Multi-Day Reliability of High-Density Electromyography for Continuous Control of Assistive Devices

Despite therapeutic efforts, individuals post-stroke often experience chronic hand deficits that can severely impact task performance and quality of life. Assistive devices could be beneficial but require user input to control the many degrees-of-freedom. High-density surface electromyography (HD-sEMG) affords a means of discerning user input but is susceptible to factors that may change from day to day, such as skin condition and electrode placement, thereby impacting the mapping from user input to desired assistance. The goal of this study was to examine the reliability of HD-sEMG control signals across multiple sessions. Eight neurotypical subjects participated in three separate sessions during which they created specified isometric flexion and extension forces with the index and middle fingers. Finger force and sEMG activity were captured throughout the trials, the latter with two high-density electrode arrays (192 channels) placed on the forearm. Models relating motor unit firing rate to fingertip force were created from the session 1 data. These models were directly employed in sessions 2 and 3 to predict fingertip force from HD-sEMG signals. While the error in model fit did increase significantly for the flexion direction for sessions 2 and 3 with respect to session 1, the increase was quite modest: error across all four models was 11.2±1.9% maximum voluntary force (MVF) (session 1), 14.4±1.7% MVF (session 2) and 14.6±2.0% MVF (session 3). These results suggest that it may be possible to employ motor unit firing models based on HD-sEMG for user input of assistive devices without revising the model each day.Clinical Relevance- This study establishes the multi-day reliability of a method to enable users during independent assistance to different digits to improve hand function.