Inertial Sensing for Gait Event Detection and Transfemoral Prosthesis Control Strategy

• Published in: IEEE transactions on biomedical engineering Vol. 65; no. 12; pp. 2704 - 2712
• Main Author: Ledoux, Elissa D.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Adult; Algorithms; Amputees; Artificial Limbs; Biosensors; Classification; Classification algorithms; Demographics; Discriminant analysis; Equipment Design; Error detection; Event detection; Force plates; Gait; Gait - physiology; Gait Analysis - instrumentation; Gait Analysis - methods; gait event detection; gait phase recognition; Gait recognition; Humans; Inertial platforms; Inertial sensing devices; Legged locomotion; Load cells; Middle Aged; Prostheses; Prosthetics; Signal Processing, Computer-Assisted; Slopes; Trans-femoral amputees; transfemoral amputee; Walking; Young Adult
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2018.2813999

Objective: This paper presents a method for walking gait event detection using a single inertial measurement unit (IMU) mounted on the shank. Methods: Experiments were conducted to detect heel strike (HS) and toe off (TO) gait events of 10 healthy subjects and 5 transfemoral amputees walking at various speeds and slopes on an instrumented treadmill. The performance of three different algorithms [thresholding (THR), linear discriminant analysis, and quadratic discriminant analysis] was evaluated on both timing and frequency of gait event detections compared to data collected using force plates. Results: Though all algorithms could be used reliably (within 8.2% stride temporal error and 0.2% frequency error), THR was the most accurate, detecting 100% of gait events within an average of 2% stride for both the healthy subjects and the amputees. Furthermore, universal parameters could be used across all speeds and slopes within each demographic. Conclusion: HS and TO for walking gait can be reliably detected in healthy and transfemoral amputee subjects using a single IMU. Significance: This work provides a robust, simple, and inexpensive method of gait event detection that does not rely on a load cell and could be easily implemented in a lower-limb prosthesis.