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

Authors
Type
Published Article
Journal
Sensors
1424-8220
Publisher
MDPI AG
Publication Date
Volume
14
Issue
2
Pages
2776–2794
Identifiers
DOI: 10.3390/s140202776
PMID: 24521944
Source
Medline

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.

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