) showed that a wide base of\nsupport in a 3-point crouch-down resulted in the shortest duration of start\ntime of various positions influencing sprint performance. Once again,\nobservation fails to explain why so few performers self-discover the 2-point crouch-down\nstrategy (4.7%) compared with those performers who preferred step-forward\n(87.1%) for the run-start.<\/p>\n\n\n\n

These observations of falling within\nor without the initial support base depict an essential question to be solved\nwith FMS prerequisites during\nchild development, which is a nonlinear evolutionary process that does not\nguarantee reliable FMS nor reveal\nacquired hidden skills. This ability to run with different strategies implies\nlow complexity and great difficulty to predict the multifactorial movement\npatterns that are involved with a vast number of degrees of freedom\ncompensating for error and risking injury. Moreover, the paucity to\nself-discover the 2-point crouch-down strategy suggests a hidden skill where\nIVP solutions for dynamic systems theory lack sufficient input information of\ninitial conditions to perform an act like 2-point crouch-down with a narrow\nbase from a stance-posture when more stable 3-D bases exist (e.g., a wide\nsupport base of the 3-point crouch-down start, step-forward, or step-back).\nThis situation might support information processing theory (1) where creative\nwording and appropriate feedback provides the performer the required\ninformation (46).<\/p>\n\n\n\n

From the dynamical systems\nperspective, the run-start configuration is modeled as an idealized 1-D\ninverted pendulum, which is a straight line of self-constrained joints and\nsegments of the body that starts as a single-joint system with a potential\nenergy and a narrow base of support in a state of stability that can be\nresearched as an IVP to assess the motion about the ankle joint when the\nrun-start transitions from an idealized 1-D single-joint system into the 3-D\nmulti-joint system of a run. Each performer attempts to solve an IVP for a\nsingle-joint system without knowing the initial conditions of the segmental\nvelocities and the skill of temporary assemblages utilizing more segments and\njoints that transition from the single-joint system (i.e., removing constraints\nand increasing degrees of freedom) into a multi-joint system to find a steady\nstate among a set of targeted initial configurations that can be trusted\nsolutions to run well.<\/p>\n\n\n\n

From an epistemological perspective,\nTask 1 lets us know that very few performers, as illustrated in Figure 1, preferred\nthe 2-point crouch down (i.e., utilize gravity) as an OPC-I to find an initial\nconfiguration within the base of support from which to run. Why this occurs may\nbe explained where a lack of vital sensory input has yet to exist for a\nmeaningful perceptual understanding that could change the belief system of the\nperformer. Furthermore, the researchers know that falling to an initial\nconfiguration within a support base to start to run requires the skill of a\nmulti-joint system different from those configuration strategies outside the\nsupport base, which seeks to answer the question how this needs to be done in a\nchaotic state of too many degrees of freedom. It appears that potential\nlearning can occur by investigating the 2-point crouch-down with a narrow base\nof support, which requires removing constraints and adding degrees of freedom, that\nare not easily self-discovered compared to falling outside the support base as\nseen with either step-forward or step-back. Task 2 provides insight about\nfalling within a narrow support base.<\/p>\n\n\n\n

Task-2<\/strong><\/p>\n\n\n\n

Method<\/em><\/strong><\/p>\n\n\n\n

Participants<\/em>. Grades K-5 (N=57) and the X-group (N=21) were the\nonly performers experiencing this task for the first time. K-5 students (N=16) were\nabsent. The 144 female runners and 80 NJ students (31 females and 49 males)\nwere excluded due to previous experience.<\/p>\n\n\n\n

Procedures<\/em>. Although starting in the stance-posture of Task\n1, the X-group performers were only asked to match the elbows-to-knees boundary\nconfiguration (Figure 2A) and the hands-to-knees target configuration (Figure\n2B). For performers in grades K-5, observations using the game Simon Says &\nShows were made by one author and independently confirmed by the other author.\nResults were recorded as OPC-I only on their ability to match the boundary\nconfiguration or a target configuration; yet, the BMM\nhelps assess the motion without a measurement device.<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 2. MJM configurations: (A) boundary and (B) target;\n(C) environmental constraint, (D) BMM\nand fulcrum, and (E) geometric model of the planar 2-joint system. Adult,\nparental, and child written consents were obtained for permission to use these\nimages.<\/p>\n\n\n\n

Performers were provided the boundary\nvalue problem (BVP: see Appendix A: The\ndynamical systems perspective<\/em>) boundary conditions for the robotic MJM with\nshow & tell instructions to keep feet and knees together, keep a straight\nback with arms kept bent for the boundary configuration and straight for the\ntarget configuration, and sustain lower leg immobility while balancing and\ncrouching down. Constraints were applied to eliminate the worst first moves.\nFor example, verbal constraints to keep knees together or some environmental\nconstraints like a chair (Figure 2C) were used to see if the performer would\nbehave more like the inanimate robot and to prevent a\nsuspected worst first move (e.g., ankle-dorsi-flexion). The BBM of whole foot\nground contact and lower leg perpendicularity to the ground, with its fulcrum\npoint (Figure 2D) ideally located at the anterior aspect of the calcaneus\nthrough the talus bone, adjusts with minimal functional variability to maintain\nthe moment arm (r1<\/sub>) of the femur mass center (m1<\/sub>) and the\nmoment arm (r2<\/sub>) of the segmental quasi-rigid mass center (m2<\/sub>)\nof head-spine-pelvis-upper extremities where m1<\/sub>r1<\/sub> = m2<\/sub>r2<\/sub>\napproximates the linear trajectory of a point particle system\u2019s center of mass\nrepresenting the idealized 2-joint planar system. This FMS\nprerequisite assesses squatting and balance capability to reconfigure body\nsegments in the 2-point crouch-down strategy optimally guided by the line of\ngravity from stance-posture to the boundary configuration as illustrated with a\ngeometric model in equilibrium (Figure 2E). <\/p>\n\n\n\n

Results<\/em><\/strong><\/p>\n\n\n\n

MJM constrained was OPC-I\nat 28.1% and 33.3% at boundary, and 100% and 95.2% at target, for K-5 students\n(N=57) and the X-group (N=21), respectively. Constrained data were attained\nwith knowledgeable application of the constraints. MJM unconstrained for\nX-group was OPC-I at 14.3% boundary and 81% target. K-5 students failed MJM\nunconstrained using the Simon Says & Shows game. Some X-group boundary\nerrors (OPC-II) are seen in Figure 3.<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 3. Sample errors: (A) trunk alignment, (B) pelvic\ntilt, (C) ankle dorsi-flexion (D) hip-knee lacks one-to-one correspondence.\nPerformers thought that they executed correctly (OPC-II). Adult, parental, and\nchild written consents were obtained for permission to use these images.<\/p>\n\n\n\n

Discussion<\/em><\/strong><\/p>\n\n\n\n

From the dynamical\nsystems perspective, starting with stance-posture of Task-1, MJM is modeled as\nan idealized 2-joint, 2-D system that represents the most basic skill for the\nhip and knee to crouch-down and to maintain equilibrium as a predictable motor\naction where retaining fixed segments (i.e., adding constraints and reducing\ndegrees of freedom), the movement of femur segment to a new position requires\nthe fixed segments of the quasi-rigid head-spine-pelvis-upper extremities to\nsolve a BVP of a known boundary configuration via highly predictable positions\nof low complexity, which are reliable scientifically and valid mathematically.<\/p>\n\n\n\n

The stance-posture of\nTask-I is an unskilled configuration of a single-joint system; whereas, MJM\nrepresents the most basic skilled configuration of a 2-joint system. Both\nsystems balance about the ankle joint, where the BMM\nwas used with MJM to construct what to observe as the worst first move (i.e.,\nankle motion) with and without constraints. MJM constrained was helpful for\nperformers to assume the target configuration; however, observation alone\ndoesn\u2019t explain why most performers had difficulty applying constraints and\nfailing to acknowledge (i.e., OPC-II) an inability to match the boundary\nconfiguration.<\/p>\n\n\n\n

MJM offers a means to\ninvestigate not only control with sensory equilibrium with properly applied\nconstraints, but also the 2-point crouch-down coordinative role of 2-joint\nsystems of the hip-knee linkage during planar motions with and without task\nconstraints unlike those of single-joint motions, which do not evaluate\ncoordination or equilibrium. Performers who are able to self-impose the\nboundary conditions must reconfigure 2-point crouch-down to utilize the force\nof gravity (i.e., a conservative force to guide the reconfigured body to unload\nand fall within the base of support to a specified target configuration). With\nthe hidden skill of unloading (a prerequisite skill for squatting), 2-point\ncrouch-down behaves like a highly predictable robotic MJM 2-joint planar system\nof low complexity may attain stabilization as described in 1972 by Greene (15)\nwhere: \u201cThe feedforward had only to bring the state of the system \u201cinto the\nright ballpark\u201d\u2014 that is, into some broad class of states, within which\nfeedback could automatically bring the system the rest of the way to the exact\nstate required\u201d (p.310). However, often postural constraints are overlooked perceptually\n(i.e., a hidden skill) with respect to even simple configurations. This\nsuggests that balance may be achieved with compensatory configurations leading\nto risk of injury or poorer performance. Failure to apply constraints of a\nsimple 2-joint planar system presupposes identifying a worst first move or\nrevealing an underdeveloped hidden skill in which practicing an inferior stable\npattern reinforces a belief system that could argue support of schema theory\n(34). Herein, there exists a paradox; namely, an inferior stable pattern is\npreferred based upon perception. Such beliefs are suspected to lead to misuse,\noveruse, or abuse that ignores microtraumatic warning signs of faulty mechanics\nthat potentially risks injury or at least results in poorer performance.<\/p>\n\n\n\n

