Spor Biyomekaniğinde Performans Analizi için Hareket Yakalama Teknolojisi Uygulamaları

Yıl 2022, Cilt: 34 Sayı: 2, 95 - 111, 30.09.2022

Kübra Elif Tozkoparan Özgür Karaduman

Öz

Bu çalışmada, spor performanslarında hareket yakalama teknolojisi kullanılarak sporcuların hareketlerini gerçek zamanlı olarak izleme ve kaydetme yoluyla fiziksel durumu tespit etme, sportif performanslarını belirleme ve yaralanmaları önleme mekanizmaları geliştirme amaçlanmaktadır. Burada, performansın fiziksel yönlerine bakılarak kinetik ve fiziksel performans arasındaki ilişkiyi anlamaya çalışmak için spor biyomekaniği analizi kullanılmaktadır. Biyomekanik analiz, en uygun hareket ve yük analizi için modeller oluşturarak performans üzerinde büyük bir etkiye sahip olma imkânı vermektedir. Dolayısıyla bu analiz, bir beceriyi gerçekleştirmenin en güvenli ve etkili yolunu belirlemek, farklı bir çevreye göre vücudun nasıl hareket ettiği veya nasıl tepki verdiğinin araştırılması için kullanılabilir. Bu çalışmada, spor biyomekaniğinde kullanılan hareket yakalama teknolojilerinin donanım ve yazılım bakımından sınıflandırılması yapılmış; bireysel ve takım sporlarında kullanılan hareket yakalama sistemleri ile ilgili çalışmaların algılayıcılara, denek sayısına, spor türüne göre avantaj ve dezavantajları ortaya koyulmuştur. Ayrıca, spor biyomekaniğinde kullanılan görüntü işleme uygulamaları, optik olan ve optik olmayan sistemler, marker kullanılarak ve marker kullanılmadan yapılan veri toplama işlemleri gibi hususlar ele alınmıştır. Spor biyomekaniğinin etkili ve doğru bir şekilde kullanımının sporcu performansı ve sporcu sağlığı için önemli bir rol oynadığı ve sporcuya özel sistemlerin geliştirilmesinde önemli katkılar sağladığı göze çarpmaktadır. Bu çalışmanın biyomekanik alanındaki çalışmalara, özellikle spor biyomekaniği araştırmalarına önemli ölçüde yol gösterici olacağını düşünmekteyiz.

Anahtar Kelimeler

Hareket Yakalama, Biyomekanik, Spor Biyomekaniği, Optik sistem, İşaretli/İşaretsiz Sistem

Kaynakça

• [1] Thomas J, Hall J.B, Bliss R. Guess TM. Comparison of Azure Kinect and optical retroreflective motion capture for kinematic and spatiotemporal evaluation of the sit-to-stand test. Gait & Posture 2022; 94: 153-159.
• [2] García-López J, Díez-Leal S, Ogueta-Alday A, Larrazabal J, and Rodríguez-Marroyo JA. Differences in pedalling technique between road cyclists of different competitive levels. Journal of Sports Sciences 2016: 34(17), 1619-1626.
• [3] Southgate DFL, Prinold JAI, and Weinert-Aplin RA. In sports innovation, technology and research motion analysis in sport 2016; 3–30.
• [4] Pueo B. High speed cameras for motion analysis in sports science. Journal of Human Sport and Exercise 2016; 11(1): 53–73.
• [5] Lopez Elvira JL, Lopez Plaza D, Lopez Valenciano A, and Alonso Montero C. Influence of footwear on foot movement during walking and running in boys and girls aged 6-7. Retos-Nuevas Tendencias En Educacion Fisica Deporte Y Recreacion 2017; 31: 128-132.
• [6] Kotsifaki A, Rossom SV, Whiteley R, Korakakis V, Bahr R, Sideris V, and Jonkers I. Single leg vertical jump performance identifies knee function deficits at return to sport after ACL reconstruction in male athletes. British Journal of Sports Medicine 2022; 20: 755–769.
• [7] Marqués L, Cela J, and Gisbert M. Pre-service physical education teachers’ self-management ability: a training experience in 3D simulation environments. Retos. Nuevas Tendencias En Educación Física, Deporte Y Recreación 2017; 32: 30–34.
• [8] Kurban T, Beşdok E. İnersiyal algılayıcı tabanlı hareket yakalama. In: Elektrik - Elektronik ve Bilgisayar Mühendisligi Sempozyumu ELECO; 26 - 30 Kasım 2008; Turkey.
• [9] Zhuang Y, Pan Y, Xiao J. A modern approach to intelligent animation 2008; 77-106.
