Abstract
This chapter is dedicated to the presentation of biofeedback applications in sport and rehabilitation. The review of such applications that come in large numbers and varieties is not in the scope of this book. To provide the complete information about the development, properties, functionalities, and results of biofeedback applications, we chose to present only those developed by the authors of this book. Properties and requirements of different sports and rehabilitation therapies are explained first, followed by typical applications scenarios including low dynamic activities, high dynamic activities, multiple sensors, and multiple user cases. Five examples of biofeedback applications are presented and discussed: Golf swing trainer, Smart golf club, Smart ski, water sport, and swimming rehabilitation. Each of them is thoroughly explained in terms of its objectives and functionalities, system architecture and setup, theoretical and research background, results and future development plans. All application presentations include details about the biofeedback system elements used (sensors, processing devices, actuators) and the most important and relevant results that are showing or proving its suitability, applicability, and usefulness for the intended function. Also, for each of the applications future development ideas are listed and explained. By studying this chapter, the reader should get a deeper insight of the various possibilities available for biofeedback application development and use.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdul Razak AH, Zayegh A, Begg RK, Wahab Y (2012) Foot plantar pressure measurement system: A review. Sensors 12(7):9884–9912
Adelsberger R, Aufdenblatten S, Gilgien M, Tröster G (2014) On bending characteristics of skis in use. Procedia Engineering 72:362–367
Ahmadi, A., Destelle, F., Monaghan, D., O’Connor, N. E., Richter, C., & Moran, K. (2014, November). A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors. In SENSORS, 2014 IEEE (pp. 2211–2214). IEEE
Barbosa AC, Castro FDS, Dopsaj M, Cunha SA, Júnior OA (2013) Acute responses of biomechanical parameters to different sizes of hand paddles in front-crawl stroke. J Sports Sci 31(9):1015–1023
Becker BE (2009) Aquatic therapy: scientific foundations and clinical rehabilitation applications. PM&R 1(9):859–872
Betzler NF, Monk SA, Wallace ES, Otto SR (2012) Effects of golf shaft stiffness on strain, clubhead presentation and wrist kinematics. Sports Biomech 11(2):223–238
Camomilla V, Bergamini E, Fantozzi S, Vannozzi G (2016) In-field use of wearable magneto-inertial sensors for sports performance evaluation. In: ISBS-conference proceedings archive, vol 33(1)
Chambers R, Gabbett TJ, Cole MH, Beard A (2015) The use of wearable microsensors to quantify sport-specific movements. Sports Med 45(7):1–17
Choi YC, Kim HK, Shim KB (2016) Analyzing the characteristics of golf driver shafts with using a strain gage. J Ceram Process Res 17:113–117
Chun S, Kang D, Choi HR, Park A, Lee KK, Kim J (2014) A sensor-aided self coaching model for uncocking improvement in golf swing. Multimed Tools Appl 72(1):253–279
Delgado-Gonzalo R, Lemkaddem A, Renevey P, Calvo EM, Lemay M, Cox K, Bertschi M (2016) Real-time monitoring of swimming performance. In: 2016 IEEE 38th annual international conference of the engineering in medicine and biology society (EMBC). IEEE, pp 4743–4746
Dopsaj M, Matković I, Thanopoulos V, Okičić T (2003) Reliability and validity of basic kinematics and mechanical characteristics of pulling force in swimmers measured by the method of tethered swimming with maximum intensity of 60 seconds. Facta Univ Ser: Phys Educ Sport 1(10):11–22
Doyle B (2015) Experts weigh in on head movement during the golf swing. Forever better golf. https://foreverbettergolf.com/articles/experts-weigh-in-on-head-movement-during-the-golf-swing/. Accessed 10 June 2018
Ebling MR (2016) IoT: from sports to fashion and everything in-between. IEEE Pervasive Comput 4:2–4
Falda-Buscaiot T, Hintzy F, Coulmy N (2016) Ground reaction force comparison between both feet during giant slalom turns in alpine skiing. In ISBS-conference proceedings archive, vol 33(1)
Ganzevles S, Vullings R, Beek PJ, Daanen H, Truijens M (2017) Using tri-axial accelerometry in daily elite swim training practice. Sensors 17(5):990
Gruwsved Å, Söderback I, Fernholm C (1996) Evaluation of a vocational training programme in primary health care rehabilitation: a case study. Work 7(1):47–61