From an epistemological\nperspective, MJM has the epistemic value of simplicity to assess the coordination\nof the hip and knee in a planar 2-joint system that avoids chaos by reducing\nthe degrees of freedom; however, this model also offers the non-epistemic value\nof wellbeing with its output that provides an evaluative judgment (6) about a\nstate of a most basic skill to crouch-down applying constraints to match either\na target or the boundary configuration. Why this occurs may be explained where\na hidden skill controlling constraints has yet to be discovered how to utilize\ngravity; as well as, a lack of vital sensory input to enable a perception that\nis difficult to discern, often resulting as an OPC-II, and fails to change a\nbelief system.<\/p>\n\n\n\n

Sensory information and\nperception (belief systems) that influence preferred behavior possess elements\nof uncertainty, which lacks both reliability and predictability. An application\nof the Le Chatelier-Braun principle attempts to measure uncertainty of sensory\nequilibrium ranging from a state of complete certainty to sensory\ndisequilibrium (28). When an unfamiliar stimulus increases uncertainty, a state\nof sensory disequilibrium exists until a restoring influence provides a new\nlevel of sensory equilibrium. Sensory equilibrium approaches a state of\ncomplete certainty as the preferred behavior when movement tasks are perceived\nas acceptance by the performer (i.e., OPC-I or OPC-II) compared to a state of\nsensory disequilibrium when movement tasks are assessed as rejection by the\nperformer (i.e., OPC-III or OPC-IV). This presents the performer with a sensory\ndilemma of discrimination with an observer-performer interaction that may undergo\na sensory order described in 1976 by Hayek (17) as a process of classification\nand reclassification in the brain \u201cto create altogether new sensory qualities\nwhich have never been experienced before\u2026 can be greatly developed by practice\u201d\n(p.152), and the observer with a wording or feedback predicament where Wulf\n(46) in 2013 argued \u201csubtle differences in the wording of instruction or\nfeedback can have significantly different effects on performance and learning\u201d\n(p.99) as with optimal configurations and movement strategies. <\/p>\n\n\n\n

Task-3<\/strong><\/p>\n\n\n\n

Method<\/em><\/strong><\/p>\n\n\n\n

Participants<\/em>. The performers from Task 1 that were available\nfor Task 3 were students in grades K-5 (N=72) except for one absentee, grades\n7-12 comprised of the female runners (N=144), and the X-group (N=21). Task 3\nwas added to the study after the NJ students (N=80).<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 4. RRStart configurations with BMM: (A) boundary and (B) target; and (C)\nfunctional BMM variability is\nhypothesized to be resolved with self-discovery learning provided MJM is set\nclose to the rear foot. Adult, parental, and child written consents, as well as\nchild verbal assent under age 7 were obtained for permission to use these images.<\/p>\n\n\n\n

Procedures.<\/em>  The\nperformers were asked to run from a d<\/em>FMS,\ncalled RRStart, which was configured and shown as a 4-point crouch-down for the\nfeet, hand, and elbow in a tandem stance with their feet about a foot\u2019s length\napart, the hand of the rear foot placed on their ribs, and the contralateral\nelbow placed at the knee of their rear leg for the RRStart boundary\nconfiguration (Figure 4A) with a BMM\nset with bodyweight primarily on the heel of the rear foot. The hand-elbow positions help attain thoracic rotation\nof the trunk. Only the X-group was told how to set the BMM\nwith whole foot ground contact weighted primarily on the perpendicular rear\nleg. The runners and elementary students were not told about perpendicularity. Simon-Says & Shows was used with K-5\nstudents; and their hand instead of the elbow was placed at the rear leg knee\nfor the RRStart target configuration (Figure 4B) because they failed the MJM\nunconstrained in Task 2. <\/p>\n\n\n\n

Three predictable\noutcomes were observed and recorded as: 1) no-step, which increases the base of\nsupport by transferring weight onto front foot before stepping forward with the\nrear foot, 2) momentum-step, where the front foot steps forward spontaneously\ndue to an assumed rear foot propulsive force that produces the momentum-step\nfrom the idealized narrow support base approximating the anterior calcaneus\npoint of the rear foot, or 3) step-back, which increases the base of support\nprior to running. Task observations were recorded as a simple tally.\nProportions were calculated to quantify behavioral preferences. All relevant\ndata regarding preferred behaviors can be obtained as percentages of the\nsamples in the paper and Figure 5.<\/p>\n\n\n\n

Results<\/em><\/strong><\/p>\n\n\n\n

RRStart strategies (Figure 5) were assessed as OPC-I for the momentum-step because it was assumed this strategy required a higher level of skill as a prerequisite for a run; but, no-step and step-back were assigned OPC-II and assumed not to optimize performance. For the RRStart (Figure 5), K-5 and the X-Group were seen with BMM intervention and without practice. K-5 (N=72) averaged OPC-II at 19.4% for no-step. K-2 (N=33) performers averaged OPC-I at 72.7% for momentum-step. Grades 3-5 (N=39) averaged OPC-II at 79.5% for step-back. The X-group (N=21) averaged OPC-I at 81% and OPC-II at 19% for momentum-step and no-step, respectively. With practice and without BMM intervention, the preferred behavior for the performers in grades 8-12 (N=130) averaged OPC-I at 12.3% and OPC-II at 87.7% for momentum-step and no-step, respectively. Grade 7 (N=14) were preferred similarly; then diverge.<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 5. RRStart preferred behaviors with BMM intervention\nand without practice (white legend keys) and preferred behaviors with practice\nand without BMM intervention (black legend keys). The X-group and grades K-2,\nespecially grade 1, preferred a momentum step (white square). Grades 3-5\npreferred the step-back (white circle). Grades 8-12 preferred no-step (black\ntriangle) and very few preferred the momentum-step (black square). The\nmomentum-step (black square) and the forward-step (black triangle) were closer\nin preference for students in grade 7.<\/p>\n\n\n\n

Discussion<\/em><\/strong><\/p>\n\n\n\n

RRStart was observed with\nand without BMM intervention or\npractice of the 2-joint system to assess the IVP 4-point crouch-down strategy\nto start a run for a complex 3-D system with moderately predictable outcomes of\neach performer\u2019s preferred behavior without knowing the initial conditions to\nseek a steady state among a set of possible initial configurations that can be\ntrusted as preferred solutions from which to run and reveal hidden skills.\nAgain, this situation might support information processing theory (1) where\ncreative wording and appropriate feedback provides the performer the required\ninformation (46). The perpendicularity of the BMM\nintervention may be the critical information given to the performer by the\nobserver.<\/p>\n\n\n\n

From the dynamical\nsystems perspective, RRStart theoretically models IVP solutions for the hidden\nskill that applies an effective propulsive force that optimizes momentum for a\n4-point crouch-down strategy to produce a momentum-step from an idealized\nnarrow support base to start a run. The researchers hypothesize that the momentum is directed\noptimally forward and up with a momentum-step, which increases step length; and\nthat the step-back or no-step strategies increase their support base before\nrunning where momentum is directed backward initially or downward,\nrespectively. RRStart offers a performance readiness evaluation of\nmomentum-step self-discovery with MJM using the BMM,\nwhich appears to be important information for the initial condition of position\nthat wasn\u2019t presented using drills during the initial study. Future study is\nneeded to resolve the contribution of MJM with RRStart as a key configuration\nleading to develop a momentum-step (see a leading MJM hypothesis). <\/p>\n\n\n\n

From an epistemological\nperspective, Task 3 lets us know that very few performers in grades 7-12, as\nillustrated in Figure 5, preferred the momentum-step without BMM intervention even with practice compared to applying\nBMM intervention where a majority\nof the performers in grades K-2 and the X-Group preferred the momentum-step\nwithout practice. It is not clear why grades 3-5 preferred step-back. RRStart\nhas the epistemic value of simplicity to study a d<\/em>FMS; however, RRStart also offers the non-epistemic value that\nrepresents a complex process to describe and explain wellbeing (6) with its\noutput (i.e., the momentum step) to provide a sensory value judgment about a\nmost basic skill to exploit momentum with a properly directed quality thrust that\nresults as a smooth transition to start a run (OPC-I) or not. This illustrates a\ncase of a non-epistemic value that the RRStart models a process where pragmatic\nlimitations of a sense exists and epistemic values do not determine the significance\nof an effortless perception (6). Why this occurs is explained with the fact\nthat the brain does not sense momentum itself; yet, this elucidates how a FMS prerequisite addresses this issue and offers a\nmeans to create, acquire, and communicate knowledge to the performer to\ndiscover the skill of exploiting momentum.<\/p>\n\n\n\n

Task-4<\/strong><\/p>\n\n\n\n

Method<\/em><\/strong><\/p>\n\n\n\n

Participants<\/em>. Only X-group performers (N=20) with one opting\nout attempted another d<\/em>FMS, called\nthe RRRun. K-5 performers (N=73) did not participate because they required intervention\ndrills and practice, which was beyond the scope of this paper. RRRun was added to\nthe study after the participation of the female camp runners (N=144) and the NJ\nstudents (N=80).<\/p>\n\n\n\n

