Simulating Ankle Torque during Walking Using a new Bioinspired Muscle Model with Application for Controlling a Powered Exoskeleton
Safoura Sadegh Pour Aji Bishe, Dan Rivera, Katherine Strausser,, Zachary Lerner, and Kiisa Nishikawa

TL;DR
This study introduces a novel muscle model-based control strategy for ankle exoskeletons that predicts muscle torque without EMG signals, enabling more adaptable and human-like assistance during walking.
Contribution
The paper presents the winding filament muscle model controller (WFMC), the first control approach based on a muscle model that does not rely on EMG signals, enhancing exoskeleton control versatility.
Findings
WFMC accurately predicts ankle torque during walking.
The control strategy adapts to different walking speeds and terrains.
Potential for improved exoskeleton design for diverse patient needs.
Abstract
Human-like motion is a primary goal for many robotic assistive devices. Emulating the strategy of the human neuromuscular system may aid the control of such powered devices, yet many challenges remain. In this study, we investigated the potential for using the winding filament model (WFM) of muscle to predict the net muscle moment of the ankle. The long-term goal is to use this model to improve ankle control of a commercial powered exoskeleton. The innovation aspects of this study are: First, there have been no commercialized active ankle exoskeletons available in the market. All the available exoskeletons have passive ankle joints, which cannot mimic human movement, especially in normal and fast walking [1]. Second, the Winding Filament Model Controller (WFMC) is the first control strategy based on a muscle model that does not use an electromyographic (EMG) signal as an input. The…
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Taxonomy
TopicsMuscle activation and electromyography studies · Prosthetics and Rehabilitation Robotics · Spinal Cord Injury Research
