Online phase detection using wearable sensors for walking with a robotic prosthesis

48Citations
Citations of this article
125Readers
Mendeley users who have this article in their library.

Abstract

This paper presents a gait phase detection algorithm for providing feedback in walking with a robotic prosthesis. The algorithm utilizes the output signals of a wearable wireless sensory system incorporating sensorized shoe insoles and inertial measurement units attached to body segments. The principle of detecting transitions between gait phases is based on heuristic threshold rules, dividing a steady-state walking stride into four phases. For the evaluation of the algorithm, experiments with three amputees, walking with the robotic prosthesis and wearable sensors, were performed. Results show a high rate of successful detection for all four phases (the average success rate across all subjects >90%). A comparison of the proposed method to an off-line trained algorithm using hidden Markov models reveals a similar performance achieved without the need for learning dataset acquisition and previous model training.

Cite

CITATION STYLE

APA

Goršič, M., Kamnik, R., Ambrožič, L., Vitiello, N., Lefeber, D., Pasquini, G., & Munih, M. (2014). Online phase detection using wearable sensors for walking with a robotic prosthesis. Sensors (Switzerland), 14(2), 2776–2794. https://doi.org/10.3390/s140202776

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free