KINEMATICAL CHARACTERISTICS OF BICYCLE KICK AND SIDE VOLLEY IN SOCCER

INTRODUCTION: There exist various techniques for successfully gaining goals: maximal instep kick, bicycling kick and/or side volley. However, due to test constraints, difficulty in multi-dimensional signal exploration and the complexity of total body control, there is hardly any scientific study that describes bicycle kick and side volley (Shan & Westerhoff, 2005). The current study tried to address this deficiency by 1) providing 3D kinematical characteristics of these two techniques using a 15-segmental full body model and 2) exploring possible parameters for quantitative evaluations of the kick quality

Challenges and Future of Wearable Technology in Human Motor-Skill Learning and Optimization

Learning how to move is a challenging task. Even the most basic motor skill of walking requires years to develop and can quickly deteriorate due to aging and sedentary lifestyles. More specialized skills such as ballet and acrobatic kicks in soccer require “talent” and years of extensive practice to fully master. These practices can easily cause injuries if conducted improperly. 3D motion capture technologies are currently the best way to acquire human motor skill in biomechanical feedback training. Owing to their tremendous promise for a plethora of applications, wearable technologies have garnered great interest in biofeedback training. Using wearable technology, some physical activity parameters can be tracked in real time and a noninvasive way to indicate the physical progress of a trainee. Yet, the application of biomechanical wearables in human motor-skill learning, training, and optimization is still in its infant phase due to the absence of a reliable method. This chapter elaborates challenges faced by developing wearable biomechanical feedback devices and forecasts potential breakthroughs in this area. The overarching goal is to foster interdisciplinary studies on wearable technology to improve how we move

HOW TOUGH IS IT TO REPEATEDLY HIT THE BALL IN GOLF?

Golf is an increasingly popular sport, whose most challenging skill is the driver swing. There have been a large number of studies characterizing golf swings, yielding insightful instructions on how to successfully structure the swing. Achieving a sub 18 handicap is no longer the primary concern for golfers. Instead, players are now most troubled by a lack of consistency during swing execution. The goal of this study is to determine how to consistently execute repeated quality golf swings. By characterizing both successful and failed swings of 22 experienced golfers, we aim to identify swing parameters that are most sensitive and/or prone to motor control variations. We specifically report on five distinct problem areas, as well as provide suggestions for how to address these problems

THE CHARACTERISTICS OF FEMALE SOCCER KICKING REVEALED BY 3D KINEMATICS AND ELECTROMYOGRAPHY

Soccer is the mosl popular sport in the world' and rapidly becoming one of the most popular sports in North America. Despite its popularity, little research has been done to facilitate the rapid demand of quantitative findings. Even less attention is being paid to the fact that females now make up almost half the players worldwide. This study initiates a research on female soccer kicking using state-of-the-art technology. The high-tech unit consists of a 3D motion capture system with 9 high-speed cameras (120 Hz) and wireless electromyography (EMG) collection. The results revealed that a) Elite subjects combined the f1exion and extension of the hip, knee and ankle joint to perform the kick while novice subjects primarily used the knee to generate momentum; b) elite group showed a significant higher EMG intensity

DEVELOPMENT OF A REAL-TIME BIOFEEDBACK TOOL FOR MARTIAL ARTS COACHING PRACTICE

Power and neural response are two vital elements in martial arts striking. Currently, there are no practical methods exist to present these aspects to practitioners in a training environment. Our study has developed one. Our method consisted of an optical signal system, EMG and 3D motion capture. The feedback provided was generated by a selfdeveloped dynamic calculation programs using kinematics and EMG data as input. The results showed that our system provided both total power and its components (i.e. linear & angular) of a striking as well as the related response time. Since the method offers feedback of power intensity, attack accuracy, central and peripheral reaction time to practitioners in a quasi-training environment, it has great potential to become a real-time biofeedback tool in practice for increasing training efficiency and effectiveness

Wie kann die dynamische Festkörper-modellierung beim motorischen Lernen behilflich sein? Fertigkeitserwerb mit hilfe dynamischer Modellierung