• [10] Motion Capture. https://en.wikipedia.org/wiki/Motion_capture (Son Erişim: 23-05-2022).
• [11] Human Motion Analysis. https://www.xsens.com/a-history-of-motion-capture (Son Erişim: 23-05-2022).
• [12] Bisesti BA, Lawrence MA, Koch AJ, and Carlson LA. Comparison of knee moments and landing patterns during a lateral cutting maneuver: shod vs. barefoot. journal of strength and conditioning research 2015; 29(11): 3075–3078.
• [13] Greenhalgh A, Sinclair J. Comparison of achilles tendon loading between male and female recreational runners. Journal of Human Kinetics 2014; 44(44): 155–159.
• [14] Mehdizadeh S, Arshi AR, and Davids K. Effect of speed on local dynamic stability of locomotion under different task constraints in running. European Journal of Sport Science 2014; 14(8): 791-798.
• [15] Otsuk M, Ito T, Honjo T, and Isaka T. Scapula behavior associates with fast sprinting in first accelerated running. SpringerPlus 2016; 5(1): 682.
• [16] Maurer C, Stief F, Jonas A, Kovac A, Groneberg DA, Meurer A, and Ohlendorf D. Influence of the lower jaw position on the running pattern. PLoS ONE 2015; 10(8): 1-16.
• [17] Goss DL, Lewek M, Yu B, Ware WB, Teyhen DS, and Gross MT. Lower extremity biomechanics and self-reported footstrike patterns among runners in traditional and minimalist shoes. Journal of Athletic Training 2015; 50(6): 603–611.
• [18] Cockcroft J, Van Den Heever D. A descriptive study of step alignment and foot positioning relative to the tee by Professional rugby union goal-kickers. Journal of Sports Sciences 2016; 34(4): 321–9.
• [19] Crotin RL, Ramsey DK. Stride Length: A reactive response to prolonged exertion potentially effecting ball velocity among baseball pitchers. International Journal of Performance Analysis in Sport 2015; 15(1): 254–267.
• [20] Crotin RL, Kozlowski K, Horvath P, and Ramsey DK. Altered stride length in response to increasing exertion among baseball pitchers. Medicine and Science in Sports and Exercise 2014; 46(3): 565– 571.
• [21] Hansen C, Rezzoug N, Gorce P, Venture, G, and Isableu B. Sequence-dependent rotation axis changes and interaction torque use in overarm throwing. Journal of Sports Sciences 2015; 34(9): 878-885.
• [22] Laughlin WA, Fleisig GS, Aune KT, and Diffendaffer AZ. The effects of baseball bat mass properties on swing mechanics, ground reaction forces, and swing timing. Sports Biomechanics 2016; 15(1): 36–47.
• [23] Danielsen J, Sandbakk O, Holmberg HC, and Ettema G. Mechanical energy and propulsion in ergometer double poling by cross-country skiers. Medicine and Science in Sports and Exercise 2015; 47(12): 2586–2594.
• [24] Hejrati B, Chesebrough S, Bo FK, Abbott JJ, and Merryweather AS. Comprehensive quantitative investigation of arm swing during walking at various speed and surface slope conditions. Human Movement Science 2016; 49: 104–115.
• [25] Carse B, Meadows B, Bowers R, and Rowe P. Affordable clinical gait analysis: An assessment of the marker tracking accuracy of a new low-cost optical 3D motion analysis system. Physiotherapy 2013; 99(4): 347–351.
• [26] Iino Y, Kojima T. Mechanical energy generation and transfer in the racket arm during table tennis topspin backhands. Sports Biomechanics 2016; 15(2): 180–197.
• [27] Sinclair J, Bottoms L. Gender differences in the kinetics and lower extremity kinematics of the fencing lunge. International Journal of Performance Analysis in Sport 2013; 13(2): 440–451.
• [28] Joyce C, Burnett A, Cochrane J, and Ball K. Three-dimensional trunk kinematics in golf: between-club differences and relationships to clubhead speed. Sports Biomechanics 2013, 12(2): 108–120.
• [29] Sommer M, Häger C, and Rönnqvist L. Synchronized metronome training induces changes in the kinematic properties of the golf swing. Sports Biomechanics 2014; 13(1): 1–16.
• [30] Milanese C, Corte S, Salvetti L, Cavedon V, and Agostini, T. Correction of a Technical Error in the Golf Swing: Error Amplification Versus Direct Instruction. Journal of Motor Behavior 2016; 48(4): 365–376.
• [31] Sinclair J, Currigan G, Fewtrell D, and Taylor PJ. Biomechanical correlates of club head velocity during the golf swing. International Journal of Performance Analysis in Sport 2014; 14(1): 54–63.