Guignard B, Rouard A, Chollet D, Seifert L (2017) Behavioral dynamics in swimming: the appropriate use of inertial measurement units. Front Psychol 8:383
Guo J, Zhou X, Sun Y, Ping G, Zhao G, Li Z (2016) Smartphone-based patients’ activity recognition by using a self-learning scheme for medical monitoring. J Med Syst 40(6):140
Hsu YL, Chen YT, Chou PH, Kou YC, Chen YC, Su HY (2016) Golf swing motion detection using an inertial-sensor-based portable instrument. In 2016 IEEE international conference on consumer electronics-Taiwan (ICCE-TW). (pp 1–2)
Jakus G, Stojmenova K, Tomažič S, Sodnik J (2017) A system for efficient motor learning using multimodal augmented feedback. Multimed Tools Appl 76(20):20409–20421
Jensen U, Schmidt M, Hennig M, Dassler FA, Jaitner T, Eskofier BM (2015) An IMU-based mobile system for golf putt analysis. Sports Eng 18(2):123–133
Jiao L, Bie R, Wu H, Wei Y, Kos A, Umek A (2018) Golf swing data classification with deep convolutional neural network. IPSI BGD Trans Internet Res 14(1):29–34
Kirby R (2009) Development of a real-time performance measurement and feedback system for alpine skiers. Sports Technol 2(1–2):43–52
Kos A, Umek A (2018) Wearable sensor devices for prevention and rehabilitation in healthcare: swimming exercise with real-time therapist feedback. IEEE Internet Things J. https://doi.org/10.1109/jiot.2018.2850664
Kos A, TomaĹľiÄŤ S, Umek A (2016) Suitability of smartphone inertial sensors for real-time biofeedback applications. Sensors 16(3):301
Kos A, Milutinović V, Umek A (2018) Challenges in wireless communication for connected sensors and wearable devices used in sport biofeedback applications. Future Gener Comput Syst. https://doi.org/10.1016/j.future.2018.03.032
Kunze K, Minamizawa K, Lukosch S, Inami M, Rekimoto J (2017) Superhuman sports: Applying human augmentation to physical exercise. IEEE Pervasive Comput 16(2):14–17
Li R, Cai Z, Lee W, Lai DT (2016) A wearable biofeedback control system based body area network for freestyle swimming. In: 2016 IEEE 38th annual international conference of the engineering in medicine and biology society (EMBC). IEEE, (pp 1866–1869)
Li X, Wang C, Wang H, Guo J (2017) Real-time dynamic data analysis model based on wearable smartband. In: International conference on intelligent and interactive systems and applications. Springer, Cham, (pp 442–449)
Lightman K (2016) Silicon gets sporty. IEEE Spectr 53(3):48–53
Llosa J, Vilajosana I, Vilajosana X, Navarro N, Surinach E, Marques JM (2009) REMOTE, a wireless sensor network based system to monitor rowing performance. Sensors 9(9):7069–7082
Magalhaes FAD, Vannozzi G, Gatta G, Fantozzi S (2015) Wearable inertial sensors in swimming motion analysis: a systematic review. J Sports Sci 33(7):732–745
Mendes JJA Jr, Vieira MEM, Pires MB, Stevan SL Jr (2016) Sensor fusion and smart sensor in sports and biomedical applications. Sensors 16(10):1569
Michahelles F, Schiele B (2005) Sensing and monitoring professional skiers. IEEE Pervasive Comput 4(3):40–45
Mitsui T, Tang S, Obana S (2015 Support system for improving golf swing by using wearable sensors. In: 2015 eighth international conference on mobile computing and ubiquitous networking (ICMU). IEEE, (pp 100–101)
Mooney R, Corley G, Godfrey A, Quinlan LR, Ă“Laighin G (2015) Inertial sensor technology for elite swimming performance analysis: a systematic review. Sensors 16(1):18
Nagle EF, Sanders ME, Franklin BA (2017) Aquatic high intensity interval training for cardiometabolic health: benefits and training design. Am J Lifestyle Med 11(1):64–76
Najafi B, Lee-Eng J, Wrobel JS, Goebel R (2015) Estimation of centre of mass trajectory using wearable sensors during golf swing. J Sports Sci Med 14(2):354
Nakazato K, Scheiber P, MĂĽller E (2011) A comparison of ground reaction forces determined by portable force-plate and pressure-insole systems in alpine skiing. J Sports Sci Med 10(4):754
Nam CNK, Kang HJ, Suh YS (2014) Golf swing motion tracking using inertial sensors and a stereo camera. IEEE Trans Instrum Meas 63(4):943–952. [192]
Naruo T, Kawashima K, Kimura T, Oota Y, Kanayama T (2013) Golf swing analysis by an inertia sensor and selecting optimum golf club. In: ISBS-conference proceedings archive, vol 1(1)
Neiva HP, Marques MC, Travassos BF, Marinho DA (2017) Wearable technology and aquatic activities: a review. Motricidade 13(1):219
