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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| Format: | Article |
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MDPI AG
2023-02-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/4/970 |
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| author | Md. Mahmudur Rahman Kok Beng Gan Noor Azah Abd Aziz Audrey Huong Huay Woon You |
| author_facet | Md. Mahmudur Rahman Kok Beng Gan Noor Azah Abd Aziz Audrey Huong Huay Woon You |
| author_sort | Md. Mahmudur Rahman |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-11T08:28:46Z |
| format | Article |
| id | doaj.art-d49c9aad457646a69bc71bd315d3b5e7 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-11T08:28:46Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-d49c9aad457646a69bc71bd315d3b5e72023-11-16T21:56:33ZengMDPI AGMathematics2227-73902023-02-0111497010.3390/math11040970Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration AlgorithmMd. Mahmudur Rahman0Kok Beng Gan1Noor Azah Abd Aziz2Audrey Huong3Huay Woon You4Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaMedical Engineering and Systems Research Group, Department of Electrical, Electronic and Systems Engineering, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaDepartment of Family Medicine, Faculty of Medicine, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur 56000, MalaysiaDepartment of Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja 86400, MalaysiaPusat GENIUS@Pintar Negara, Universiti Kebangsaan Malaysia, Bangi 43600, MalaysiaIn 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.https://www.mdpi.com/2227-7390/11/4/970inertial measurement unitaccelerometergyroscopemagnetometerelectro-goniometerjoint angle |
| spellingShingle | Md. Mahmudur Rahman Kok Beng Gan Noor Azah Abd Aziz Audrey Huong Huay Woon You Upper Limb Joint Angle Estimation Using Wearable IMUs and Personalized Calibration Algorithm Mathematics inertial measurement unit accelerometer gyroscope magnetometer electro-goniometer joint angle |
| title | 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_short | 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 |
| topic | inertial measurement unit accelerometer gyroscope magnetometer electro-goniometer joint angle |
| url | https://www.mdpi.com/2227-7390/11/4/970 |
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