**Author details**

Gongbing Shan University of Lethbridge, Lethbridge, Canada

\*Address all correspondence to: g.shan@uleth.ca

© 2020 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**51**

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

Acta Medica Scandinavica. 1986;**220**(S711):143-147

1991;**22**(3):379-392

Verlag; 1999. p. 183

[11] Petruzzello SJ, Landers DM, Salazar W. Biofeedback and sport/ exercise performance: Applications and limitations. Behavior Therapy.

[12] Shan G, Bohn C. Anthropometrical data and coefficients of regression related to gender and race. Applied Ergonomics. 2003;**34**(4):327-337

[13] Shan G. A Biomechanical Model for Motor Learning Based on Individual Anthropometrical Data. Müster: Lit

[14] Wąsik J et al. The influence of gender, dominant lower limb and type of target on the velocity of taekwon-do front kick. Acta of Bioengineering and Biomechanics. 2018;**20**(2):133-138

[15] Wan B, Shan G. Biomechanical modeling as a practical tool for predicting injury risk related to repetitive muscle lengthening during learning and training of human complex motor skills. Springerplus. 2016;**5**(1):441

[16] Visentin P et al. Unraveling mysteries of personal performance style; biomechanics of left-hand position changes (shifting) in violin performance. PeerJ. 2015;**3**:e1299

Enke Verlag; 1996

2003;**18**(1):3-10

[17] Ballreich R, Baumann W. Grundlagen der Biomechanik des Sports [The Basics of Biomechanics in Sports]. Stuttgart:

[18] Shan G, Visentin P. A quantitative three-dimensional analysis of arm kinematics in violin performance. Medical Problems of Performing Artists.

[19] Shan G et al. How can dynamic rigid-body modeling be helpful in motor learning?—Diagnosing performance

*DOI: http://dx.doi.org/10.5772/intechopen.91356*

[2] Magill RA. Motor Learning Concepts and Applications. 6th ed. Boston:

[3] Visentin P, Shan G, Wasiak EB. Informing music teaching and learning using movement analysis technology. International Journal of Music Education. 2008;**26**(1):73-87

[4] Zhang X et al. Wearables,

biomechanical feedback, and human motor-skills' learning & optimization. Applied Sciences. 2019;**9**(2):226

[5] Mischke J. Wearable Technology: The Latest Trend in Professional Sports. 2018. Available from: https://www. wearable-technologies.com/2018/05/ wearable-technology-the-latest-trend-inprofessional-sports/ [Cited: 28 July 2018]

[6] Seshadri DR et al. Wearable devices for sports: New integrated technologies allow coaches, physicians, and trainers to better understand the physical demands of athletes in real time. IEEE

[7] Bandodkar AJ, Wang J. Non-invasive wearable electrochemical sensors: A review. Trends in Biotechnology.

[8] Chambers R et al. The use of wearable microsensors to quantify sport-specific movements. Sports Medicine. 2015;**45**(7):1065-1081

Nature. 2016;**529**(7587):475

[10] Radin E. Role of muscles in protecting athletes from injury.

[9] Heikenfeld J. Bioanalytical devices: Technological leap for sweat sensing.

Pulse. 2017;**8**(1):38-43

2014;**32**(7):363-371

[1] Tate JJ, Milner CE. Real-time kinematic, temporospatial, and kinetic biofeedback during gait retraining in patients: A systematic review. Physical

Therapy. 2010;**90**:1123-1134

McGraw-Hill; 2001

**References**

*Challenges and Future of Wearable Technology in Human Motor-Skill Learning and Optimization DOI: http://dx.doi.org/10.5772/intechopen.91356*
