Tracking of strength training: validation of a motion-recognition algorithm and a pilot towards 1RM, muscle loading and fatique index using a smart watch

Lorenzetti, Silvio; Huber, Dominik (2018). Tracking of strength training: validation of a motion-recognition algorithm and a pilot towards 1RM, muscle loading and fatique index using a smart watch In: Hume, Patria A.; Alderson, Jacqueline A.; Wilson, Barry D. (eds.) 36th Conference of the International Society of Biomechanics in Sports. ISBS Proceedings Archive: Vol. 36 (pp. 886-889). Marquette, MI: Northern Michigan Univerity

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Ubiquitous wrist-worn devices have become a noteworthy research topic in motion recognition of strength training exercises. This study was designed to develop a watchOS and iOS application and assess its exercise recognition and repetition counting accuracy. As a pilot, a method to estimate the 1 repetition maximum and muscle stress and fatigue was explored. To test the exercise recognition and repetition counting accuracy, a workout consisting of nine sets with five randomly ordered resistance training exercises and repetition amounts was conducted when wearing an Apple watch. Overall mean %error in exercise recognition was 3.5% and 0.92% in repetition counting. In the future this app can also be used for estimation of 1 repetition maximum, muscle stress and fatigue.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

Swiss Federal Institute of Sports Magglingen SFISM > EHSM - Leistungssport

Name:

Lorenzetti, Silvio0000-0002-8339-8960;
Huber, Dominik;
Hume, Patria A.;
Alderson, Jacqueline A. and
Wilson, Barry D.

ISSN:

1999-4168

Series:

ISBS Proceedings Archive

Publisher:

Northern Michigan Univerity

Language:

English

Submitter:

Admin import user

Date Deposited:

24 Nov 2021 14:15

Last Modified:

24 Nov 2021 14:20

Related URLs:

Uncontrolled Keywords:

Strength training Sensor App Training control Training supervision

ARBOR DOI:

10.24451/arbor.10444

URI:

https://arbor.bfh.ch/id/eprint/10444

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