Procedures<\/em>. The X-group performers were asked to attempt\nthe RRRun as a simultaneous 2-point crouch-down of the hand and foot, which\ninvolves touching their contralateral knee with their hand at the same time\ntheir foot strikes the ground while running at a preferred speed within a\ndistance less than 20 meters. Their bilateral ability was observed when the\nperformers were asked to repeat the task on the opposite side. The three\npossible outcomes observed with hand-knee contact were recorded as: 1)\nfoot-grounded, 2) foot-airborne, or 3) no-contact. To avoid the common occurrence\nof foot-airborne, the researchers emphasized instruction to touch the knee when the foot hits\nthe ground for a pragmatic perceptive assessment of the RRRun at footstrike.<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 6. RRRun (A) left foot contact reported perceptively\nas a good thrust during the run; (B) right foot contact reported perceptively\nas awkward, which would likely make the performer think something is wrong and\nthe observer believe the performer\u2019s perception of a flinging right arm to\ncompensate a loss of balance is an error rather than a self-discovery,\nevolutionary process with functional variability supported with BMM that aids learning and adaptation; and (C)\nright foot contact reported perceptively a good thrust during the run after 2\nweeks of self-discovery practice. Parental and child written consents were\nobtained for permission to use these images.<\/p>\n\n\n\n

Results<\/em><\/strong><\/p>\n\n\n\n

For the X-group executing\na few RRRun trials, unilateral outcomes for no-contact and foot-grounded were\nseen OPC-II or OPC-IV at 65% and OPC-I at 35%, respectively. All non-contact\noutcomes were seen and acknowledged by the observer and performer,\nrespectively. All unilateral foot-grounded outcomes were seen in the ballpark<\/em>; and each performer\nreported feeling a quality thrust on one side; yet, no thrust on the other. Of\nthe two performers (10%) who were observed successful bilaterally, a 12-year\nold female had been videoed during the RRRun, which revealed screenshots that\nher reported quality thrust did hit the simultaneous 2-point crouch-down BMM target configuration (Figure 6A) on her left\nfoot; and that she reported feeling awkward when touching her knee at right\nfoot contact with compensatory right arm to balance at the simultaneous 2-point\ncrouch-down BMM target\nconfiguration (Figure 6B).<\/p>\n\n\n\n

Discussion<\/em><\/strong><\/p>\n\n\n\n

RRRun is a non-epistemic process\nthat models (6) a sensory experience of a quality thrust transitioning smoothly\nthroughout the phases of the RRRun where pragmatic limitations of a feeling exist and epistemic values do\nnot determine the significance of a quality perception. This experience results\nin an increased wellbeing that is essential for the performer to trust feeling\nan applied force that can be aided by the observer with the BMM screenshot. The objective is a value judgment to\nassess the hidden skill of applying an effective force that avoids the misuse\nof an improperly directed force. Reliance on such a perception of force is\nquestionable (28); however, clinically this perception aids to develop and\nlearn the hypothesized hidden skill of the effective force to exploit momentum\nin a run. Also, unilateral outcomes provide motivation to self-discover the feeling\nof a quality thrust bilaterally with a smooth transition into the run. RRRun\nprovides the performer what to feel, which cannot be described like the taste\nof an apple. Rather, it can only be known through feel. What the researchers know here is that the\nperformer feels whether or not they experience a thrust; as well as, whether or\nnot there is a sense of awkwardness or smoothness performing the task. Why this\noccurs may be explained similarly to Task 1 where a lack of vital sensory input\nhas yet to exist for a meaningful perceptual understanding that could change\nthe belief system of the performer. Caution is advised attempting RRRun at\nfaster speeds. Also, cautions with footstrike have been expressed (16,26).\nFuture study is needed for the contribution of MJM using BMM with RRRun as a key configuration to develop\nthe momentum-step (see a leading MJM hypothesis).<\/p>\n\n\n\n

GENERAL DISCUSSION<\/strong><\/p>\n\n\n\n

The researchers used these 4 independent\ntasks to introduce a qualitative methodology for both practitioners and\nresearchers to identify a set of worst first moves, reveal hidden skills, and\nprovide perceptive value-judgments with respect to what needs to be known to\ngroup the preferred behaviors of performers as witnessed by the observer. This\nwas done using a scientific epistemology involving dynamical systems and the\nconcept of idealization for the different dimensions of these four tasks;\nnamely, a single-joint 1-D system, a 2-joint 2-D system, and two d<\/em>FMS 3-D systems (i.e., RRStart and\nRRRun) as FMS prerequisites for\nrunning.<\/p>\n\n\n\n

The researchers observed different\nrunning strategies with which performers seek a more stable configuration from\nwhich to run (e.g., step-back, step-forward, crouch-down, momentum-step,\nfoot-grounded, no-step, and no-contact). However, d<\/em>FMS like RRStart, yielding momentum-step with self-discovery, and\nRRRun, sensing an asymmetry with respect to force or an awkwardness, solve an IVP\nwhere the performer must spontaneously rely on not only the initial conditions\nof position and velocity, but also the somatosensory inputs from the pressure\non the sole of the rear foot, and the proprioceptive signals about the status\nof the joints, participating muscles, and configurations. Inverse dynamics of\nthe motor system involves muscle torque activation that ideally moves the limbs\nof the body as desired (45). Inverse kinematics is the required motor control\nfor reaching actions whereupon before planning those acts were described in\n2002 by Wise & Shadmehr (45) as \u201c\u2026 the motor system must estimate both\ncurrent hand position and the direction and magnitude of the movement needed to\nreach the target\u201d (p.11). Analogous to hand position is the run-start, RRStart,\nRRRun configurations requiring increased sensory\ninput to solve the initial conditions of their IVP. Furthermore, the forward\ndynamics of the motor system\u2019s applied force estimates needed to produce the\ndesired motion relies on this computation with the ability to predict the\nsensory consequences of motor commands (45).<\/p>\n\n\n\n

The Biomechanical Problem<\/em><\/strong><\/p>\n\n\n\n

Seeking an optimal\ninitial configuration is a problem in nonlinear dynamics for systems of greater\ncomplexity than the expected MJM as their trajectories are unpredictable (chaotic).\nThis is further complicated by the fact that biomechanical models and their\nstudies are incapable of quantifying the sensory and perceptual contributions\nof skill development. In addition, inverse dynamics attempts to analyze more\nsuitable trajectories for more complex systems of three joints or more, but is\nlimited even when compared with forward dynamics. Forward dynamics was claimed\nas the golden standard (29) from which gait analysis laboratories using inverse\ndynamics vary greatly to match forward dynamics data. Forward dynamics relies\non computing double integration of the ground reaction forces of existing\nconfigurations to calculate center of mass of the body\u2019s position that\nrepresents locomotion throughout its trajectory. Conversely, inverse dynamics\nuses kinematics (i.e., the geometry of the system) in approximating the body\u2019s\nposition with double derivation that risks error in acceleration calculations\nwhen compared with forward dynamics data. Moreover, neither forward dynamics\nnor inverse dynamics is able to find new configurations that have yet to exist\nor assess sensory inputs that have perceptive epistemic value, which cannot be\nquantified. For example, a forward dynamics analysis of the straddle high jump\ntechnique before the existence of the Fosbury Flop technique would fail to\ndiscover the Fosbury Flop in spite of any inverse dynamics analysis of the\nstraddle high jump that closely approximates its forward dynamics data.\nLikewise, these forward dynamics studies could only compare known crouch-down\ninitial configurations and their motions; and they could neither discover an\nunknown optimal crouch-down initial configuration nor original d<\/em>FMS like the RRStart and the RRRun that\nprovide value-judgments for what can be known through feel and a method to\ntrain and learn with the explicit knowledge of MJM\u2019s geometry and the tacit\nknowledge (31) acquired from decades of hands-on clinical experience regarding\nhuman movement skill associated with both enhanced athletic performance and\nfunctional rehabilitation moving toward optimal health (8,18).<\/p>\n\n\n\n

The Value of the\nBioMechanical Marker<\/em><\/strong><\/p>\n\n\n\n

A geometrical\ninterpretation at an observable level of FMS\nprerequisites affords economy and insight in monitoring the outcomes to\ninvestigate novel MJM solutions. Geometrically, the center of mass of the body\nrepresents its location either stationary or moving. The center of mass of the\nbody can be assumed to travel a one-dimensional linear trajectory in the\nhip-knee planar motion of the MJM 2-joint system, which is bounded anatomically\nby a terminal configuration at the start of its linear path and by a boundary\nconfiguration at its end range of motion to maintain equilibrium as seen with\nthe BMM. According to Glazier and\nRobins (12) in 2012, qualitative analytical techniques are not the traditional\n\u201c\u2026 observation and subjective evaluation of movement sequences \u2026 but rather the\nstudy of geometric properties of movement\u201d (p.121). Robotic MJM gives both a\nvisual image and a mathematically defined geometric coordinative movement\npattern for a technique analysis of whether or not a performer successfully\napplies self-imposed constraints while attempting to perform the\nprocess-oriented, self-discovery approach of pragmatically solving a two-point\nBVP for the motion of an idealized, 2-joint planar system. At its boundary or\ntarget configuration, MJM has a high predictability to function reliably as a\nmechanism, which identifies the performer\u2019s sensibility and knowledge about the\nworst first move, and provides a means to compare the ability of the performer\nto control and coordinate the simple 2-joint system to match a boundary or a\ntarget configuration of low complexity. In addition, MJM is observed at a key BMM moment, which helps the observer clinically\nassess the RRStart in a state of static equilibrium and RRRun using a\nscreenshot for dynamic equilibrium.<\/p>\n\n\n\n