• [32] Betzler NF, Monk SA, Wallace ES, and Otto SR. The relationships between driver clubhead presentation characteristics, ball launch conditions and golf shot outcomes. Journal of Sports Engineering and Technology 2014; 228(4): 242–249.
• [33] Lädermann A, Chagué S, Kolo FC, and Charbonnier C. Kinematics of the shoulder joint in tennis players. Journal of Science and Medicine in Sport 2016; 19(1): 56–63.
• [34] Martin C, Bideau B, Bideau N, Guillaume N, Delamarche P, and Kulpa R. Energy Flow Analysis During the Tennis Serve Comparison Between Injured and Noninsured Tennis Players. The American Journal of Sports Medicine 2014; 42(22): 2751–2760.
• [35] Martin C, Kulpa R, Delamarche P, and Bideau B. Professional tennis players’ serve: correlation between segmental angular momentums and ball velocity. Sports Biomechanics 2013; 12(1): 2-14.
• [36] Martin C, Kulpa R, Ropars M, Delamarche P, and Bideau B. Identification of temporal pathomechanical factors during the tennis serve. Medicine and Science in Sports and Exercise 2013; 45(11): 2113-2119.
• [37] Martin C, Bideau B, Delamarche P, and Kulpa R. Influence of a prolonged tennis match play on serve biomechanics. PLoS ONE 2015; 11(8): 1-14.
• [38] Reid M, Giblin G, and Whiteside D. A Kinematic comparison of the overhand throw and tennis serve in tennis players: How similar are they really? Journal of Sports Sciences 2015; 33(7): 713-723.
• [39] Judson LJ, Churchill SM, Barnes A, Stone JA, Brookes IGA, Wheat J. Measurement of bend sprinting kinematics with three-dimensional motion capture: a test–retest reliability study, Journal of Biomechanics 2020; 19(6): 761-777.
• [40] Elgammal A, Lee CS. Tracking people on a torus. IEEE Transactions on Pattern Analysis and Machine Intelligence 2009; 31(3): 520-38
• [41] Inamura T, Toshima I, Tanie H, and Nakamura Y. Embodied symbol emergence based on mimesis theory. International Journal of Robotics Research 2004, 23(4-5): 363-377.
• [42] Kulic D, Takano JW and Nakamura Y. Incremental learning, clustering and hierarchy formation of whole body motion patterns using adaptive hidden Markov chains. International Journal of Robotics Research 2008; 27(7): 761-784.
• [43] Shon AP, Grochow K, and Rao RPN. Robotic imitation for human motion capture using Gaussian processes. In: 5th IEEE-RAS International Conference on Humanoid Robots; December 2005; Tsukuba: IEEE. pp. 129-134.
• [44] Shon AP, Grochow K, Hertzmann A, and Rao RPN. Learning shared latent structure for image synthesis and robotic imitation. In Weiss Y, Schlkopf B, and Platt JC (Eds), Advances in Neural Information Processing Systems, MIT Press, Cambridge, MA, 2005.
• [45] Butt A, Rovini E, Dolciotti C, Bongioanni P, De Petris G and Cavallo F. Leap Motion Evaluation for Assessment of Upper Limb Motor Skills in Parkinson’s Disease. In: International Conference on Rehabilitation Robotics (ICORR), July 2017; IEEE. pp. 116-121.
• [46] Gieser SN, Boisselle A, and Makedon F. Realtime static gesture recognition for upper extremity rehabilitation using the leap motion. In: International Conference on Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management, August 2015; Springer. pp. 144-154.
• [47] Yahya M, Shah JA, Warsi A, Kadir K, Khan S, and Izani M. Real time elbow angle estimation using single RGB camera. arXiv preprint arXiv 2018; 1808.07017.
• [48] Manghisi VM, Uva AE, Fiorentino M, Bevilacqua V, Trotta GF, and Monno G. Real time RULA assessment using Kinect v2 sensor. Applied Ergonomics 2017; 65: 481-491.
• [49] Skublewska-Paszkowska, M, Montusiewicz J, Łukasik E, Pszczoła-Pasierbiewicz I, Baran KR, Smołka J, and Pueo, B. Motion capture as a modern technology for analysing ergometer rowing. Advances in Science and Technology Research Journal 2016; 10(29): 132–140.
• [50] Naksuk N, Lee G, and Rietdyk S. Whole-body human-to-humanoid motion transfer, In: Proceedings of 2005 5th IEEE-RAS International Conference on Humanoid Robotics, 2005; Tsukuba, pp. 104-109.
