From Control Algorithm to Human Trial: Biomechanical Proof of a Speed-Adaptive Ankle–Foot Orthosis for Foot Drop in Level-Ground Walking

Background/Objectives: This study focuses on the motion planning and control of an active ankle–foot orthosis (AFO) that leverages biomechanical insights to mitigate footdrop, a deficit that prevents safe toe clearance during walking. Methods: To adapt the motion of the device to the user’s walking speed, a geometric model was used, together with real-time measurement of the user’s gait cycle. A geometric speed-adaptive model also scales a trapezoidal ankle-velocity profile in real time using the detected gait cycle. The algorithm was tested at three different walking speeds, with a prototype of the AFO worn by a test subject. Results: At walking speeds of 0.44 and 0.61 m/s, reduced tibialis anterior (TA) muscle activity was confirmed by electromyography (EMG) signal measurement during the stance phase of assisted gait. When the AFO was in assistance mode after toe-off (initial and mid-swing phase), it provided an average of 48% of the estimated required power to make up for the deliberate inactivity of the TA muscle. Conclusions: Kinematic analysis of the motion capture data showed that sufficient foot clearance was achieved at all three speeds of the test. No adverse effects or discomfort were reported during the experiment. Future studies should examine the device in populations with footdrop and include a comprehensive evaluation of safety.

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Publication Details

Journal
Biomechanics
Published
2025-07-04
DOI
https://doi.org/10.3390/biomechanics5030051
Primary Topic
Prosthetics and Rehabilitation Robotics
Type
article
Field-Weighted Citation Impact
0.00

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article

From Control Algorithm to Human Trial: Biomechanical Proof of a Speed-Adaptive Ankle–Foot Orthosis for Foot Drop in Level-Ground Walking

Pouyan Mehryar, Abbas A. Dehghani-Sanij, Sina Firouzy, Uriel Martínez-Hernández
Biomechanics
Prosthetics and Rehabilitation Robotics
article

From Control Algorithm to Human Trial: Biomechanical Proof of a Speed-Adaptive Ankle–Foot Orthosis for Foot Drop in Level-Ground Walking

Pouyan Mehryar, Abbas A. Dehghani-Sanij, Sina Firouzy, Uriel Martínez-Hernández
article en

Abstract

Background/Objectives: This study focuses on the motion planning and control of an active ankle–foot orthosis (AFO) that leverages biomechanical insights to mitigate footdrop, a deficit that prevents safe toe clearance during walking. Methods: To adapt the motion of the device to the user’s walking speed, a geometric model was used, together with real-time measurement of the user’s gait cycle. A geometric speed-adaptive model also scales a trapezoidal ankle-velocity profile in real time using the detected gait cycle. The algorithm was tested at three different walking speeds, with a prototype of the AFO worn by a test subject. Results: At walking speeds of 0.44 and 0.61 m/s, reduced tibialis anterior (TA) muscle activity was confirmed by electromyography (EMG) signal measurement during the stance phase of assisted gait. When the AFO was in assistance mode after toe-off (initial and mid-swing phase), it provided an average of 48% of the estimated required power to make up for the deliberate inactivity of the TA muscle. Conclusions: Kinematic analysis of the motion capture data showed that sufficient foot clearance was achieved at all three speeds of the test. No adverse effects or discomfort were reported during the experiment. Future studies should examine the device in populations with footdrop and include a comprehensive evaluation of safety.

BiomechanicsVol. 5(3)
University of Leeds (GB), Imperial College London (GB), University of Bath (GB)
Royal Society, University of Leeds, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 85%
Prosthetics and Rehabilitation Robotics
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From Control Algorithm to Human Trial: Biomechanical Proof of a Speed-Adaptive Ankle–Foot Orthosis for Foot Drop in Level-Ground Walking — Pouyan Mehryar, Abbas A. Dehghani-Sanij, et al. · Biomechanics (2025) | TGRS Research Map | TGRS