Closing the Wearable Gap–Part IX: Validation of an Improved Ankle Motion Capture Wearable

• Main Authors: Will Carroll, Alana Turner, Purva Talegaonkar, Erin Parker, J. Carver Middleton, Preston Peranich, David Saucier, Reuben F. Burch, John E. Ball, Brian K. Smith, Harish Chander, Adam C. Knight, Charles E. Freeman
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Biomechanics; body sensor networks; soft robotics; wearable computers; wearable sensors; stretch sensors
• Online Access: https://ieeexplore.ieee.org/document/9508398/
• ISSN: 2169-3536

Soft robotic sensors, a class of pliable, embeddable sensors, are well-suited for applications in wearable technology because of their ease of integration with common clothing articles. The suitability of soft robotic sensors for estimation of human joint angles has been proven; this research represents another step towards development of a reliable laboratory data collection platform for the human ankle joint complex. In this research, the accuracy and repeatability of a newly-developed wearable prototype are evaluated as a potential replacement for camera-based motion capture by measuring differences between simultaneously collected motion capture and stretch sensor data. The accuracy of these measurements is compared to measurements collected using a previous prototype for validation. Results show that the newly-developed prototype is capable of joint angle estimation within 1.86° mean-absolute-error during complex, dynamic movements and that wearing shoes over the sock prototype does not significantly degrade performance.