• [51] Sigal L, Balan A, and Black M. HumanEva: synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion. International Journal of Computer Vision 2009; 87(1-2): 4-27.
• [52] Rawal A, Chehata A, Horberry T, Shumack M, Chen C, and Bonato L. Defining the upper extremity range of motion for safe automobile driving. Clinical Biomechanics 2008; 54: 78-85.
• [53] Figueiredo PRP, Silva PL, Avelar BS, da Fonseca ST, Bootsma RJ, and Mancini MC. Upper limb performance and the structuring of joint movement in teenagers with cerebral palsy: the reciprocal role of task demands and action capabilities. Experimental Brain Research 2015; 233(4): 1155-1164.
• [54] Yang C, Kerr A, Stankovic V, Stankovic L, Rome P, and Cheng S. Human upper limb motion analysis for post-stroke impairment assessment using video analytics. IEEE Access 2016, 4: 650-659.
• [55] Zhang Y, Ma Y, and Liu G. Lumbar spinal loading during bowling in cricket: a kinetic analysis using a musculoskeletal modelling approach. Journal of Sports Sciences 2016; 34(11): 1030–1035.
• [56] Frayne RJ, Dean, RB, and Jenkyn TR. Improving ice hockey slap shot analysis using three-dimensional optical motion capture: A pilot study determining the effects of a novel grip tape on slap shot performance. Proceedings of the Institution of Mechanical Engineers. Part P: Journal of Sports Engineering and Technology 2015; 229(2): 136–144.
• [57] Bernardina GRD, Cerveri P, Barros RML, Marins JCB, and Silvatti AP. Action Sport Cameras as an Instrument to Perform a 3D Underwater Motion Analysis. Plos One 2016; 11(8).
• [58] Hansen C, Gibas D, Honeine JL, Rezzoug N, Gorce P, and Isableu B. An inexpensive solution for motion analysis. Proceedings of the Institution of Mechanical Engineers. Part P: Journal of Sports Engineering and Technology 2014; 228(3): 165–170.
• [59] Thewlis D, Bishop C, Daniell N, and Paul G. Next-generation low-cost motion capture systems can provide comparable spatial accuracy to high-end systems 2013; 29(1): 112–117.
• [60] Mundy PD, Lake JP, Carden PJC, Smith NA, and Lauder MA. Agreement between the force platform method and the combined method measurements of power output during the loaded countermovement jump. Sports Biomechanics 2016; 15(1): 23–35.
• [61] Chiu LZF, Bryanton MA, and Moolyk AM. Proximal-todistal sequencing in vertical jumping with and without arm swing. Journal of Strength and Conditioning Research 2014; 28(5): 1195–1202.
• [62] Pueo, B. High speed cameras for motion analysis in sports science. Journal of Human Sport and Exercise 2016; 11(1): 53–73.
• [63] Estevan I, Falco C, Silvernail JF, and Jandacka D. Comparison of lower limb segments kinematics in a taekwondo kick. an approach to the proximal to distal motion. Journal of Human Kinetics 2015; 47(1): 41–49.
• [64] Estevan I, Freedman Silvernail J, Jandacka D, and Falco C. Segment coupling and coordination variability analyses of the roundhouse kick in taekwondo relative to the 68 initial stance position. Journal of Sports Sciences 2016; 34(18): 1766–1773.
• [65] Estevan I, Jandacka D, and Falco C. Effect of stance position on kick performance in taekwondo. Journal of Sports Sciences 2013; 31(16): 1815–1822.
• [66] Gomo O, van den Tillaar R. The effects of grip width on sticking region in bench press. Journal of Sports Sciences 2015; 1– 7.
• [67] Hart NH, Cochrane JL, Spiteri T, Nimphius S, and Newton RU. Relationship between leg mass, leg composition and foot velocity on kicking accuracy in Australian football. Journal of Sports Science and Medicine 2016; 15(2): 344–351.
• [68] Huchez A, Haering D, and Holvoët P. Local versus global optimal sports techniques in a group of athletes. Computer Methods in Biomechanics and Biomedical Engineering 2013; 18: 37–41.
• [69] Lazzeri M, Kayser B, and Armand S. Kinematic predictors of wrist shot success in floorball/unihockey from two different feet positions. Journal of Sports Sciences 2016; 1–8.
• [70] Lockie RG, Callaghan SJ, and Jeffriess MD. Acceleration kinematics in cricketers: Implications for performance in the field. Journal of Sports Science and Medicine 2014; 13(1): 128–136.
• [71] López, JL, López D, López A, and Alonso C. Influence of footwear on foot movement during walking and running in boys and girls aged 6-7. Retos. Nuevas Tendencias En Educación Física, Deporte Y Recreación 2017; 31: 128–132.
