A Simple Low-Cost Wearable Sensor for Long-Term Ambulatory Monitoring of Knee Joint Kinematics

• Published in: IEEE transactions on biomedical engineering Vol. 67; no. 12; pp. 3483 - 3490
• Main Authors: Oubre, Brandon, Daneault, Jean-Francois, Boyer, Katherine, Kim, Jae Hyun, Jasim, Mahmood, Bonato, Paolo, Lee, Sunghoon Ivan
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biomechanical Phenomena; Biomedical monitoring; Drug therapy; Humans; Joints (anatomy); Kinematics; Knee; Knee Joint; knee joint kinematics; Legged locomotion; Locomotion; long-term monitoring; Low cost; Monitoring; Monitoring, Ambulatory; Musculoskeletal diseases; Rehabilitation; remote monitoring; Root-mean-square errors; Sensors; Soft wearable sensor; Walking; Wearable Electronic Devices; Wearable sensors; Wearable technology
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2020.2988438

Objective: Accurate monitoring of joint kinematics in individuals with neuromuscular and musculoskeletal disorders within ambulatory settings could provide important information about changes in disease status and the effectiveness of rehabilitation programs and/or pharmacological treatments. This paper introduces a reliable, power efficient, and low-cost wearable system designed for the long-term monitoring of joint kinematics in ambulatory settings. Methods: Seventeen healthy subjects wore a retractable string sensor, fixed to two anchor points on the opposing segments of the knee joint, while walking at three different self-selected speeds. Joint angles were estimated from calibrated sensor values and their derivatives in a leave-one-subject-out cross validation manner using a random forest algorithm. Results: The proposed system estimated knee flexion/extension angles with a root mean square error (RMSE) of <inline-formula><tex-math notation="LaTeX">5.0^{\circ }\pm 1.0^{\circ }</tex-math></inline-formula> across the study subjects upon removal of a single outlier subject. The outlier was likely a result of sensor miscalibration. Conclusion: The proposed wearable device can accurately estimate knee flexion/extension angles during locomotion at various walking speeds. Significance: We believe that our novel wearable technology has great potential to enable joint kinematic monitoring in ambulatory settings and thus provide clinicians with an opportunity to closely monitor joint recovery, develop optimal, personalized rehabilitation programs, and ultimately maximize therapeutic outcomes.