Wearable magnetic induction-based approach toward 3D motion tracking

Negar Golestani; Mahta Moghaddam

doi:10.1038/s41598-021-98346-5

Wearable magnetic induction-based approach toward 3D motion tracking

Sci Rep. 2021 Sep 23;11(1):18905. doi: 10.1038/s41598-021-98346-5.

Authors

Negar Golestani¹, Mahta Moghaddam²

Affiliations

¹ Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA. golestani.negar@gmail.com.
² Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA.

Abstract

Activity recognition using wearable sensors has gained popularity due to its wide range of applications, including healthcare, rehabilitation, sports, and senior monitoring. Tracking the body movement in 3D space facilitates behavior recognition in different scenarios. Wearable systems have limited battery capacity, and many critical challenges have to be addressed to gain a trade-off among power consumption, computational complexity, minimizing the effects of environmental interference, and achieving higher tracking accuracy. This work presents a motion tracking system based on magnetic induction (MI) to tackle the challenges and limitations inherent in designing a wireless monitoring system. We integrated a realistic prototype of an MI sensor with machine learning techniques and investigated one-sensor and two-sensor configuration setups for motion reconstruction. This approach is successfully evaluated using measured and synthesized datasets generated by the analytical model of the MI system. The system has an average distance root-mean-squared error (RMSE) error of 3 cm compared to the ground-truth real-world measured data with Kinect.