Real-time Neuromuscular Control of Exoskeletons

Paused · Not applicable

Conditions studied: Stroke

In brief

The purpose of this study is to develop a real-time controller for exoskeletons using neural information embedded in human musculature. This controller will consist of an online interface that anticipates human movement based on high-density electromyography (HD-EMG) recordings, and then translates it into functional assistance. This study will be carried out in both healthy participants and participants post-stroke. The researchers will develop an online algorithm (decoder) in currently existing exoskeletons that can extract hundreds of motor unit (MU) spiking activity out of HD-EMG recordings. The MU spiking activity is a train of action potentials coded by its timing of occurrence that gives access to a representative part of the neural code of human movement. The researchers will also develop a command encoder that can anticipate human intent (multi-joint position and force commands) from MU spiking activity to translate the neural information to movement. The researchers will integrate the decoder with the command encoder to showcase the real-time control of multiple joint lower-limb exoskeletons.

Key facts

Study ID
NCT04661891
Run by
Shirley Ryan AbilityLab
People needed
80
Starts
2021-05-05
Expected to finish
2026-07-15
Last updated by the study team
2026-07-14

Who can join

Age: 18 and older, up to 80. Sex: any. Healthy volunteers: accepted.

Where it is running

Full record on ClinicalTrials.gov

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