Speech-Based Human-Exoskeleton Interaction for Lower Limb Motion Planning

TL;DR

This paper introduces a speech-based motion planning system for lower limb exoskeletons, enabling faster, hands-free control that enhances safety and stability for users with impairments.

Contribution

A novel speech-based control strategy integrating speech processing, finite state machine, and pattern generator for real-time exoskeleton trajectory planning.

Findings

Speech system achieved low word and intent errors.

Voice commands reduced completion time by 54%.

Users maintained postural stability hands-free.

Abstract

This study presents a speech-based motion planning strategy (SBMP) developed for lower limb exoskeletons to facilitate safe and compliant human-robot interaction. A speech processing system, finite state machine, and central pattern generator are the building blocks of the proposed strategy for online planning of the exoskeleton's trajectory. According to experimental evaluations, this speech-processing system achieved low levels of word and intent errors. Regarding locomotion, the completion time for users with voice commands was 54% faster than that using a mobile app interface. With the proposed SBMP, users are able to maintain their postural stability with both hands-free. This supports its use as an effective motion planning method for the assistance and rehabilitation of individuals with lower-limb impairments.