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Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm

In physical therapy, exercises improve range of motion, muscle strength, and flexibility, where motion-tracking devices record motion data during exercises to improve treatment outcomes. Cameras and inertial measurement units (IMUs) are the basis of these devices. However, issues such as occlusion,...

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Main Authors: Rahman, Md. Mahmudur, Beng Gan, Kok, Abd Aziz, Noor Azah, Huong, , Audrey, You, Huay Woon
Format: Article
Language:English
Published: 2023
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/8600/1/J15791_db2f85e07307d354877a0361d6099ef4.pdf
http://eprints.uthm.edu.my/8600/
https://doi.org/10.3390/math11040970
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spelling my.uthm.eprints.86002023-05-02T02:10:42Z http://eprints.uthm.edu.my/8600/ Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm Rahman, Md. Mahmudur Beng Gan, Kok Abd Aziz, Noor Azah Huong, , Audrey You, Huay Woon T Technology (General) In physical therapy, exercises improve range of motion, muscle strength, and flexibility, where motion-tracking devices record motion data during exercises to improve treatment outcomes. Cameras and inertial measurement units (IMUs) are the basis of these devices. However, issues such as occlusion, privacy, and illumination can restrict vision-based systems. In these circumstances, IMUs may be employed to focus on a patient’s progress quantitatively during their rehabilitation. In this study, a 3D rigid body that can substitute a human arm was developed, and a two-stage algorithm was designed, implemented, and validated to estimate the elbow joint angle of that rigid body using three IMUs and incorporating the Madgwick filter to fuse multiple sensor data. Two electro-goniometers (EGs) were linked to the rigid body to verify the accuracy of the joint angle measuring algorithm. Additionally, the algorithm’s stability was confirmed even in the presence of external acceleration. Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996◦ In all cases, the joint angles were within therapeutic limits. 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/8600/1/J15791_db2f85e07307d354877a0361d6099ef4.pdf Rahman, Md. Mahmudur and Beng Gan, Kok and Abd Aziz, Noor Azah and Huong, , Audrey and You, Huay Woon (2023) Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm. Mathematics. pp. 1-17. https://doi.org/10.3390/math11040970
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Rahman, Md. Mahmudur
Beng Gan, Kok
Abd Aziz, Noor Azah
Huong, , Audrey
You, Huay Woon
Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm
description In physical therapy, exercises improve range of motion, muscle strength, and flexibility, where motion-tracking devices record motion data during exercises to improve treatment outcomes. Cameras and inertial measurement units (IMUs) are the basis of these devices. However, issues such as occlusion, privacy, and illumination can restrict vision-based systems. In these circumstances, IMUs may be employed to focus on a patient’s progress quantitatively during their rehabilitation. In this study, a 3D rigid body that can substitute a human arm was developed, and a two-stage algorithm was designed, implemented, and validated to estimate the elbow joint angle of that rigid body using three IMUs and incorporating the Madgwick filter to fuse multiple sensor data. Two electro-goniometers (EGs) were linked to the rigid body to verify the accuracy of the joint angle measuring algorithm. Additionally, the algorithm’s stability was confirmed even in the presence of external acceleration. Multiple trials using the proposed algorithm estimated the elbow joint angle of the rigid body with a maximum RMSE of 0.46◦ Using the IMU manufacturer’s (WitMotion) algorithm (Kalman filter), the maximum RMSE was 1.97◦ For the fourth trial, joint angles were also calculated with external acceleration, and the RMSE was 0.996◦ In all cases, the joint angles were within therapeutic limits.
format Article
author Rahman, Md. Mahmudur
Beng Gan, Kok
Abd Aziz, Noor Azah
Huong, , Audrey
You, Huay Woon
author_facet Rahman, Md. Mahmudur
Beng Gan, Kok
Abd Aziz, Noor Azah
Huong, , Audrey
You, Huay Woon
author_sort Rahman, Md. Mahmudur
title Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm
title_short Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm
title_full Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm
title_fullStr Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm
title_full_unstemmed Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm
title_sort upper limb joint angle estimation using wearable imus and personalized calibration algorithm
publishDate 2023
url http://eprints.uthm.edu.my/8600/1/J15791_db2f85e07307d354877a0361d6099ef4.pdf
http://eprints.uthm.edu.my/8600/
https://doi.org/10.3390/math11040970
_version_ 1765299035590098944
score 13.211869

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