Translating Practice into\nTheory<\/em><\/strong><\/p>\n\n\n\n

Complex systems research\nfor the emergent patterns of human movement has been argued to start directly\nat the observable level of behavior (25). An epistemic framework is needed to\nbridge the gap between practice and theory. Evidence of this gap in research\nwas held in 2016, where after\nalmost 2 decades of research, Latash (20) wrote, \u201cWhile the recent progress in\nbiomechanics and motor control has been impressive, we are still far from being\nable to make recommendations for practitioners, such as physical therapists,\ncoaches and physical education teachers. The current established knowledge is\nmeager and the intuition of a good clinician or a good coach typically beats\nrecommendations that can be made by a researcher\u201d (pp.17-18). <\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 7. RRRun (A) an IVP of unknown initial conditions\nprior to toe-off; (B) whole-foot contact characterizing the first BVP point\nstarting with a known BMM 2-point\nsimultaneous crouch-down target configuration; (C) the second BVP point ending\na phase transition of whole-foot maintenance prior to heel-lift; (D) a third\npoint depicting one of many possible forward lean configurations prior to\ntoe-off; (E) the known whole-foot configuration as seen with BMM, representing the hypothetical IVP initial\nconfiguration of running periodicity; and (F) an IVP solution of a known\nposition and uncertain velocities to hit another forward lean configuration\nprior to toe-off. Parental and child written consents were obtained for\npermission to use images.<\/p>\n\n\n\n

For the good clinician or good coach,\nthe researchers present systems thinking with a qualitative methodology for how\nwhat they know to explain and predict natural phenomena that cannot be observed\nempirically; rather, that which is known through the senses as a non-epistemic\nvalue of wellbeing in modeling the process of d<\/em>FMS. For example, consider the follow-up screenshots of a video\nwith a Samsung Galaxy (S7) are used to illustrate what the researchers know\nabout the self-discovery experienced using RRRun by a 12-year-old female from\nthe X-group. After two weeks of having played independently with RRRun to\nself-discover bilateral symmetry, she was seen as a follow-up and reported a\nquality thrust on the right foot as seen with the simultaneous 2 -point\ncrouch-down BMM target\nconfiguration (Figure 6C). One week later, her video screenshots showed a\nforward lean configuration on the left foot prior to toe-off (Figure 7A), her\nleft hand touching her right knee in the simultaneous 2-point crouch-down BMM\ntarget configuration of right whole-foot strike (Figure 7B), maintaining\nwhole-foot contact prior to heel-lift at another MJM (beyond the scope of this\npaper) where she reported experiencing a good thrust (propulsive force) (Figure\n7C), a forward lean configuration prior to toe-off (Figure 7D), the left\nwhole-foot strike seen with the BMM\nat a theoretical initial configuration of the run or sprint (Figure 7E), and\nending the left foot stride at another forward lean configuration prior to\ntoe-off (Figure 7F). An epistemology is needed to close this gap leading to\nwellbeing, and it is worth the pursuit (18).<\/p>\n\n\n\n

Epistemological Insights and\nTheoretical Concepts<\/em><\/strong><\/em><\/strong><\/p>\n\n\n\n

From the perspective of an observer-performer\ninteraction, the researchers connect observation to theory with the\nepistemological systems concept (42) that involves distinguishing the empirical\nand the theoretical concepts in order to grasp systems concepts by bridging the\nusage of their languages describing observations. Clinically, pictures are the\nlanguage of a thousand words and observations are the first step in the\nscientific process to answer the question: What do the researchers see and what\ndoes the runner feel? Video screenshots, the language of observable\nconfigurations, offer the perspectives of both the observer and the performer.\nThe researchers opine that her reported feeling a good thrust with the RRRun\nprovided her with a justified belief to continue independently to self-discover\nbilateral success. Her forward lean (Figure 7A) theoretically required an IVP\nsolution for momentum to be directed optimally forward and up; rather than\nleaning too far forward redirecting momentum forward and down. It is the opinion\nof the researchers that she possessed the intrinsic dynamics to trust that her\ntoe-off IVP solution would hit the known BMM\nsimultaneous 2-point crouch-down target configuration (Figure 7B) without her\nexplicit knowledge of the IVP initial conditions of many possible toe-off\nconfigurations. From an epistemological perspective, the belief of the\nresearchers is supported observing the whole-foot BMM\nand hearing about her justified belief claiming feeling a quality thrust\nwithout any awkwardness. Theoretically, her simultaneous 2-point crouch-down\ntarget has established the first of two points for solving a 2-point BVP within\nthis piecewise phase of interest that a hidden skill may be revealed with other\npoints between the two footstrike BVP points. In theory, there are infinite\nnumbers of transitional configurations of which heel contact (Figure 7C)\nremains debatable as a justified belief in sprinting. From perspective of the\nobserver, the representational momentum that is directed from the forward lean\n(Figure 7D) can be supported by Nakamoto, et al (27) in 2015 who claim such a\nperspective \u201c\u2026 depends not only on raw visual information, but also on internal\nrepresentations that include the expectation for a future object location,\nperhaps based on prior knowledge\u201d (p.970); that is BMM.\nThe researchers\u2019 belief is that the expected future location is the theoretical\ninitial configuration of the run or sprint between steps as seen with the BMM configuration (Figure 7E) that the observer\nwould predict to see at the completion of the step from right whole-foot to\nleft whole-foot, which is a known position. From her perspective, she feels a\nchange in momentum at impact (i.e., an impulsive force) and the muscular forces\nstabilizing segmental rotary motion as an effortless and smooth transition into\nthe run. Her brain cannot feel momentum itself, and is subjected to its\nconsequences of linearly directing the center of mass of the body and angularly\nsegmental spin about bodily axes. However, this created another IVP for her to\nsolve the unknown initial segmental velocities to complete the stride between\nleft footstrikes at another forward lead configuration prior to toe-off (Figure\n7F), which depends on her producing and feeling a quality thrust (i.e., a\npropulsive force). This example using RRRun, a d<\/em>FMS prerequisite, reclassifies from an OPC-III to an OPC-I with\nonly her self-discovery playing with the RRRun. The information provided to\nthis performer was the feeling of awkwardness and no thrust (Figure 6B) that\nshe rejected the task; yet, seen achieving the BMM,\nshe was classified an OPC-III. However, the comparison with a quality thrust\nduring the BMM of the left foot\n(Figure 6A) was assessed as an OPC-I, which helps to create, acquire, and\ncommunicate knowledge to the performer to discover the skill bi-laterally as an\nOPC-I (Figure 6C). The knowledge of what the researchers know and how the\nresearchers know it with respect to what the performer senses and then perceives requires future study for translating practice\ninto theory using FMS\nprerequisites with a BMM of an MJM\n2-joint system.<\/p>\n\n\n\n

Olympic Sprinting: Is\nThere a Hidden Skill?<\/em><\/strong><\/p>\n\n\n\n

Performers who\nsuccessfully hit the simultaneous 2-point crouch-down target configuration\nstarting from many possible unknown initial conditions at the toe-off\nconfiguration represent the hidden skill in which they self-discover a forward\ndynamic solution for the IVP to hit the known configured target with moderate\npredictability and functional variability from which to learn (5,24). This\ninvolves a low tolerance of error in the temporary assemblage of a coordinative\nstructure required in order to establish the first point for the 2-point BVP,\nwhich is necessary and sufficient to have at least one more point to hit a BMM target configuration at the next footstrike.\nHowever, theoretically critical information is likely missed by not identifying\nother configured targets as critical points between these 2 BVP points, which\ngenerate piecewise intervals of an inverse dynamic solution. Mathematically,\nhuman gait was modeled in 3-D space with 34 degrees of freedom as a piecewise\nfunction, and with a future goal to model running (9).<\/p>\n\n\n\n

Clinically, RRRun provides a dynamic\nvisual model of a piecewise function of intervals between steps. For example,\nrather than an interval between steps, heel-lift from whole-foot and toe-off\nare other points of interest theoretically on the same foot before the next\nfootstrike, especially because whole-foot contact is considered a sprinting\nerror; and therefore, heel-lift remains a debatable hidden skill. This debate\n(21) had already entered the distance running world showing that the minimally\nshod Tarahumara Indians during running used strikes at mid-foot (40%), forefoot\n(30%), and rear-foot (30%). The researchers\u2019 contention is that MJM at a key BMM moment of whole-foot contact as seen with\nOlympic sprint champions (Figure 8) approximates an optimal initial\nconfiguration of periodicity from which to sprint with a momentum-step directed\noptimally forward and up at the toe-off lean compared to sprinters who are\nlikely leaning too far forward with their momentum directed forward and down at\ntoe-off; and thus, the heel doesn\u2019t make contact with the ground (see Appendix A:\nThe Visual Search<\/em>).<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 8. Dynamic MJM whole-foot contacts with the track\nare seen at 100 meters for (A) Owens in 1936 and (B) Bolt in 2009; at 400\nmeters for (C) Van Niekerk in 2016; and at 300 meters for (D) Van Niekerk in\n2017 at the 56th Ostrava Golden Spike; (E) whole-foot contact is maintained.\nThese screenshots are used in accordance with the Fair Use Act only for\neducational and research purposes that add new information. They are not a\nsubstitute for their original use; and they are different from their intended\nuse and the nature of their copyrighted work.<\/p>\n\n\n\n

