1
|
Tan JS, Beheshti BK, Binnie T, Davey P, Caneiro JP, Kent P, Smith A, O’Sullivan P, Campbell A. Human Activity Recognition for People with Knee Osteoarthritis-A Proof-of-Concept. SENSORS (BASEL, SWITZERLAND) 2021; 21:3381. [PMID: 34066265 PMCID: PMC8152007 DOI: 10.3390/s21103381] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 05/05/2021] [Accepted: 05/05/2021] [Indexed: 11/16/2022]
Abstract
Clinicians lack objective means for monitoring if their knee osteoarthritis patients are improving outside of the clinic (e.g., at home). Previous human activity recognition (HAR) models using wearable sensor data have only used data from healthy people and such models are typically imprecise for people who have medical conditions affecting movement. HAR models designed for people with knee osteoarthritis have classified rehabilitation exercises but not the clinically relevant activities of transitioning from a chair, negotiating stairs and walking, which are commonly monitored for improvement during therapy for this condition. Therefore, it is unknown if a HAR model trained on data from people who have knee osteoarthritis can be accurate in classifying these three clinically relevant activities. Therefore, we collected inertial measurement unit (IMU) data from 18 participants with knee osteoarthritis and trained convolutional neural network models to identify chair, stairs and walking activities, and phases. The model accuracy was 85% at the first level of classification (activity), 89-97% at the second (direction of movement) and 60-67% at the third level (phase). This study is the first proof-of-concept that an accurate HAR system can be developed using IMU data from people with knee osteoarthritis to classify activities and phases of activities.
Collapse
Affiliation(s)
- Jay-Shian Tan
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | | | - Tara Binnie
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | - Paul Davey
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | - J. P. Caneiro
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | - Peter Kent
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | - Anne Smith
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | - Peter O’Sullivan
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| | - Amity Campbell
- School of Allied Health, Faculty of Health Sciences, Curtin University, Perth 6845, Australia; (J.-S.T.); (T.B.); (P.D.); (J.P.C.); (A.S.); (P.O.); (A.C.)
| |
Collapse
|