loading
Documents

Research.Publish.Connect.

Paper

Authors: Sarvenaz Salehi 1 and Didier Stricker 2

Affiliations: 1 Daimler Protics, Germany ; 2 German Research Center for Artificial Intelligence (DFKI), Germany

ISBN: 978-989-758-403-9

ISSN: 2184-4380

Keyword(s): Inertial Sensors, Body-IMU Calibration, Body Motion Tracking, Exercise Monitoring.

Abstract: This work validates the application of a low-cost inertial tracking suit, for strength exercise monitoring. The procedure includes an offline processing for body-IMU calibration, online tracking and identification of lower body motion. We proposed an optimal movement pattern of the body-IMU calibration method from our previous work. Here in order to reproduce real extreme situations, we used data from different types of movements with high acceleration intensity. For such movements, an optimal orientation tracking approach is introduced which requires no accelerometer measurements and it thus minimizes error of existing outliers. The online tracking algorithm is based on an extended Kalman filter(EKF), which estimates the position of upper and lower legs with respect to the pelvis along with hip and knee joint angles. This method benefits from the estimated values in calibration process i.e. joint axes and positions, as well as biomechanical constraints of lower body. Therefore it req uires no aiding sensors such as magnetometer. The algorithm was evaluated using optical tracker for two types of exercises:squat and abd/adduction which resulted average Root Mean Square Error(RMSE) of 9cm. Additionally, this work presents a personalized exercise identification approach, where an online template matching algorithm is applied and optimised using Zero Velocity Crossing(ZVC) for feature extraction. This results reducing the execution time to 93% and improving the accuracy to 33%. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.208.132.33

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Salehi, S. and Stricker, D. (2020). Validation of a Low-cost Inertial Exercise Tracker.In Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS, ISBN 978-989-758-403-9, ISSN 2184-4380, pages 97-104. DOI: 10.5220/0008965800970104

@conference{sensornets20,
author={Sarvenaz Salehi. and Didier Stricker.},
title={Validation of a Low-cost Inertial Exercise Tracker},
booktitle={Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS,},
year={2020},
pages={97-104},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008965800970104},
isbn={978-989-758-403-9},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Sensor Networks - Volume 1: SENSORNETS,
TI - Validation of a Low-cost Inertial Exercise Tracker
SN - 978-989-758-403-9
AU - Salehi, S.
AU - Stricker, D.
PY - 2020
SP - 97
EP - 104
DO - 10.5220/0008965800970104

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.