The Inverted U-Model<\/em><\/strong><\/p>\n\n\n\n

The concept of MJM, as\nwhole sub-systems contained within the larger body of FMS\nsystems, reveals hidden skills to be assessed and trained with creative,\nempirically observable d<\/em>FMS like\nRRStart and RRRun that offer theoretical conceptualization of hidden skill. The\nd<\/em>FMS is a tactic that provides a\ncomparison to other strategies that give meaning for the performer with respect\nto momentum in an optimal state of variability to organize chaotic behavior in\na more predictable manner over time. A hypothesis that involved human movement\nvariability was explained in 2013 by Stergiou et al. (38) with an inverted\nU-model \u201c\u2026 based on the idea that mature motor skills and healthy states are\nassociated with optimal movement variability that reflects the adaptability of\nthe underlying control system\u201d (p.96), which depicts chaotic systems in an\ninverted U-shaped relationship. In 2004, Shalizi et al (33) defined \u201c\u2026\ncomplexity as the amount of information for optimal statistical prediction\u201d\n(p.4). In 2015, Stephens (37) argued that complexity for complex systems is not\na measure of degrees of freedom, non-linear interactions, or a balance between\norder and disorder, but rather meaning and fitness for languages and biological\nsystems, respectively as distinguishing properties of complex systems.<\/p>\n\n\n\n

\"Figure<\/figure>\n\n\n\n

Figure 9. The inverted U-model of gross motor skills show a\nrelationship of low complexity for FMS and MJM compared to a greater complexity\nfor dFMS; and predictability is least for FMS and most for MJM with dFMS\nsomewhat likely.<\/p>\n\n\n\n

The researchers submit FMS, d<\/em>FMS,\nand MJM as another inverted U-shaped relationship (Figure 9) that exhibits\ngross motor skill predictability with respect to constraints applied to the\ndegrees of freedom of a system; such that FMS\npossess the least constraints, d<\/em>FMS\ndeal with some, and MJM have the most. Complexity is highest for 3-D d<\/em>FMS, which are reconfigured systems\ninvolving competing strategies and sensory input that adopt a new update rule\nwithin a given environment greater than the less complex old rules (37) of the\n3-D FMS and the sub-level of the\n2-D MJM configured system. The researchers propose that these competing\nstrategies update their rules during an observable motion in a certain dynamic\nstate towards a particular goal with something that the brain cannot feel \u2013\nmomentum \u2013 such that, there is a sense of smoothness, effortlessness,\nproficiency, grace, or power. The CNS experiences changes in momentum (i.e., a\nforce). This inability to feel momentum is a measure of complexity that the\nbrain must self-discover meaning of this phenomenon in the complex state of d<\/em>FMS reconfigured strategies as momentum\nevolves better and better with updated rules that aid the brain in choosing a\nnewly preferred running strategy in a state that did not exist originally,\nwhich is compared and understood with competing strategies\nof lesser complexity leading to a deeper understanding through perceptive\nlearning with bodily sensory inputs (17,22) and wellbeing (8,18).<\/p>\n\n\n\n

A Leading MJM Hypothesis <\/em><\/strong><\/p>\n\n\n\n

A leading joint\nhypothesis (LJH) was offered as an alternative theory (7) that permitted\ntransparency for the control of human movements to address the significant\nlimitations of the major human movement control theories that involve multiple\njoints in spite of their invaluable contributions. LJH is theorized on the\nnotion that the central nervous system exploits interaction torque involving\nthe linkages of several segments. Future research could be discovered in other\nanatomical units as a leading structure greater than the single joint as seen with the leading role of the hip-knee\nlinkage in cycle pedaling (32), which may also serve as leading structures\nbeyond the LJH of a single joint. Furthermore, MJM is suspected to signify a\npredictable occurrence of low complexity and minimal variability of hip-knee\ncoupling seen in running (9). The researchers propose the hip-knee linkage in\nMJM might also function as a prospective leading MJM hypothesis. Extending the\nscope of the LJH beyond a single joint, a leading MJM hypothesis with MJM and d<\/em>FMS may provide answers to know how to\nask questions to identify hidden skills and identify the set of worst first\nmoves. For example, does using the BMM\nof MJM for the key BVP points seen in the RRRun (Figure 7) provide a leading\nMJM hypothesis for IVP solutions theoretically; as well as for the BMM to assess performance clinically? The MJM and d<\/em>FMS are clinical assessments for\ntranslating practice into theory where future research is required to determine\nreliability and validity. This would establish performance readiness evaluation\nprocedures and injury risk assessment algorithms using early MJM tests and d<\/em>FMS interventions to prevent ignoring the signs or symptoms of\nmicrotraumatic events leading to misdirected forces (misuse), repetitive joint\nstressors (overuse), and misguided beliefs of \u201cno pain, no gain\u201d (abuse) not\nonly in the athlete but also for everyone.<\/p>\n\n\n\n

CONCLUSIONS<\/strong><\/p>\n\n\n\n

FMS prerequisites, which\nwere introduced and assessed epistemologically and algorithmically in OPC, offer\na scientific epistemology as a different scientific inquiry at the observable\nlevel of a pragmatic qualitative methodology that uses systems thinking for translating\npractice into theory by integrating mathematical and dynamical systems concepts\nwith belief systems in physical education as illustrated with running. By\naddressing the what is known questi<\/em>on\nthat leads to ask why and how, this approach moves toward optimal health biomechanically\nand a wellbeing sense with the epistemic and non-epistemic values that support the\nOPC value-judgments of the FMS\nprerequisites to promote learning for physical educators and healthcare\nprofessionals; as well as, to challenge the belief systems of students,\nathletes, or community-at-large involving their perception, motor actions, and\nbodily senses.<\/p>\n\n\n\n

A major limitation of this study is that it\nrelies on observable data without using biomechanical equipment; however, these\nMJM and d<\/em>FMS observations represent\nnovel outcomes that should stimulate theoreticians to contemplate and mathematicians\nto model the inverted U-model and the leading MJM hypothesis of the\nunobservables derived from MJM and d<\/em>FMS\nthat have not yet been well expressed.<\/p>\n\n\n\n

FMS prerequisites will help\nto 1) prevent undesirable chaotic behavior by pragmatically solving IVP for an\noptimal, self-organizing task like the crouch-down running strategies that\nexploits the momentum-step to optimize motion (e.g., step-length and\ndirection), 2) discover newly preferred steady states of the system, 3) assess\nthe trust of the system, including the belief system of the performer, to rely\non its initial conditions, 4) encourage other researchers and practitioners to design\nother MJM and d<\/em>FMS as FMS prerequisites to provide very early detection\nof flawed gross motor skill development before manifesting into the signs and\nsymptoms of injury or poor performance, which are the rudimentary\nconfigurations for injury risk assessments and performance readiness\nevaluations, and 5) provide new leadership with key stakeholders to pursue a\nnew direction for physical education which has failed the children with respect to\npedagogical strategies to optimize the development, learning, and testing of\nfundamental movement skills as a foundation for sport, as well as a sense of\nwellbeing and moving towards optimal heath biomechanically across a lifespan.<\/p>\n\n\n\n

APPLICATIONS IN SPORT<\/strong><\/p>\n\n\n\n

This original research methodology of sorting out observer-performer interactions acquires what the observer (physical education teacher, coach, health professional, parent) needs to know and learn about the aptitude of a performer\u2019s fundamental movement skills (FMS) as illustrated with running, and what performers (athletes, students, community-at-large) need to feel and trust about their belief system to promote sensory and perceptive learning where novel FMS prerequisites discover hidden skills leading to optimal FMS development. The ultimate goal is to translate practice into theory that leads to a paradigm shift for prevention of sports injuries and flawed performances by means of moving towards optimal health biomechanically and wellbeing.<\/p>\n\n\n\n

ACKNOWLEDGMENTS<\/strong><\/p>\n\n\n\n

The first author wishes to thank Professor H. Michael Lacker, MD, PhD for many years of friendship and collaboration. The researchers are grateful to Gladys Davis, Head of School, for her support with access to K-5 students. Screenshots in Figure 8 showing whole-foot contact for Jesse Owens winning the 1936 Olympics, Usain Bolt in Berlin at the 2009 World Athletics Championships breaking the 100 meter world record, and Wayde van Niekerk\u2019s 400 meter world record at the 2016 Olympic Games and his 300 meter world record at the 56th Ostrava Golden Spike, IAAF World Challenge on June 28, 2017 are used in accordance with the Fair Use Act only for educational and research purposes that add new information, and not a substitute for original use. They are different from their intended use, the nature of their copyrighted work; and they are provided on the internet at no expense.<\/p>\n\n\n\n