Nemec B, Petrič T, Babič J, Supej M (2014) Estimation of alpine skier posture using machine learning techniques. Sensors 14(10):18898–18914
Parvis M, Grassini S, Angelini E, Scattareggia P (2016) Swimming symmetry assessment via multiple inertial measurements. In: 2016 IEEE international symposium on medical measurements and applications (MeMeA). IEEE, (pp. 1–6)
Parvis M, Corbellini S, Lombardo L, Iannnucci L, Grassini S, Angelini E (2017) Inertial measurement system for swimming rehabilitation. In: 2017 IEEE international symposium on medical measurements and applications (MeMeA). IEEE, (pp. 361–366)
Prins J, Cutner D (1999) Aquatic therapy in the rehabilitation of athletic injuries. Clin Sports Med 18(2):447–461
Qualisys, Motion Capture System. http://www.qualisys.com. Accessed 27 June 2018
Sakurai Y, Fujita Z, Ishige Y (2016) Automatic identification of subtechniques in skating-style roller skiing using inertial sensors. Sensors 16(4):473
Shyr TW, Shie JW, Jiang CH, Li JJ (2014) A textile-based wearable sensing device designed for monitoring the flexion angle of elbow and knee movements. Sensors 14(3):4050–4059
Silva ASM (2014) Wearable sensors systems for human motion analysis: sports and rehabilitation. Doctoral dissertation, Universidade do Porto, Portugal
Singh R, Stringer H, Drew T, Evans C, Jones RS (2015) Swimming breaststroke after total hip replacement; are we sending the correct message. J Arthritis 4(147):2
Stamm A, James DA, Thiel DV (2013) Velocity profiling using inertial sensors for freestyle swimming. Sports Eng 16(1):1–11
Stančin S, Tomažič S (2013) Early improper motion detection in golf swings using wearable motion sensors: The first approach. Sensors 13(6):7505–7521
Sturm D, Yousaf K, Eriksson M (2010) A wireless, unobtrusive kayak sensor network enabling feedback solutions. In 2010 international conference on body sensor networks (bsn). IEEE, (pp 159–163)
Sun Y, Song H, Jara AJ, Bie R (2016) Internet of things and big data analytics for smart and connected communities. IEEE Access 4:766–773
Tessendorf B, Gravenhorst F, Arnrich B, Tröster G (2011) An imu-based sensor network to continuously monitor rowing technique on the water. In 2011 seventh international conference on intelligent sensors, sensor networks and information processing (ISSNIP). IEEE, (pp 253–258)
Ueda M, Negoro H, Kurihara Y, Watanabe K (2013) Measurement of angular motion in golf swing by a local sensor at the grip end of a golf club. IEEE Trans Human-Mach Syst 43(4):398–404
Umek, A., & Kos, A. (2018a). Smart equipment design challenges for real time feedback support in sport. Facta Universitatis, Series: Mechanical Engineering
Umek A, Kos A (2018b) Wearable sensors and smart equipment for feedback in watersports. Procedia Comput Sci 129:496–502
Umek A, Tomažič S, Kos A (2015) Wearable training system with real-time biofeedback and gesture user interface. Pers Ubiquit Comput 19(7):989–998
Umek A, Zhang Y, TomaĹľiÄŤ S, Kos A (2017) Suitability of strain gage sensors for integration into smart sport equipment: A golf club example. Sensors 17(4):916
Wang Z, Wang J, Zhao H, Yang N, Fortino G (2016) CanoeSense: monitoring canoe sprint motion using wearable sensors. In: 2016 IEEE international conference on systems, man, and cybernetics (SMC) IEEE
Wei Y, Jiao L, Wang S, Bie R, Chen Y, Liu D (2016) Sports motion recognition using MCMR features based on interclass symbolic distance. Int J Distrib Sens Netw 12(5):7483536
Woods T (2009) Maintain a quiet head http://www.golfdigest.com/golf-instruction/2009-10/tiger_woods_keep_quiet_head. Golf digest. Accessed 26 June 2018
Yilmaz I, Yanardag M, Birkan B, Bumin G (2004) Effects of swimming training on physical fitness and water orientation in autism. Pediatr Int 46(5):624–626
Yu G, Jang YJ, Kim J, Kim JH, Kim HY, Kim K, Panday SB (2016) Potential of IMU sensors in performance analysis of professional alpine skiers. Sensors 16(4):463
Zhang Z, Zhang Y, Kos A, Umek A (2017) A sensor-based golfer-swing signature recognition method using linear support vector machine. Elektrotehniski Vestnik 84(5):247–252
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kos, A., Umek, A. (2018). Applications. In: Biomechanical Biofeedback Systems and Applications. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-319-91349-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-91349-0_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91348-3
Online ISBN: 978-3-319-91349-0
eBook Packages: Computer ScienceComputer Science (R0)