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Myoelectric interface training enables targeted reduction in abnormal muscle co-activation
Journal of NeuroEngineering and Rehabilitation volume 19, Article number: 67 (2022)
Abstract
Background
Abnormal patterns of muscle co-activation contribute to impaired movement after stroke. Previously, we developed a myoelectric computer interface (MyoCI) training paradigm to improve stroke-induced arm motor impairment by reducing the abnormal co-activation of arm muscle pairs. However, it is unclear to what extent the paradigm induced changes in the overall intermuscular coordination in the arm, as opposed to changing just the muscles trained with the MyoCI. This study examined the intermuscular coordination patterns of thirty-two stroke survivors who participated in 6 weeks of MyoCI training.
Methods
We used non-negative matrix factorization to identify the arm muscle synergies (coordinated patterns of muscle activity) during a reaching task before and after the training. We examined the extent to which synergies changed as the training reduced motor impairment. In addition, we introduced a new synergy analysis metric, disparity index (DI), to capture the changes in the individual muscle weights within a synergy.
Results
There was no consistent pattern of change in the number of synergies across the subjects after the training. The composition of muscle synergies, calculated using a traditional synergy similarity metric, also did not change after the training. However, the disparity of muscle weights within synergies increased after the training in the participants who responded to MyoCI training—that is, the specific muscles that the MyoCI was targeting became less correlated within a synergy. This trend was not observed in participants who did not respond to the training.
Conclusions
These findings suggest that MyoCI training reduced arm impairment by decoupling only the muscles trained while leaving other muscles relatively unaffected. This suggests that, even after injury, the nervous system is capable of motor learning on a highly fractionated level. It also suggests that MyoCI training can do what it was designed to do—enable stroke survivors to reduce abnormal co-activation in targeted muscles.
Trial registration This study was registered at ClinicalTrials.gov (NCT03579992, Registered 09 July 2018—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03579992?term=NCT03579992&draw=2&rank=1)
Background
Stroke, the largest cause of long-term disability worldwide, often damages motor pathways in the brain and induces abnormal spatiotemporal patterns of co-activation across arm muscles [1], also called abnormal muscle synergies [2,3,4,5]. Using dimensionality reduction methods, such as non-negative matrix factorization (NMF) or principal component analysis (PCA), several studies characterized the stroke-induced abnormal muscle synergies based on the electromyography (EMG) signals of the arm muscles [6,7,8]. Commonly observed abnormal muscle synergies after stroke include coupling of activity between elbow flexors and shoulder abductors during isometric torque generation [1, 4] and dynamic reaching [9]. Moreover, stroke induces co-activation of the anterior, middle, and posterior deltoid during the stable force maintaining phase of the isometric reaching task [7]. This co-activation inhibits the ability to flex the shoulder maximally. These abnormal patterns contribute to motor impairment and reduced function after stroke, partially by limiting range of motion during reaching [10, 11]. Thus, targeting these abnormal patterns is a potential new avenue for stroke rehabilitation.
Our previous study developed a myoelectric computer interface (MyoCI) paradigm to reduce abnormal co-activation and thereby impairment [12, 13]. Mugler et al. [13] examined 6 weeks of in-lab MyoCI training in thirty-two chronic stroke survivors with moderate-to-severe impairment. Before the training, each participant went through a screening process to identify the three most abnormally co-activating arm muscle pairs (defined by pairwise correlation coefficients) during free-reaching to targets, placed at waist and shoulder height, in front of and lateral to the impaired limb. After the screening, the participants were randomized to three different training groups (60 and 90 min using isometric activation; 90 min with activation during unrestricted movement). The participants were trained on and learned to activate each identified muscle pair separately for 2 weeks. At the end of the MyoCI training, participants had reduced arm impairment (measured using the Fugl-Meyer Assessment), improved motor function and elbow range-of-motion, and reduced spasticity (measured with the Modified Ashworth Scale). However, it remains unclear how MyoCI training affected intermuscular coordination in the arm in reaching movements.
Here, we investigate to what extent MyoCI training changed intermuscular coordination. We assessed the composition and number of muscle synergies as effects on the more global arm muscle network. Further, we augmented our muscle synergy analysis by developing the disparity index (DI), which measures the disparity between the synergy activation weights of each pair of muscles trained.
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