TRACKING OF STRENGTH TRAINING: VALIDATION OF A MOTION-RECOGNITION ALGORITHM & A PILOT TOWARDS 1RM, MUSCLE LOADING AND FATIGUE INDEX USING A SMARTWATCH APP

Authors

Silvio Lorenzetti, Swiss Federal Institute of Sport Magglingen SFISMFollow
Dominik Huber, Institute for Biomechanics, ETH Zurich

Category

Technology/equipment

Document Type

Paper

Abstract

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. Furthermore, as a pilot, a method to estimate the 1 repetition maximum and muscle stress and fatigue is 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.

Recommended Citation

Lorenzetti, Silvio and Huber, Dominik (2018) "TRACKING OF STRENGTH TRAINING: VALIDATION OF A MOTION-RECOGNITION ALGORITHM & A PILOT TOWARDS 1RM, MUSCLE LOADING AND FATIGUE INDEX USING A SMARTWATCH APP," ISBS Proceedings Archive: Vol. 36: Iss. 1, Article 214.
Available at: https://commons.nmu.edu/isbs/vol36/iss1/214