CONFLICT OF INTEREST<\/strong><\/p>\n\n\n\n

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<\/p>\n\n\n\n

REFERENCES<\/strong><\/p>\n\n\n\n

  1. Anson, G., Elliott, D., & Davids, K. (2005). Information processing and constraint-based views of skill acquisition: Divergent or complimentary? Motor Control, 9<\/em>, 217-241. Retrieved from https:\/\/pdfs.semanticscholar.org\/48ec\/8414b9804b3d23574cc9693fc45c0295e59e.pdf<\/li>
  2. Barnett, L. M., Stodden, D., Cohen, K. E., Smith, J. J., Lubans, D. R., Lenoir, M., Iivonen, S., Miller, A. D., Laukkanen, A., Dudley, D., Lander, N. J., Brown, H., & Morgan, P. J. (2016). Fundamental movement skills: An important focus. Journal of Teaching in Physical Education, 35<\/em>(3), 219-225. doi.org\/10.1123\/jtpe.2014-0209<\/li>
  3. Bernstein, N. A. (1967). The co-ordination and regulation of movements. Oxford: Pergamon Press.<\/li>
  4. Darlaston-Jones, D. (2007). Making connections: The relationship between epistemology and research methods. The Australian Community Psychologist, 19<\/em>(1), 19-27. Retrieved from https:\/\/groups.psychology.org.au\/Assets\/Files\/Darlaston-Jones_19(1).pdf <\/li>
  5. Davids, K., Glazier, P., Ara\u00fajo, D., & Bartlett, R. (2003). Movement systems as dynamical systems: The functional role of variability and its implications for sports medicine. Sports Medicine, 33<\/em>(4), 245-260. doi:10.2165\/00007256-200333040-00001<\/li>
  6. Dickmann, S., & Peterson, M. (2013). The role of non-epistemic values in engineering models. Science and Engineering Ethics, 19<\/em>, 207-218. Retrieved from https:\/\/link.springer.com\/content\/pdf\/10.1007%2Fs11948-011-9300-4.pdf <\/li>
  7. Dounskaia, N. (2010). Control of human limb movements: The leading joint hypothesis and its practical applications. Exercise Sport Sciences Reviews, 38<\/em>(4), 201-208. doi:10.1097\/JES.0b013e3181f45194<\/li>
  8. Faust, H. S. (2013). A cause without an effect? Primary prevention and causation. Journal of Medicine and Philosophy, 38<\/em>, 539-558. doi:10.1093\/jmp\/jht039 <\/li>
  9. Felis, M. L., & Mombaur, K. (2016). \u201cSynthesis of full-body 3-d human gait using optimal control methods,\u201d in 2016 IEEE International Conference on Robotics and Automation (ICRA) <\/em>(Stockholm: IEEE), 1560\u20131566<\/li>
  10. Flor\u00eda, P., S\u00e1nchez-Sixto, A., Ferber, R., & Harrison, A. J. (2018). Effects of running experience on coordination and its variability in runners. Journal of Sports Sciences, 36<\/em>(3), 272-278. doi:10.1080\/02640414.2017.1300314      <\/li>
  11. Frost, D. M., & Cronin, J. B. (2011). Stepping back to improve sprint performance: A kinetic analysis of the first step forwards. Journal of Strength and Conditioning Research, 25<\/em>(10), 2721-2728. doi:10.1519\/JSC.0b013e31820d9ff6<\/li>
  12. Glazier, P. S., & Robins, M. T. (2012). Comment on \u201cUse of deterministic models in sports and exercise biomechanics research\u201d by Chow and Knudson (2011). Sports Biomechanics 11<\/em>(1), 120-122. doi:10.1080\/14763141.2011.650189<\/li>
  13. Grecic, D. (2017). Making sense of skill \u2013 a personal narrative of becoming more skilled at skill. Journal of Qualitative Research in Sports Studies<\/em>, 11(1), 33-48. Retrieved from https:\/\/works.bepress.com\/clive_palmer\/147\/<\/li>
  14. Grecic, D., & Collins, D. (2013). The epistemological chain: Practical applications in sports, Quest, 65<\/em>(2), 151-168. doi: 10.1080\/00336297.2013.773525           <\/li>
  15. Greene, P. H. (1972). Problems of organization of motor systems. In R. Rosen & F. Snell (Eds.), Progress in Theoretical Biology, Vol. 2<\/em>. (pp 303\u2013338). Academic Press, New York<\/li>
  16. Hamill, J., & Gruber, A. H. (2017). Is changing footstrike pattern beneficial to runners? Journal of Sport and Health Science, 6<\/em>(2), 146-153. doi.org\/10.1016\/j.jshs.2017.02.004<\/li>
  17. Hayek, F. A. (1976). The Sensory Order<\/em> (paperback edition.). The University of Chicago Press, Chicago, Illinois<\/li>
  18. Khushf, G. (2013). A framework for understanding medical epistemologies. Journal of Medicine and Philosophy, 38<\/em>, 461-486. doi:10.1093\/jmp\/jht044<\/li>
  19. Kraan, G. A., van Veen, J., Snijders, C. J., & Storm, J. (2001). Starting from standing: why step backwards? Journal of Biomechanics, 34<\/em>(2), 211-215. doi: 10.1016\/s0021-9290(00)00178-0<\/li>
  20. Latash, M. (2016). Biomechanics as a window into the neural control of movement. Journal of Human Kinetics, 52<\/em>, 7-20. doi: 10.1515\/hukin-2015-0190<\/li>
  21. Lieberman, D. E. (2014). Strike type variation among Tarahumara Indians in minimal sandals versus conventional running shoes. Journal of Sport and Health Science 3<\/em>(2), 86-94. doi.org\/10.1016\/j.jshs.2014.03.009<\/li>
  22. Light, R. (2008). Complex learning theory \u2013 Its epistemology and its assumptions about learning: Implications for physical education. Journal of Teaching in Physical Education, 27<\/em>, 21-37. Retrieved from http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.457.9365&rep=rep1&type=pdf <\/li>
  23. Ma\u2019ayan A. (2017). Complex systems biology. Journal of the Royal Society Interface<\/em> 14: 20170391, 1-9. doi.org\/10.1098\/rsif.2017.0391<\/li>
  24. Manoel, Ede. J., & Connolly, K. J. (1995). Variability and the development of skilled actions. International Journal of Psychophysiology, 19<\/em>(2), 129-147. doi.org\/10.1016\/0167-8760(94)00078-S<\/li>
  25. Mayer-Kress, G., Liu, Yeou-Teh, & Newell, K. M. (2006). Complex systems and human movement. Complexity, 12<\/em>(2), 40-51. doi.org\/10.1002\/cplx.20151<\/li>
  26. Moore, I. S. (2016). Is there an economical running technique? A review of modifiable biomechanical factors affecting running economy. Sports Medicine, 46<\/em>(6), 793-807. doi:10.1007\/s40279-016-0474-4<\/li>
  27. Nakamoto, H., Mori, S., Ikudome, S., Unenaka, S., & Imanaka, K. (2015). Effects of sports expertise on representational momentum during timing control. Attention, Perception, & Psychophysics, 77<\/em>, 961-971. doi:10.3758\/s13414-014-0818-9<\/li>
  28. Norwich, K. H. (2010). Le Chatelier\u2019s principle in sensation and perception: fractal-like enfolding at different scales. Frontier in Physiology, 28<\/em>, 1-7. doi.org\/10.3389\/fphys.2010.00017<\/li>
  29. Pavei, G., Seminati, E., Cazzola, D., & Minetti, A. E. (2017). On the estimation accuracy of the 3d body center of mass trajectory during human locomotion: Inverse vs. forward dynamics. Frontiers in Physiology, 8<\/em>, 1-13. doi: 10.3389\/fphys.2017.00129<\/li>
  30. Philp, F., Blana, D., Chadwick, E. K., Stewart, C., Stapleton, C., Major, K., & Pandyan, A. D. (2018). Study of the measurement and predictive validity of the functional movement screen. BMJ Open Sport & Exercise Medicine, 4<\/em>, 1-7. doi:10.1136\/bmjsem-2018-000357<\/li>
  31. Polanyi, M. (1974). Personal knowledge: Towards a post-critical philosophy. (paperback edition). The University of Chicago Press, Chicago, Illinois<\/li>
  32. Raasch, C. C., & Zajac, F. E. (1999). Locomotor strategy for pedaling: muscle groups and biomechanical functions. Journal of Neurophysiology, 82<\/em>(2), 515-525. doi:10.1152\/jn.1999.82.2.515<\/li>
  33. Shalizi, C. R., Shalizi, K. L., & Haslinger, R. (2004). Quantifying self-organization with optimal predictors. Physical Review Letters, 93<\/em>(11), 1-4. doi.org\/10.1103\/PhysRevLett.93.118701. Retrieved from https:\/\/arxiv.org\/pdf\/nlin\/0409024.pdf<\/li>
  34. Shea, C. H., & Wulf, G. (2005). Schema theory: A critical appraisal and reevaluation. Journal of Motor Behavior, 37<\/em>(2), 85-101. Retrieved from http:\/\/gwulf.faculty.unlv.edu\/wp-content\/uploads\/2014\/05\/Shea_Wulf_2005.pdf<\/li>
  35. Skraba, Z. P. (2016, September, 1). Stride length vs stride frequency in the 400 metres. Blog zigapskraba<\/em>. Retrieved from https:\/\/zigapskraba.com\/2016\/09\/01\/stride-length-vs-stride-frequency-in-the-400-metres\/<\/li>
  36. Slawinski, J., Houel, N., Bonnefoy-Mazure, A., Lissajoux, K., Bocquet, V., & Termoz, N. (2017). Mechanics of standing and crouching sprint starts. Journal of Sports Sciences, 35<\/em>(9), 858-865. doi:10.1080\/02640414.2016.1194525<\/li>
  37. Stephens, C. R. (2015). What isn\u2019t complexity? Nonlinear Sciences > Adaptation and Self-Organizing Systems <\/em>(nlin.AO), Cornell University, (2) 1-26. Retrieved from https:\/\/arxiv.org\/ftp\/arxiv\/papers\/1502\/1502.03199.pdf<\/li>
  38. Stergiou, N., Yu, Y., & Kyvelidou, A. (2013). A perspective on human movement variability with applications in infancy motor development. Kinesiology Review, 2<\/em>, 93-102. doi:10.1123\/krj.2.1.93<\/li>
  39. Termoz, N., Lissajoux, K., & Slawinski, J. (2015). Kinetic analysis of different running starts: Impact on forward center of mass acceleration and performance. 33rd International Conference on Biomechanics in Sports<\/em>, Poitiers, France, June 29 – July 3, 2015. F. Colloud, M. Domalain, & T. Monnet (Eds.). Retrieved from https:\/\/ojs.ub.uni-konstanz.de\/cpa\/article\/view\/6498<\/li>
  40. Thelen, E. & Smith, L. B. (2005). Dynamic systems theories, Handbook, Chapter 6, 258-312. Retrieved from https:\/\/cogdev.sitehost.iu.edu\/labwork\/handbook.pdf<\/li>
  41. Turvey, M. T., (1990). Coordination. American Psychologist<\/em>, 45(8), 938-953. Retrieved from https:\/\/doi.org\/10.1037\/0003-066X.45.8.938<\/li>
  42. Verhoeff, R. P., Knippels, M-C. P. J., Gilissen, M. G. R., & Boersma, K. T. (2018). The theoretical nature of systems thinking. Perspectives on systems thinking in biology education. Frontiers in Education, 3<\/em>(40), 1-11. doi.org\/10.3389\/feduc.2018.00040<\/li>
  43. Wenning, C. J. (2009). Scientific epistemology: How scientists know what they know. Journal of Physics Teacher Education Online, 5<\/em>(2), 3-15. Retrieved from https:\/\/pdfs.semanticscholar.org\/8854\/19ef96c2a5abec87f7dd53dbd258f78b9427.pdf?_ga=2.120836744.1617789758.1581169402-1044859988.1572144347<\/li>
  44. Whiteside, D., Deneweth, J., Pohorence, M. A., Sandoval, B., Russell, J. R., McLean, S. G., Zernicke, R. F., & Goulet, G. C. (2016). Grading the functional movement screen: A comparison of manual (real-time) and objective methods. Journal of Strength and Conditioning Research, 30<\/em>(4), 924-933. Retrieved from https:\/\/pdfs.semanticscholar.org\/e295\/52e4da590cffadaa33cb7b48063577bc519f.pdf<\/li>
  45. Wise, S. P., & Shadmehr, R. (2002). Motor control. In Vilayanur Ramachandran (Ed-in-Chief), Encyclopedia of the Human Brain (p.137-157). Elsevier Science<\/em>. Retrieved from https:\/\/pdfs.semanticscholar.org\/3032\/af138c2fa5f7acedaa47bbe7f3e07f8162ec.pdf?_ga=2.75013522.1617789758.1581169402-1044859988.1572144347<\/li>
  46. Wulf, G. (2013). Attentional focus and motor learning: a review of 15 years. International Review of Sport and Exercise Psychology, 6<\/em>(1), 77-104. Retrieved from http:\/\/gwulf.faculty.unlv.edu\/wp-content\/uploads\/2018\/11\/Wulf_AF_review_2013.pdf<\/li>
  47. Zajac, F. E. (1993). Muscle coordination of movement: A perspective. Journal of<\/em> Biomechanics, 26<\/em>, Suppl. 1, 109-124. doi:10.1016\/0021-9290(93)90083-q<\/li><\/ol>\n\n\n\n

