Skip to main content

Applications

  • Chapter
  • First Online:
Biomechanical Biofeedback Systems and Applications

Part of the book series: Human–Computer Interaction Series ((HCIS))

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 99.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abdul Razak AH, Zayegh A, Begg RK, Wahab Y (2012) Foot plantar pressure measurement system: A review. Sensors 12(7):9884–9912

    Article  Google Scholar 

  • Adelsberger R, Aufdenblatten S, Gilgien M, Tröster G (2014) On bending characteristics of skis in use. Procedia Engineering 72:362–367

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Barbosa AC, Castro FDS, Dopsaj M, Cunha SA, JĂşnior OA (2013) Acute responses of biomechanical parameters to different sizes of hand paddles in front-crawl stroke. J Sports Sci 31(9):1015–1023

    Article  Google Scholar 

  • Becker BE (2009) Aquatic therapy: scientific foundations and clinical rehabilitation applications. PM&R 1(9):859–872

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Dopsaj M, Matković I, Thanopoulos V, OkiÄŤić 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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)

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Gruwsved Ă…, Söderback I, Fernholm C (1996) Evaluation of a vocational training programme in primary health care rehabilitation: a case study. Work 7(1):47–61

    Article  Google Scholar 

  • Guignard B, Rouard A, Chollet D, Seifert L (2017) Behavioral dynamics in swimming: the appropriate use of inertial measurement units. Front Psychol 8:383

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • Jakus G, Stojmenova K, TomaĹľiÄŤ S, Sodnik J (2017) A system for efficient motor learning using multimodal augmented feedback. Multimed Tools Appl 76(20):20409–20421

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • Kirby R (2009) Development of a real-time performance measurement and feedback system for alpine skiers. Sports Technol 2(1–2):43–52

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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)

    Google Scholar 

  • Lightman K (2016) Silicon gets sporty. IEEE Spectr 53(3):48–53

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Michahelles F, Schiele B (2005) Sensing and monitoring professional skiers. IEEE Pervasive Comput 4(3):40–45

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Google Scholar 

  • 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]

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • Neiva HP, Marques MC, Travassos BF, Marinho DA (2017) Wearable technology and aquatic activities: a review. Motricidade 13(1):219

    Google Scholar 

  • Nemec B, PetriÄŤ T, BabiÄŤ J, Supej M (2014) Estimation of alpine skier posture using machine learning techniques. Sensors 14(10):18898–18914

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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)

    Google Scholar 

  • Prins J, Cutner D (1999) Aquatic therapy in the rehabilitation of athletic injuries. Clin Sports Med 18(2):447–461

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Silva ASM (2014) Wearable sensors systems for human motion analysis: sports and rehabilitation. Doctoral dissertation, Universidade do Porto, Portugal

    Google Scholar 

  • 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

    Google Scholar 

  • Stamm A, James DA, Thiel DV (2013) Velocity profiling using inertial sensors for freestyle swimming. Sports Eng 16(1):1–11

    Article  Google Scholar 

  • StanÄŤin S, TomaĹľiÄŤ S (2013) Early improper motion detection in golf swings using wearable motion sensors: The first approach. Sensors 13(6):7505–7521

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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)

    Google Scholar 

  • 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

    Article  Google Scholar 

  • Umek, A., & Kos, A. (2018a). Smart equipment design challenges for real time feedback support in sport. Facta Universitatis, Series: Mechanical Engineering

    Google Scholar 

  • Umek A, Kos A (2018b) Wearable sensors and smart equipment for feedback in watersports. Procedia Comput Sci 129:496–502

    Article  Google Scholar 

  • Umek A, TomaĹľiÄŤ S, Kos A (2015) Wearable training system with real-time biofeedback and gesture user interface. Pers Ubiquit Comput 19(7):989–998

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • 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

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

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)

Publish with us

Policies and ethics