• [72] Zago M, Piovan AG, Annoni I, Ciprandi D, Iaia FM, and Sforza C. Dribbling determinants in sub-elite youth soccer players. Journal of Sports Sciences 2015; 414: 1–9.
• [73] Sinclair J, Fewtrell D, Taylor PJ, Bottoms L, Atkins S, and Hobbs SJ. Three dimensional kinematic correlates of ball velocity during maximal instep soccer kicking in males. European Journal of Sport Science 2014; 14(8): 799–805.
• [74] Sinclair J, Fewtrell D, Taylor PJ, Atkins S, Bottoms L, and Hobbs SJ. Three dimensional kinematic differences between the preferred and non-preferred limbs during maximal instep soccer kicking. Journal of Sports Sciences 2014; 32(20): 1914–1923.
• [75] Inoue K, Nunome H, Sterzing T, Shinkai H, and Ikegami Y. Dynamics of the support leg in soccer instep kicking. Journal of Sports Sciences 2014; 32(11): 1023–1032.
• [76] Arshi AR, Nabavi H, Mehdizadeh S, and Davids K. An alternative approach to describing agility in sports through establishment of a relationship between velocity and radius of curvature. Journal of Sports Sciences 2014; 33(13): 1349–1355.
• [77] Nedergaard NJ, Heinen F, Sloth S, Holmberg HC, and Kersting UG. Biomechanics of the ski cross start indoors on a customised training ramp and outdoors on snow. Sports Biomechanics 2015; 14(3): 273–286.
• [78] Zhang Z, Li S, Wan B, Visentin P, Jiang Q, Dyck M, Shan, G. The Influence of X-Factor (Trunk Rotation) and Experience on the Quality of the Badminton Forehand Smash. Journal of Human Kinetics 2016; 53(1): 9–22.
• [79] Kasmer ME, Ketchum NC, and Liu XC. The effect of shoe type on gait in forefoot strike runners during a 50-km run. Journal of Sport and Health Science 2014; 3(2), 122– 130.
• [80] Gageler WH, Thiel D, Neville J, James DA. Feasibility of using virtual and body worn inertial sensors to detect whole-body decelerations during stopping. Procedia Engineering 2013; 60(0): 28–33.
• [81] Hollander K, Hoenig T, Edouuard P. Biomechanics of running. In: IEEE International Workshop on The Running Athlete, April 2022; IEEE. pp. 3-11.
• [82] Losciale JM, Ithurburn MP, Paterno MV, and Schmitt LC, Passing return-to-sport criteria and landing biomechanics in young athletes following anterior cruciate ligament reconstruction. In: Proceedings of the IEEE International Conference on Journal of Orthopaedic Research, 2022; 40(1), pp. 208-218.
• [83] Hindle BR, Keogh JWL, Lorimer AV. Inertial-based human motion capture: a technical summary of current processing methodologies for spatiotemporal and kinematic measures. Applied Bionics and Biomechanics 2021.
• [84] Ruiz-del-Solar J, Palma-Amestoy R, Marchant R, Parra-Tsunekawa I, and Zegers P. Learning to fall: designing low damage fall sequences for humanoid soccer robots, robotics and autonomous systems. Humanoid Soccer Robots 2009; 57(8): 796-807.
• [85] Pastor I, Hayes HA, and Bamberg SJ. A feasibility study of an upper limb rehabilitation system using kinect an computer games. In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 2012; IEEE. pp. 1286-1289.
• [86] Taborri J, Keogh J, Kos A, Santuz A, Umek A, Urbanczyk C, Kruk E, Rossi S. Sport biomechanics applications using inertial, force, and emg sensors: a literature overview. Journal of Applied Bionics and Biomechanics 2020.
• [87] McGinnis RS, Cain SM, Davidson SP, Vitali RV, Perkins NC, and McLean SG. Quantifying the effects of load carriage and fatigue under load on sacral kinematics during countermovement vertical jump with IMU-based method. Sports Engineering 2016; 19(1): 21–34.
• [88] Bötzel K, Marti FM, Rodríguez MÁC, Plate A, and Vicente AO. Gait recording with inertial sensors - How to determine initial and terminal contact. Journal of Biomechanics 2016; 49(3): 332–337.
• [89] Rantalainen T, Hart NH, Nimphius S, and Wundersitz DW. Associations Between Step Duration Variability and Inertial Measurement Unit Derived Gait 70 Characteristics. Journal of Applied Biomechanics 2016; 32(4): 401–406.
• [90] Telfer S, Woodburn J, and Turner DE. An ultrasound based non-invasive method for the measurement of intrinsic foot kinematics during gait. Journal of Biomechanics 2014; 47(5): 1225-1228.