    Appendix A<\/strong><\/p>\n\n\n\n

    The <\/em><\/strong>Observer\u2014Performer Classification<\/em><\/strong><\/p>\n\n\n\n

    Dealing with these epistemological\nquestions to construct knowledge and understanding from the experiences derived\nwith the interaction of the observer and the performer, the researchers begin a\nqualitative methodology with an Observer-Performer\nClassification (OPC) for grouping observed human movement skilled actions into\none of four categories. OPC is a two-dimensional taxonomy that possesses two\ngeneral characteristics; namely, an internal perception of motion experienced\nby the performer as preferred or not, and an external assessment of that\nperformance as witnessed by the observer as acceptable or not. Just because a\nmotor action is accepted as correct by the observer and preferred by the\nperformer, does not make it true. Whatever is believed by the observer and the\nperformer, the epistemology perspective asks how can they find out what can be\nknown about such a perceptual experience shaping their belief systems as witnessed\nby the observer and felt by the performer. Briefly, an OPC-I is that the\nobserver agreed with the preferred behavior of the performer, who now\nacknowledged feeling ready for practice with a given task where both are\nassumed to be correct towards a wellbeing experience and knowledge if\nperformance is enhanced within a reasonable period of time; otherwise, it is\nreclassified OPC-IV. An OPC-II is observer disapproval assumed to be correct\nand performer approval is assumed to be incorrect. However, knowledge and a\nwellbeing experience are acquired by providing the performer with show-and-tell\ninformation that results with enhanced performance as a reclassified OPC-I;\notherwise, it is reclassified OPC-IV. It is assumed that the performer\npossesses the coordinative dynamics that is capable of a different kinematic\nmotor action; however, the performer has yet to experience it because of not\nknowing what to control kinematically. An OPC-III is observer approval assumed\nto be correct and performer disapproval is assumed to be incorrect. However,\nknowledge and a wellbeing experience are acquired by providing the performer\nwith drill-&-feel tactics that result with enhanced performance as a\nreclassified OPC-I; otherwise, it is reclassified OPC-IV. It is assumed that\nthe performer does not possess the coordinative dynamics concomitant\nwith the requisite flexibility and biological requirements that are necessary\nand sufficient for the motor action. Caution is advised with OPC-III value\njudgments that in reality are OPC-IV because the observer is wrong when there\nis: 1) a physiological or a psychological deficit, 2) an undiagnosed injury or\nmicrotrauma, 3) a compensatory action that disguises error, 4) functional\nvariability that is mistaken as error, or 5) an unqualified, inexperienced, or\nbiased observer for a given action or task. An OPC-IV is disapproval that\nis assumed to be correct by\nboth the observer and the performer. However, both knowledge about what the\nbody senses and learns (22), as well as, a wellbeing experience (8,18) are\nacquired by providing the performer with FMS\nprerequisites (e.g., MJM; d<\/em>FMS) that\nresult with enhanced performance as a reclassified OPC-I; otherwise, research\nis recommended. The researchers argued that the FMS\nprerequisites identify hidden skills, optimize momentum, utilize gravity, and\nexplore the notion of worst first move to avoid misuse, overuse, or abuse with\nrespect to injury or poor performance by moving toward optimal health\nbiomechanically and epistemologically. Caution is advised with OPC-IV when a\nmedical referral or other prerequisites (e.g.; nutrition, physiology;\npsychology) are warranted.<\/p>\n\n\n\n

    OPC assignments and their key\nepistemic assumptions for classifying a given motor action is the process by\nwhich it can be discovered: how do you know what you know? This approach deals\nwith the scientific epistemological question regarding the nature of the\nvalue-judgment relationship between the observer and what can be known from\nwhat is observed and how the researchers teach and study this by interacting\nwith what the performer senses and believes that may be true or false. Physical\neducation teachers, coaches, athletic trainers, physical therapists, sports\nmedicine doctors are among those professionals faced with injuries or poor performances\nat all skill levels. When observing any skill level, especially the Olympic or\nprofessional athlete, they are challenged by the dilemma as to what\nobservations provide meaningful information to the athlete. The researchers\nillustrate this epistemic framework with some FMS\nprerequisites to discover preferred behaviors that reveal hidden skills for\nrunning and squatting with an original study using these four independent tasks\nof different dimensions as a method to reveal what the researchers know that\noffers translating\npractice into theory via these unique FMS\nprerequisites; namely, MJM and d<\/em>FMS.<\/p>\n\n\n\n

    The dynamical systems perspective<\/em><\/strong><\/p>\n\n\n\n

    Skilled FMS\nactions like running involving these biological systems compose many elements\nthat require both control and coordination. Biological systems involve\ncoordinating many different component parts that\nconsist of about 100 mechanical degrees of freedom, characterizable by position\nand velocity, yield a state space of, at least, 200 dimensions (41). Hundreds\nof muscles operating as linear actuators (47) enable movements and maintain\npostures involving kinetic and potential energies within a complex, interactive\nneuro-musculo-skeletal system. Fundamental to position and velocity are the\ngeneralized coordinates that define the configuration space of the physical\nsystem often modeled as a particle system that represents the whole (i.e.;\ncenter of mass of the body), and the concept of self-organization. Dynamical\nsystems emerge without prespecification where the patterns organize themselves\nin a sequence of complexity to simplicity to complexity (40). Running\u2019s\ncomplexity is low because it possesses a simplicity from which a vast number of\npatterns can be randomly selected and organized by very young children; yet its\npotential to evolve optimally remains unpredictable. Therefore, can a system\u2019s\npreferred behaviors (see Task 1) be reduced to a lesser complexity of highly\npredictable FMS prerequisites\nto reveal hidden skills with MJM (see Task 2) to identify key configurations\nand then explain behavior? Can deficient hidden skills be revealed for injury\nrisk assessments and performance readiness evaluations with tactics as d<\/em>FMS (see Tasks 3 & 4) of greater\ncomplexity, yet fairly predictable to skill development of a whole system\n(e.g., a runner)? <\/p>\n\n\n\n

    The researchers use dynamical systems\nconcepts to provide systems thinking in physical education that may translate\nfrom practice into theory. The complexity and the multi-dimensionality of the\nsensory-motor system solve Bernstein\u2019s degrees of freedom problem (3,41) by\ntemporary assemblages, which are coordinative structures of muscle complexity\nsuch that skill involves adding and removing constraints that reduce and\nincrease the degrees of freedom, respectively. <\/p>\n\n\n\n

    The dynamical systems theory\nperspective describes transitional relationships among the parts of a whole\nwhile it fundamentally struggles with two major qualitative problems involving\nthe chaotic behavior of a system (e.g., a performer): 1) discovering steady\nstates of the system and 2) assessing the trust of the system to rely on its\ninitial conditions (e.g., segmental position and its velocity). For the system\nto discover a steady state, the dynamic system theoretical argument claims the\nsystem is attracted from a nearby state to a steadier state. The more complex\nthe system, the more difficult it is to assess its dependence on initial\nconditions. Modeling complex systems fundamentally strive to resolve collective\nbehaviors that emerge from the relationship of their component parts and their\nenvironment during a state of flux.<\/p>\n\n\n\n

