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Review

Extended Application of Inertial Measurement Units in Biomechanics: From Activity Recognition to Force Estimation

Key Laboratory for Space Bioscience and Biotechnology, School of Life Sciences, Northwestern Polytechnical University, Xi’an 710072, China
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Author to whom correspondence should be addressed.
Sensors 2023, 23(9), 4229; https://doi.org/10.3390/s23094229
Submission received: 27 February 2023 / Revised: 20 April 2023 / Accepted: 22 April 2023 / Published: 24 April 2023
(This article belongs to the Section Physical Sensors)

Abstract

Abnormal posture or movement is generally the indicator of musculoskeletal injuries or diseases. Mechanical forces dominate the injury and recovery processes of musculoskeletal tissue. Using kinematic data collected from wearable sensors (notably IMUs) as input, activity recognition and musculoskeletal force (typically represented by ground reaction force, joint force/torque, and muscle activity/force) estimation approaches based on machine learning models have demonstrated their superior accuracy. The purpose of the present study is to summarize recent achievements in the application of IMUs in biomechanics, with an emphasis on activity recognition and mechanical force estimation. The methodology adopted in such applications, including data pre-processing, noise suppression, classification models, force/torque estimation models, and the corresponding application effects, are reviewed. The extent of the applications of IMUs in daily activity assessment, posture assessment, disease diagnosis, rehabilitation, and exoskeleton control strategy development are illustrated and discussed. More importantly, the technical feasibility and application opportunities of musculoskeletal force prediction using IMU-based wearable devices are indicated and highlighted. With the development and application of novel adaptive networks and deep learning models, the accurate estimation of musculoskeletal forces can become a research field worthy of further attention.
Keywords: inertial measurement unit; human activity recognition; joint force; ground reaction force; machine learning inertial measurement unit; human activity recognition; joint force; ground reaction force; machine learning

Share and Cite

MDPI and ACS Style

Liang, W.; Wang, F.; Fan, A.; Zhao, W.; Yao, W.; Yang, P. Extended Application of Inertial Measurement Units in Biomechanics: From Activity Recognition to Force Estimation. Sensors 2023, 23, 4229. https://doi.org/10.3390/s23094229

AMA Style

Liang W, Wang F, Fan A, Zhao W, Yao W, Yang P. Extended Application of Inertial Measurement Units in Biomechanics: From Activity Recognition to Force Estimation. Sensors. 2023; 23(9):4229. https://doi.org/10.3390/s23094229

Chicago/Turabian Style

Liang, Wenqi, Fanjie Wang, Ao Fan, Wenrui Zhao, Wei Yao, and Pengfei Yang. 2023. "Extended Application of Inertial Measurement Units in Biomechanics: From Activity Recognition to Force Estimation" Sensors 23, no. 9: 4229. https://doi.org/10.3390/s23094229

APA Style

Liang, W., Wang, F., Fan, A., Zhao, W., Yao, W., & Yang, P. (2023). Extended Application of Inertial Measurement Units in Biomechanics: From Activity Recognition to Force Estimation. Sensors, 23(9), 4229. https://doi.org/10.3390/s23094229

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