• [91] Wang F, Skubic M, Rantz M, and Cuddihy PE. Quantitative gait measurement with pulse-doppler radar for passive in-home gait assessment. IEEE Transactions on Biomedical Engineering 2014; 61(9): 2434-2443.
• [92] Papi E, Osei-Kuffour D, Chen YMA, and McGregor, AH. Use of wearable technology for performance assessment: a validation study. Medical Engineering & Physics 2015; 37(7): 698–704.
• [93] Fasel B, Favre J, Chardonnens J, Gremion G, and Aminian K. An inertial sensor based system for spatio-temporal analysis in classic cross-country skiing diagonal technique. Journal of Biomechanics 2015; 48(12): 3199–3205.
• [94] Atrsaei A, Salarieh H, and Alasty A. Human arm motion tracking by orientation-based fusion of inertial sensors and Kinect using unscented Kalman filter. Journal of Biomechanical Engineering 2016; 138(9).
• [95] Fasel B, Praz C, Kayser B, and Aminian K. Measuring spatiotemporal parameters of uphill ski-mountaineering with ski-fixed inertial sensors. Journal of Biomechanics 2016; 1-4.
• [96] Calinon S, Guenter F, and Billard A. On learning, representing and generalizing a task in a humanoid robot. IEEE Transactions on Systems, Man and Cybernetics: Part B 2007; 37(2): 286-298.
• [97] Field M, Stirling D, Naghdy F, and Pan Z. Motion segmentation for humanoid control planning. In: ARAA Australasian Conference on Robotics and Automation, 3-5 December 2008; Canberra,
• [98] Fujimori Y, Ohmura Y, Harada T, and Kuniyoshi Y. Wearable motion capture suit with full-body tactile sensors. In: IEEE International Conference on Robotics and Automation, 12-17 May 2009; Kobe. IEEE. pp. 3186-3193.
• [99] Miller N, Jenkins OC, Kallmann M, and Mataric, MJ. Motion capture from inertial sensing for untethered humanoid teleoperation. 4th IEEE/RAS International Conference on Humanoid Robots, 10-12 November 2012; Los Angeles, CA. IEEE. pp. 547-565.
• [100] Vlasic D, Adelsberger R, Vannucci G, Barnwell J, Gross M, Matusik W, and Popovic J. Practical motion capture in everyday surroundings. ACM Transactions on Graphics 2007; 26(3): 35-es.
• [101] Ward JA, Lukowicz P, Troster G, and Starner T. Activity recognition of assembly tasks using body-worn microphones and accelerometers. In: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006; 28(10), pp. 1553-1567.
• [102] Biswas D, Cranny A, Gupta N, Maharatna K, Achner J, Klemke J, Jöbges M, and Ortmann S. Recognizing upper limb movements with wrist worn inertial sensors using k-means clustering classification. Human Movement Science 2015. 40: 59-76.
• [103] El-Gohary M, McNames J. Human joint angle estimation with inertial sensors and validation with a robot arm. IEEE Transactions on Biomedical Engineering 2015; 62(7): 1759-1767.
• [104] McLeod A, Bochniewicz EM, Lum PS, Holley RJ, Emmer G, and Dromerick AW. Using wearable sensors and machine learning models to separate functional upper extremity use from walking-associated arm movements. Archives of Physical Medicine and Rehabilitation 2016; 97(2): 224-231.
• [105] Ruffaldi E, Peppoloni L, Filippeschi A. Sensor fusion for complex articulated body tracking applied in rowing. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology 2015; 229(2): 92–102.
• [106] Zorko M, Nemec B, Babiè J, Lešnik B, and Supej M. The waist width of skis influences the kinematics of the knee joint in alpine skiing. Journal of Sports Science and Medicine 2005; 14(3): 606–619.
• [107] Kim YK. The Effect of Different Warm-up Procedures on Bat Speed in Baseball. Korean Journal of Sport Biomechanics 2013; 23(2): 91–97.
• [108] Matsunaga T, Oshita M. Recognition of walking motion using support vector machine. In: Proceedings of the ISICE2007, pp. 337-342.
• [109] Moldenhauer J, Boesnach I, Beth T, Wank V, and Bos K. Analysis of human motion for humanoid robots. In: Proceedings of the International Conference on Robotics and Automation, 18-22 April 2005; Barcelona, Spain. IEEE. pp. 311-316.
• [110] Ramana PKR, Grest D, and Volker K. Human action recognition in table-top scenarios: an HMM-based analysis to optimize the performance. In: Proceedings of 12th International Conference on Computer Analysis of Images and Patterns, 2007; 27-29 August 2007; Vienna, Austria. pp. 101-108.