The purpose of this research project was to bridge the gap between motion analysists and athletes and coaches by establishing a platform for the communication amongst the three parties. The first part of this project depicted that: 1) differences amongst the external view (motion analysists), internal sight (athletes) and internal sight from external view (coaches) were caused by the inertial (environment-fixed) and the non-inertial (body-fixed) system; 2) joint rotations were not identical with the muscular moment, therefore, passive rotations can occur; 3) critical phases in a skill control, which can be revealed by using modeling simulation, should be emphasized during learning; and 4) dynamic modeling has the potential to link and to unify the three views and supply a more holistic picture of human motor control. Based on these results, a learning model was constructed in the second part of the project. The essence of the model is to supply learners with the control signal (muscle moments) obtained from individual anthropometrical data and should-be-learned kinematics. Such an individualized learning process consists of: 1) obtaining kinematic characteristics of a should-be-learned skill using motion capture, 2) substituting the model’s anthropometrical data with a learner’s data, and applying inverse dynamic analysis to the model for obtaining muscle moments – the individualized control signal, and 3) applying the control information in the skill learning. The model was validated in a motor learning study. The study unveiled that dynamic modeling is well suited for improving communication with athletes and coaches as well as for improving efficiency of learning.Uvod Svrha ovog istraživačkog projekta bila je premostiti jaz između znanstvenika koji se bave istraživanjima pokreta te sportaša i trenera uspostavljanjem platforme za komunikaciju između triju skupina. U prvom dijelu projekta (Shan i sur., 2004) utvrđeno je da: 1) su razlike između vanjske perspektive (analitičari pokreta), unutarnjeg pogleda (dojam sportaša) i unutarnjeg gledišta iz vanjske perspektive (treneri) uzrokovane inercijalnim (nepomičan u odnosu na okolini) i neinercijalnim (nepomičan u odnosu na sportaševo tijelo) sustavom, kao i uparivanjem segmenata tijela; 2) rotacije zglobova nisu jednake mišićnim momentima, stoga se mogu pojaviti pasivne rotacije; 3) kritične faze u kontroli vještine, koje se mogu otkriti korištenjem simulacije modela, iznimno su važne za učenje i da ih se treba u tom procesu naglašavati i 4) dinamičko modeliranje može poslužiti kao platforma za povezivanje i ujednačivanje tri različita pogleda te pridonijeti stvaranju cjelovitije slike o ljudskoj motoričkoj kontroli. Stoga, radi uspostavljanja što bolje komunikacije sa sportašima i trenerima, analitičari pokreta ne bi trebali stati na deskriptivnoj razini, koja nudi jedino kinematičke parametre vještine. Takva deskripcija dokazano odstupa od sportaševa osjećaja kontrole ili trenerova iskustva. Iskusni su treneri svjesni da je za pojednostavljivanje motoričkog učenja ključno učeniku / sportašu prenijeti znanje o tome koji su specifični mišići uključeni u pokret, kolika je sila potrebna te kakvo je stvarno vremensko-prostorno usklađivanje (timing) nužno za motoričku kontrolu. Ti aspekti pokreta pripadaju kontrolnim parametrima i mogu se izvesti iz dinamičkog i inverznog dinamičkog modeliranja. Takav scenarij sugerira da se dinamičko modeliranje može koristiti kao platforma za unapređenje komunikacije između analitičara pokreta i onih koji to realiziraju u praksi. U drugom di-jelu projekta (predstavljenom u ovom broju) konstruiran je model za učenje koji je utemeljen na razmatranjima iz prvog rada. Bit je modela opskrbiti onoga koji uči upravljačkim informacijama - mišićnim momentima. Takve se informacije mogu pojedinačno priskrbiti primjenom inverzne dinamičke analize na konstruiranom modelu tako da individualne antropometrijske karakteristike i kinematički parametri koje treba naučiti budu ulaz za modelnu analizu. Na taj se način dizajnira individualiziran program učenja koji sadrži: 1) dobivanje kinematičkih karakteristika vještine koju treba naučiti korištenjem zahvaćanja pokreta (motion capture) i analize, 2) zamjenjivanje modelnih antropometrijskih podataka podacima osobe koja uči i primjenu inverzne dinamičke analize na model kako bi se utvrdili zglobno-mišićni momenti, što onome koji uči daje individualizirane važne kontrolne informacije i 3) primjenu kontrolne informacije u procesu učenja vještine. Rezultati i rasprava Model je procijenjen u istraživanju iz područja motoričkog učenja. Uzorak ispitanika činilo je 20 studenata sporta, podijeljenih u dvije grupe. U okviru eksperimenta istraživala su se dva aspekta učenja – znanje o pokretu i izvedba pokreta. Prva je grupa učila vještinu na konvencionalan način, koristeći se samo vizualnim informacijama. Druga je grupa uz vizualne informacije dobila i dodatne informacije o kontroli mišića. Istraživanje je evaluirano fenomenološki (pomoću upitnika) i objektivno (ekspertnom analizom video zapisa). Rezultati su pokazali da je prema, mišljenju ispitanika, metoda koja je uz vizualne nudila i kinematičke informacije kao i informacije o kontroli mišića bolja i da omogućuje bolje razumijevanje vještine. U okviru objektivne analize eksperti su procijenili da je izvedba grupe koja je imala dodatne informacije bolja od izvedbe ispitanika koji su učili na uobičajen način. Zaključak S obzirom na usporedbu subjektivne i objektivne procjene, može se zaključiti da se informacije o mišićnim momentima, dobivene na osnovi inverznog dinamičkog modeliranja, mogu koristiti kao kontrolni obrazac te da olakšavaju komunikaciju između tri skupine sudionika motoričkog učenja i da proces učenja pojednostavljuju.Die Absicht dieses Projekts war, die Kluft zwischen den Bewegungsanalysten, den Sportlern und Trainern zu überbrücken, um eine Platform für die Kommunikation zwischen den drei Parteien herzustellen. Im ersten Teil des Projekts wurde klar, dass 1) die Unterschiede zwischen der äußeren Sicht (den Bewegungsanalysten), der inneren Sicht (den Sportlern) und der inneren Sicht aus äußerem Betrachtungspunkt (den Trainern) von (umweltgebundenen) Inertialsystemen und (körpergebundenen) Nicht-Intertialsystemen verursacht sind; 2) dass die Gelenkrotationen mit den Muskelmomenten nicht identisch sind, weshalb passive Rotationen aufkommen können; 3) dass man Nachdruck auf kritische Phasen der Fertigkeitskontrolle während des Erwerbs setzen sollte, was man mit Hilfe der Modellierungssimulation erzielen kann; 4) dass die dynamische Modellierung imstande ist, die drei Sichten zu verbinden und zu vereinigen, um dadurch das holistische Bild von der menschlichen motorischen Kontrolle zu gewinnen. Aufgrund dieser Ergebnisse, wurde im zweiten Teil des Projekts ein Lernmodell entworfen. Der Kern des Modells ist, den Lernenden ein Kontrollsignal (Muskelmomente) zur Verfügung zu stellen, das sich aus individuellen anthropometrischen Angaben und einer noch-zu-erwerbenden Kinematik ergibt. Ein solcherarts individualisierter Erwerbsprozess setzt voraus, dass 1) man die kinematischen Eigenschaften einer zu erwerbenden Fertigkeit mit Hilfe der Bewegungserfassung bestimmt, 2) dass man die anthropometischen Angaben des Modells mit denen des Lernenden ersetzt, und die inverse dynamische Analyse auf das Modell anwendet, um Muskelmomente, bzw. ein individualisiertes Kontrollsignal zu bekommen, und 3) das man die Kontrollinformation beim Fertigkeitserwerb anwendet. Das Modell wurde in der motorischen Lernstudie gültig gemacht. Die Studie zeigte, dass sich die dynamische Modellierung sehr gut eignet, um die Kommunikation zwischen den Sportlern und Trainern zu verbessern, sowie den Lernprozess zu fördern

