Wearable myoelectric interface enables high-dose, home-based training in severely impaired chronic stroke survivors

Abstract

Background: High-intensity occupational therapy can improve arm function after stroke, but many people lack access to such therapy. Home-based therapies could address this need, but they don't typically address abnormal muscle co-activation, an important aspect of arm impairment. An earlier study using lab-based, myoelectric computer interface game training enabled chronic stroke survivors to reduce abnormal co-activation and improve arm function. Here, we assess feasibility of doing this training at home using a novel, wearable, myoelectric interface for neurorehabilitation training (MINT) paradigm.

Objective: Assess tolerability and feasibility of home-based, high-dose MINT therapy in severely impaired chronic stroke survivors.

Methods: Twenty-three participants were instructed to train with the MINT and game for 90 min/day, 36 days over 6 weeks. We assessed feasibility using amount of time trained and game performance. We assessed tolerability (enjoyment and effort) using a customized version of the Intrinsic Motivation Inventory at the conclusion of training.

Results: Participants displayed high adherence to near-daily therapy at home (mean of 82 min/day of training; 96% trained at least 60 min/day) and enjoyed the therapy. Training performance improved and co-activation decreased with training. Although a substantial number of participants stopped training, most dropouts were due to reasons unrelated to the training paradigm itself.

Interpretation: Home-based therapy with MINT is feasible and tolerable in severely impaired stroke survivors. This affordable, enjoyable, and mobile health paradigm has potential to improve recovery from stroke in a variety of settings. Clinicaltrials.gov: NCT03401762.

Figure 1

MINT Device and electrodes. The MINT device (black case) was attached to a strap on the participant’s arm. The red line on the EMG sticker was used to guide participants to line up the recording electrodes (red clips) with the long axis of each muscle. The white clip is the reference electrode.

Figure 2

MINT training group screenshots and cursor mappings. Examples of screenshots and cursor mapping for the different MINT training groups. (A) In the sham control, participants controlled the cursor with one muscle in one direction (red arrow indicates mapping direction of increasing EMG activity). (B) The 2D group controlled the cursor as a vector sum of the two muscles (red arrows indicate mapping directions). (C) The Reach group provided similar feedback to the 2D group with the addition of prompting the participants to reach out in a direction using the targeted muscle (e.g., elbow flexion for biceps, green arrow). (D) The 3D group controlled the cursor as a vector sum of three muscles (dashed arrow, mapping into the screen). The game “skins” changed with each different set of muscles trained.

Figure 3

CONSORT flowchart.

Figure 4

Histogram of responses to questions assessing enjoyment (black) and effort (gray) from the modified IMI survey. Almost all participants enjoyed the training to some extent and were motivated to exert high effort.

Figure 5

Game performance and co‐activation improved with training. (A) Mean (±SE) performance (weighted TTT) over all trials on each day over participants from all groups, over all three muscle sets combined. Gray dashed line is best‐fit linear regression, R = −0.77, p = 0.008. (B) Co‐activation (R) over all experimental groups decreased significantly (*) from baseline (blue) to the last day of training (black). Data are combined over all three muscle sets.