• [111] Yamamoto T, Fujinami T. Hierarchical organization of the coordinative structure of the skill of clay kneading. Human Movement Science 2008; 27 (5): 812- 822.
• [112] Zhao L and Badler NI. Acquiring and validating motion qualities from live limb gestures. Graphical Models 2005. 67(1): 1-16.
• [113] Bai L, Pepper MG, Yan Y, Spurgeon SK, Sakel M, and Phillips M. Quantitative assessment of upper limb motion in neurorehabilitation utilizing inertial sensors. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering 2015; 23(2), pp. 232-243.
• [114] Huang MH, Brown SH. Age differences in the control of postural stability during reaching tasks. Gait &Amp Posture 2013; 38(4), pp. 837-842.
• [115] Pang M, Guo S, Huang Q, Ishihara H, and Hirata H. Electromyography based quantitative representation method for upper-limb elbow joint angle in sagittal plane. Journal of Medical and Biological Engineering 2015; 35(2): 165-177.
• [116] Abrams GD, Harris AH, Andriacchi TP, Safran MR, and Safran M. Biomechanical analysis of three tennis serve types using a markerless system. Br J Sports Med 2014; 48: 339–342.
• [117] Nakano N, Sakura T, Ueda K, Omura L, Kimura A, Iion Y, Fukashiro S, and Yoshioka S. Evaluation of 3D Markerless Motion Capture Accuracy Using OpenPose with Multiple Video Cameras. Journal of Sports Science, Technology and Engineering 2020; 2:50.
• [118] Drazan JF, Phillips WT, Seethapathi N, Hullfish TJ, Baxter JR. Moving outside the lab: Markerless motion capture accurately quantifies sagittal plane kinematics during the vertical jump. In: IEEE International Conference on Journal of Biomechanics, 26 August 2021; 125.
• [119] Wade L, Needham L, McGuigan P, Bilzon J. Applications and limitations of current markerless motion capture methods for clinical gait biomechanics. In: IEEE Transactions on Sports Medicine and Rehabilitation, 25 February 2022.
• [120] Xu X, Robertson M, Chen KB, Lin JH, and McGorry RW. Using the Microsoft KinectTM to assess 3-D shoulder kinematics during computer use. Applied Ergonomics 2017; 65: 418-423.
• [121] Schlagenhauf F, Sreeram S, and Singhose WE. Comparison of kinect and vicon motion capture of upperbody joint angle tracking. In: 14th International Conference on Control and Automation (ICCA), 2018; IEEE.
• [122] Yang C, Kerr A, Stankovic A, Stankovic L, and Rowe P. Upper limb movement analysis via marker tracking with a single-camera system. In: International Conference on Image Processing (ICIP), 2014; IEEE.
• [123] Auvinet E, Multon F, and Meunier J. New Lower-Limb gait asymmetry indices based on a depth camera. Sensors 2015; 15(3): 4605-4623.
• [124] Pfister A, West AM, Bronner S, and Noah JA. Comparative abilities of Microsoft Kinect and Vicon 3D motion capture for gait analysis. J Med Eng Technol 2014; 38(5): 1464-522.
• [125] Sandau M, Koblauch H, Moeslund TB, Aanæs H, Alkjær T, and Simonsen EB. Markerless motion capture can provide reliable 3D gait kinematics in the sagittal and frontal plane. Medical Engineering and Physics 2014; 36(9): 1168–1175.
• [126] Clark RA, Bower KJ, Mentiplay BF, Paterson K, and Pua YH. Concurrent validity of the Microsoft Kinect for assessment of spatiotemporal gait variables. Journal of Biomechanics 2013; 46(15): 2722–2725.
• [127] Kim J, Gravunder A, and Park HS. Commercial Motion Sensor Based Low-Cost and Convenient Interactive Treadmill. Sensors 2015; 15(9): 23667–23683.
• [128] Krigslund R, Dosen S, Popovski P, Dideriksen JL, Pedersen GF, and Farina D. A novel technology for motion capture using passive UHF RFID tags. IEEE Transactions on Biomedical Engineering 2012; 60(5): 1453–1457.
• [129] Eltoukhy M, Kelly A, Kim CY, Jun HP, Campbell R, and Kuenze C. Validation of the Microsoft Kinect® camera system for measurement of lower extremity jump landing and squatting kinematics. Sports Biomechanics / International Society of Biomechanics in Sports 2016, 1–14.
• [130] O’Keefe JA, Orías AAE, Khan H, Hall DA, Berry-Kravis E, and Wimmer MA. Implementation of a markerless motion analysis method to quantify hyperkinesis in males with fragile X syndrome. Gait and Posture 2014; 39(2): 827–830.