    Modeling a system undergoing\ntransitions often requires mathematically solving an initial value problem\n(IVP) where the differential equation is an evolution equation specifying how\nthe system evolves over time given its initial conditions of a movement\nfunction. Often, these conditions are the position of a configured system and\nthe initial velocities of each configured part. If these conditions are known,\nthen the IVP answers the question of aim in order how to hit the target.\nHowever, if the initial conditions are unknown, then the differential equations\nare solved as boundary value problems (BVP) with a set of additional\nconstraints, called the boundary conditions. The BVP answers the question: Does\naiming from a given starting point hit the target? Either an assumed starting\npoint or target could be erroneous, resulting in no solution.<\/p>\n\n\n\n

    A solution for a differential\nequation is neither a single value nor necessarily a single solution. In fact,\nit can have multiple solutions, as well as no solution. If there is a solution,\nit is a function, which is a rule regarding inputs that are the initial\nconditions or boundary conditions of an IVP or a BVP, respectively. If the\ninitial conditions of the IVP are unknown (see Task-1), then given a two-point\nBVP with boundary conditions, the problem is likely to have a solution within a\ncontinuous domain provided all the inputs are\navailable to perform the output. This means there is a movement function that\nindicates how to perform an act that is constrained to behave like the\nidealization of a mechanism (see Task-2). Constraining a 2-joint system to\nbehave like a robotic MJM provides a means to construct known configurations\n(i.e., coordinative structures) of reduced complexity and a\nbiomechanical-marker (BMM) for d<\/em>FMS of greater complexity from which to\nidentify the hypothetical worst first move or a structural problem. The\nobjective of this process is to reveal and self-discover hidden skills with MJM\nand d<\/em>FMS that evaluate and organize a\nsteady state of stability and adaptability to learn and perform well during\nstarting a movement (see Task-3), and during the dynamic stability of the\nmotion itself to discriminate perceptive capability clinically (see Task-4).<\/p>\n\n\n\n

    In the dynamic\nperspective, some control parameter must be changing in order for the stability\nof an existing organized system to be disrupted, eliminated, and replaced by a\nnew organization. The key is to identify one or more of the appropriate\ncollective variables that identify a few modes of preferred behavior (i.e., the\nstable attractor states) of the system. Worthy information about hopeful\ncollective variables or a potential BMM\nis attained when the system shifts abruptly from one coordinative mode to\nanother: that is, from one attractor state to another. Upon identifying the\ncollective variables, these phase transitions are seen as qualitative changes\nin behavior where order loses one preferred behavior and regains a more\npreferred behavior or a worthy behavior. A behavior that is worthy may not be\nan ideal solution of the precision robot, but rather a realistic solution that\nbest fits a restricted state of one\u2019s intrinsic dynamics.<\/p>\n\n\n\n

    The Visual Search<\/em><\/strong><\/p>\n\n\n\n

    The researchers conducted a YouTube\nvisual search of Olympic sprinters as illustrated in Figure 8 with key video\nscreenshots in accordance with the Fair Use Act for educational and research\npurposes. Video evidence of whole-foot contact were seen for the 100-meter\nworld records of Jesse Owens (Figure 8A) in 1936 Olympic Games and Usain Bolt\n(Figure 8B) in 2009; as well as, Wayde Van Niekerk\u2019s world records for the 2016\nOlympic Games in the 400 meter race (Figure 8C) and for his 300-meter sprint\n(Figure 8D) at the 2017 IAAF World Challenge.<\/p>\n\n\n\n

    From the perspective of the visual\nsearch, the researchers clinically investigated the controversial notion that\nsprinting only impacts the forefoot of an Olympic sprinter. Whole-foot contact\noccurs in a few milliseconds as seen with Olympian Wayde van Niekerk (Figure\n8D) and maintained prior to heel-lift (Figure 8E). This observation is further\ncomplicated because heel contact with the ground is considered a sprinting\nerror; however, this visual search is empirical evidence, which in theory is\nthe inverse approach where body configurations can be used both clinically and\ntheoretically as input but only at a discrete set of target times and not the\nentire motion. Mathematically, each phase of motion can be solved independently\nas separate 2-point BVP solutions that are concatenated to describe the motor\ntask (beyond the scope of this paper). Whole-foot contact with evidence of the BMM is hypothesized exploiting dynamic stability of\nan effective propulsive force to properly direct and ideally optimize momentum.\nThese screenshots of van Niekerk\u2019s 300 world record are empirical evidence of\nthe BMM at whole-foot contact,\nwhich the researchers hypothesize optimizes the momentum-step; thereby,\nincreasing his step length. This hypothesis is somewhat supported by a\ndescriptive analysis investigating stride length comparing van Niekerk to\nMichael Johnson, the former 300-meter and 400-meter record holder, showed that\nvan Niekerk\u2019s 163 steps averaged 23.8 cm more per step than Johnson\u2019s 180.5 steps (35).<\/p>\n","protected":false},"excerpt":{"rendered":"

    Authors: Robert P. Narcessian and Janet M. Leet Corresponding Author:Robert […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_options":[]},"categories":[580,295],"tags":[1575,1574,1572,1573,318,409],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4btio-1NT","jetpack-related-posts":[{"id":66,"url":"https:\/\/thesportjournal.org\/article\/results-and-recommendations-of-the-world-summit-on-physical-education\/","url_meta":{"origin":6937,"position":0},"title":"Results and Recommendations of the World Summit on Physical Education","date":"February 13, 2008","format":false,"excerpt":"Document presented on behalf of the World Summit on Physical Education by the International Council of Sport Science and Physical Education for MINEPS III Introduction Over 250 delegates from 80 countries, representing governments, inter-governmental and non-governmental organizations (NGO), and academic institutions attended the World Summit on Physical Education (Berlin, November\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":1508,"url":"https:\/\/thesportjournal.org\/article\/physical-activities-and-their-relation-to-physical-education-a-200-year-perspective-and-future-challenges\/","url_meta":{"origin":6937,"position":1},"title":"Physical Activities and Their Relation to Physical Education: A 200-Year Perspective and Future Challenges","date":"January 27, 2014","format":false,"excerpt":"Submitted by Suzanne Lundvall and Peter Schantz. 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We at The Sport Journal feel the views expressed in this article are important enough to republish for our\u2026","rel":"","context":"In "Contemporary Sports Issues"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":54,"url":"https:\/\/thesportjournal.org\/article\/analysis-of-selected-physical-and-performance-attributes-of-the-united-states-olympic-team-handball-players-preliminary-study\/","url_meta":{"origin":6937,"position":2},"title":"Analysis of Selected Physical and Performance Attributes of the United States Olympic Team Handball Players: Preliminary Study","date":"February 11, 2008","format":false,"excerpt":"Submitted by: Brian Bergemann, Ph.D. During the Spring of 1995, prior to the Olympic Games in Atlanta, the United States Team Handball team and coaches came to the United States Sports Academy in Daphne, AL for testing. Dr. Thomas P. Rosandich, president of the U.S. Team Handball Federation, and the\u2026","rel":"","context":"In "Sports Coaching"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":5024,"url":"https:\/\/thesportjournal.org\/article\/the-examination-of-research-related-anxiety-of-students-taking-master-and-doctorate-degree-in-the-field-of-physical-education-and-sports\/","url_meta":{"origin":6937,"position":3},"title":"The Examination of Research-Related Anxiety of Students Taking Master and Doctorate Degree in the Field of Physical Education and Sports","date":"April 20, 2017","format":false,"excerpt":"Authors: Ender SENEL (1), Mevlut YILDIZ (1), Mehmet ULAs (2), Hasan SAHAN (1) Mugla Sitki Kocman University, Faculty of Sports Sciences, Turkey. (2) Mehmet Akif Ersoy University, School of Physical Education and Sport, Turkey. (3) Akdeniz University, Faculty of Sport Sciences, Turkey. Corresponding Author: Ender SENEL Mugla Sitki Kocman University,\u2026","rel":"","context":"In "Commentary"","img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":8414,"url":"https:\/\/thesportjournal.org\/article\/rowing-performance-following-a-single-teaching-session-in-school-children\/","url_meta":{"origin":6937,"position":4},"title":"Rowing Performance Following a Single Teaching Session in School Children","date":"November 25, 2022","format":false,"excerpt":"Authors: Giovanni Ficarra1, Fabio Trimarchi1, Alessandra Bitto2, Debora Di Mauro1 1Department of Biomedical and Dental Sciences and Morphological and Functional Sciences, 2Department of Clinical and Experimental Medicine, University of Messina, c\/o AOU Policlinico G. Martino, Via C. Valeria, Gazzi, 98125, Messina, Italy. Corresponding Author: Prof. Alessandra Bitto, MD, PhD Department\u2026","rel":"","context":"In "Sport Education"","img":{"alt_text":"","src":"https:\/\/i0.wp.com\/thesportjournal.org\/wp-content\/uploads\/2022\/11\/Table-1-Ficarro-2022.jpg?resize=350%2C200&ssl=1","width":350,"height":200},"classes":[]},{"id":8156,"url":"https:\/\/thesportjournal.org\/article\/relationships-between-bmi-and-self-perception-of-adequacy-in-and-enjoyment-of-physical-activity-in-youth-following-a-physical-literacy-intervention\/","url_meta":{"origin":6937,"position":5},"title":"Relationships Between BMI and Self-Perception of Adequacy in and Enjoyment of Physical Activity in Youth Following a Physical Literacy Intervention","date":"March 11, 2022","format":false,"excerpt":"Authors: Brandi M. Eveland-Sayers1, Andy R. Dotterweich1, Alyson J. Chroust2, Abigail D. Daugherty3, and Kara L. 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