Biomechanical modeling as a practical tool for predicting injury risk related to repetitive muscle lenthening during learning and training of human complex motor skills

Open access article. Creative Commons 4.0 International License (CC BY 4.0) appliesPrevious studies have shown that muscle repetitive stress injuries (RSIs) are often related to sport trainings among young participants. As such, understanding the mechanism of RSIs is essential for injury prevention. One potential means would be to identify muscles in risk by applying biomechanical modeling. By capturing 3D movements of four typical youth sports and building the biomechanical models, the current study has identified several risk factors related to the development of RSIs. The causal factors for RSIs are the muscle over-lengthening, the impactlike (speedy increase) eccentric tension in muscles, imbalance between agonists and antagonists, muscle loading frequency and muscle strength. In general, a large range of motion of joints would lead to over-lengthening of certain small muscles; Limb’s acceleration during power generation could cause imbalance between agonists and antagonists; a quick deceleration of limbs during follow-throughs would induce an impact-like eccentric tension to muscles; and even at low speed, frequent muscle over-lengthening would cause a micro-trauma accumulation which could result in RSIs in long term. Based on the results, the following measures can be applied to reduce the risk of RSIs during learning/training in youth participants: (1) stretching training of muscles at risk in order to increase lengthening ability; (2) dynamic warming-up for minimizing possible imbalance between agonists and antagonists; (3) limiting practice times of the frequency and duration of movements requiring strength and/or large range of motion to reducing micro-trauma accumulation; and (4) allowing enough repair time for recovery from micro-traumas induced by training (individual training time). Collectively, the results show that biomechanical modeling is a practical tool for predicting injury risk and provides an effective way to establish an optimization strategy to counteract the factors leading to muscle repetitive stress injuries during motor skill learning and training.Ye

Kinematics of the turning kick: measurements obtained in testing well-trained taekwon-do athletes

Sherpa Romeo blue journal. Open access article. Creative Commons Attribution Non-commercial 4.0 License (CC BY-NC 4.0) applies.Background & Study Aim: The aim of the paper is the influence of selected kinematic factors on the turning kick technique. This issue is practically relevant in the traditional version of taekwon-do, where an effectively performed strike may divulge the winner. Material & Method: Using 3D motion capture technology, six International Taekwon-do Federation athletes were tested. Biomechanical parameters related to range of motion, kick power and kick time were applied in the analyses. The athletes executed the turning kick three times in a way typically applied in a board breaking kick. The quantification focused on the speed changes related to kicking leg extension, the maximum knee and foot velocities in the Cartesian coordinate system and the total time of kick execution. The descriptive statistics (i.e. average values and the standard deviations) and correlation analysis were applied in data analysis. Results: The results have shown that the effect of the kick is mainly represented by component of kick foot velocity in frontal – and lateral-directions. The correlation analyses unveil that the maximal knee speeds reached in frontal – and lateral-directions as well as foot take-off velocity in frontal – and vertical-directions are highly correlated to kick foot effectiveness (r = 0.60 to 0.87). The analysis of velocity development in relation to kick leg extension divulges that the maximal velocity occurs around 80% of a full leg extension. Conclusion: For increasing kick effectiveness, athletes should work on the foot take-off velocity, the dynamics of the knee motion and consider the optimum kick length for kicking power maximization.Ye