• [131] Schmitz A, Ye M, Boggess G, Shapiro R, Yang R, and Noehren B. The measurement of in vivo joint angles during a squat using a single camera markerless motion capture system as compared to a marker based system. Gait and Posture 2015; 41(2): 694–698.
• [132] Bonnechère B, Jansen B, Salvia P, Bouzahouene H, Omelina L, Moiseev F, Van Sint Jan S. Validity and reliability of the Kinect within functional assessment activities: Comparison with standard stereophotogrammetry. Gait and Posture 2014; 39(1): 593–598.
• [133] Schmitz A, Ye M, Shapiro R, Yang R, and Noehren B. Accuracy and repeatability of joint angles measured using a single camera markerless motion capture system. Journal of Biomechanics 2014, 47(2), 587–591.
• [134] Yeung LF, Cheng KC, Fong CH, Lee WCC, and Tong KY. Evaluation of the Microsoft Kinect as a clinical assessment tool of body sway. Gait & Posture 2014; 40(4): 532 538.
• [135] Motion Capture: Magnetic Systems. Next Generation. Imagine Media October 1995; 10: 51.
• [136] Gustafson JA, Dowling B, Heidloff D, Quigley RJ, Garrigues GE. Optimizing Pitching Performance through Shoulder and Elbow Biomechanics. IEEE Transactions on Operative Techniques in Sports Medicine 2022; 150890.
• [137] Trasolini NA, Nicholson KF, Mylott J, Bullock GS, Phil D, Hulburt TC, Waterman BR. Biomechanical Analysis of the Throwing Athlete and Its Impact on Return to Sport. Arthroscopy, Sports Medicine, and Rehabilitation 2022; e83-e91.
• [138] Choo CZY, Chow JY, Komar J. Validation of the Perception Neuron system for full-body motion capture. Journal of Biomechanics 2022; 31(10): 957–961.
• [139] Diffendaffer A.Z., Bagwell M.S., Fleisig G.S. (2022). The Clinician’s Guide to Baseball Pitching Biomechanics. Journal of Biomechanics, https://doi.org/10.1177/19417381221078537
• [140] https://www.technaid.com/products/motion-capture-system-tech-mcs-hub-imu/ (Son erişim :23.05.2022)
• [141] Wade L, Needham L, McGuigan P, Bilzon J. Applications and limitations of current markerless motion capture methods for clinical gait biomechanics. PeerJ 2022; 10: e12995.
• [142] Girbés-Juan V, Schettino V, Gracia L, Solanes JE, Demiris Y, Tornero J. Combining haptics and inertial motion capture to enhance remote control of a dual-arm robot. Measurement 2022; 1-20.
• [143] Beetz M, von Hoyningen-Huene N, Kirchlechner B, Gedikli S, Siles F, Durus M, and Lames M. Aspogamo: Automated sports game analysis models. International Journal of Computer Science in Sport 2009; 8(1): 1-21.
• [144] Corazza S, Mündermann L, Gambaretto E, Ferrigno G, Andriacchi TP. Markerless motion capture through visual hull, articulated icp and subject specific model generation. International Journal of Computer Vision 2010; 87(1): 156-169.
• [145] Maletsky LP, Sun J, and Morton NA. Accuracy of an optical active-marker system to track the relative motion of rigid bodies. Journal of Biomechanics 2007; 40(3): 682-685.
• [146] Begon M, Colloud F, Fohanno V, Bahuaud P, and Monnet T. Computation of the 3D kinematics in a global frame over a 40 m- long pathway using a rolling motion analysis system. Journal of Biomechanics 2009; 42(16): 2649–2653.
• [147] Spörri J, Schiefermüller C, and Müller E. Collecting kinematic data on a Ski track with optoelectronic stereophotogrammetry: A methodological study assessing the feasibility of bringing the biomechanics lab to the field. PloS One 2016; 11(8): e0161757.
• [148] Panjkota A, Stancic I, and Supuk T. Outline of a qualitative analysis for the human motion in case of ergometer rowing. In: WSEAS International Conference. Proceedings. Mathematics and Computers in Science and Engineering; 2009.
• [149] Windolf M, Götzen N, and Morlock, M. Systematic accuracy and precision analysis of video motion capturing systemsexemplified on the vicon-460 system. Journal of Biomechanics 2008; 41(12): 2776–2780.
• [150] Van Der Kruk E, Reijne MM. Accuracy of human motion capture systems for sport applications; state-of-the-art review. European journal of sport science 2018; 18(6): 806-819