Wearable Loop Sensors for Knee Flexion Monitoring: Dynamic Measurements on Human Subjects

• Published in: IEEE open journal of engineering in medicine and biology Vol. 5; pp. 542 - 550
• Main Authors: Anderson, Ian, Cosma, Christopher, Zhang, Yingzhe, Mishra, Vigyanshu, Kiourti, Asimina
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Angular resolution; Biomedical monitoring; Calibration; Cameras; Correlation coefficient; Correlation coefficients; dynamic motion capture; e-textile; Error detection; Gold; Human motion; human subject validation; Human subjects; joint flexion; Legged locomotion; Lidar; loop sensors; Monitoring; Motion capture; Network analysers; Phantoms; Root-mean-square errors; Sensors; Smart textiles; State-of-the-art reviews; Walking; Wearable sensors; Wearable technology; wearables; joint flexion; wearables; Calibration; dynamic motion capture; human subject validation; loop sensors; e-textile
• DOI: 10.1109/OJEMB.2024.3417376
• ISSN: 2644-1276

Goals: We have recently introduced a new class of wearable loop sensors for joint flexion monitoring that overcomes limitations in the state-of-the-art. Our previous studies reported a proof-of-concept on a cylindrical phantom limb, under static scenarios and with a rigid sensor. In this work, we evaluate our sensors, for the first time, on human subjects, under dynamic scenarios, using a flexible textile-based prototype tethered to a network analyzer. An untethered version is also presented and validated on phantoms, aiming towards a fully wearable design. Methods: Three dynamic activities (walking, brisk walking, and full flexion/extension, all performed in place) are used to validate the tethered sensor on ten (10) adults. The untethered sensor is validated upon a cylindrical phantom that is bent manually at random speed. A calibration mechanism is developed to derive the sensor-measured angles. These angles are then compared to gold-standard angles simultaneously captured by a light detection and ranging (LiDAR) depth camera using root mean square error (RMSE) and Pearson's correlation coefficient as metrics. Results: We find excellent correlation (≥ 0.981) to gold-standard angles. The sensor achieves an RMSE of 4.463° ± 1.266° for walking, 5.541° ± 2.082° for brisk walking, 3.657° ± 1.815° for full flexion/extension activities, and 0.670° ± 0.366° for the phantom bending test. Conclusion: The tethered sensor achieves similar to slightly higher RMSE as compared to other wearable flexion sensors on human subjects, while the untethered version achieves excellent RMSE on the phantom model. Concurrently, our sensors are reliable over time and injury-safe, and do not obstruct natural movement. Our results set the ground for future improvements in angular resolution and for realizing fully wearable designs, while maintaining the abovementioned advantages over the state-of-the-art.