Fine motor control is achieved through the coordinated activation of groups of muscles, or “muscle synergies.” Muscle synergies change after stroke as a consequence of the motor deficit. We investigated the pattern and longitudinal changes in upper limb muscle synergies during therapy in a largely unconstrained movement in patients with a broad spectrum of poststroke residual voluntary motor capacity. Electromyography (EMG) was recorded using wireless telemetry from 6 muscles acting on the more-affected upper body in 24 stroke patients at early and late therapy during formal Wii-based Movement Therapy (WMT) sessions, and in a subset of 13 patients at 6-month follow-up. Patients were classified with low, moderate, or high motor-function. The Wii-baseball swing was analyzed using a non-negative matrix factorization (NMF) algorithm to extract muscle synergies from EMG recordings based on the temporal activation of each synergy and the contribution of each muscle to a synergy. Motor-function was clinically assessed immediately pre- and post-therapy and at 6-month follow-up using the Wolf Motor Function Test, upper limb motor Fugl-Meyer Assessment, and Motor Activity Log Quality of Movement scale. Clinical assessments and game performance demonstrated improved motor-function for all patients at post-therapy (p < 0.01), and these improvements were sustained at 6-month follow-up (p > 0.05). NMF analysis revealed fewer muscle synergies (mean ± SE) for patients with low motor-function (3.38 ± 0.2) than those with high motor-function (4.00 ± 0.3) at early therapy (p = 0.036) with an association trend between the number of synergies and the level of motor-function. By late therapy, there was no significant change between groups, although there was a pattern of increase for those with low motor-function over time. The variability accounted for demonstrated differences with motor-function level (p < 0.05) but not time. Cluster analysis of the pooled synergies highlighted the therapy-induced change in muscle activation. Muscle synergies could be identified for all patients during therapy activities. These results show less complexity and more co-activation in the muscle activation for patients with low motor-function as a higher number of muscle synergies reflects greater movement complexity and task-related phasic muscle activation. The increased number of synergies and changes within synergies by late-therapy suggests improved motor control and movement quality with more distinct phases of movement.

Poststroke weakness on the more-affected side may arise from reduced corticospinal drive, disuse muscle atrophy, spasticity, and abnormal coordination. This study investigated changes in muscle activation patterns to understand therapy-induced improvements in motor-function in chronic stroke compared to clinical assessments and to identify the effect of motor-function level on muscle activation changes. Electromyography (EMG) was recorded from five upper limb muscles on the more-affected side of 24 patients during early and late therapy sessions of an intensive 14-day program of Wii-based Movement Therapy (WMT) and for a subset of 13 patients at 6-month follow-up. Patients were classified according to residual voluntary motor capacity with low, moderate, or high motor-function levels. The area under the curve was calculated from EMG amplitude and movement duration. Clinical assessments of upper limb motor-function pre- and post-therapy included the Wolf Motor Function Test, Fugl-Meyer Assessment and Motor Activity Log Quality of Movement scale. Clinical assessments improved over time (p < 0.01) with an effect of motor-function level (p < 0.001). The pattern of EMG change by late therapy was complex and variable, with differences between patients with low compared to moderate or high motor-function levels. The area under the curve (p = 0.028) and peak amplitude (p = 0.043) during Wii-tennis backhand increased for patients with low motor-function, whereas EMG decreased for patients with moderate and high motor-function levels. The reductions included movement duration during Wii-golf (p = 0.048, moderate; p = 0.026, high) and Wii-tennis backhand (p = 0.046, moderate; p = 0.023, high) and forehand (p = 0.009, high) and the area under the curve during Wii-golf (p = 0.018, moderate) and Wii-baseball (p = 0.036, moderate). For the pooled data over time, there was an effect of motor-function (p = 0.016) and an interaction between time and motor-function (p = 0.009) for Wii-golf movement duration. Wii-baseball movement duration decreased as a function of time (p = 0.022). There was an effect on Wii-tennis forehand duration for time (p = 0.002), an interaction of time and motor-function (p = 0.005) and an effect of motor-function level on the area under the curve (p = 0.034) for Wii-golf. This study demonstrated different patterns of EMG changes according to residual voluntary motor-function levels, despite heterogeneity within each level that was not evident following clinical assessments alone. Thus, rehabilitation efficacy might be underestimated by analyses of pooled data.

Background Electroencephalographic (EEG) neurofeedback has been utilized to regulate abnormal brain activity associated with chronic pain. Methods In this systematic review, we synthesized the evidence from randomized controlled trials (RCTs) to evaluate the effect of EEG neurofeedback on chronic pain using random effects meta‐analyses. Additionally, we performed a narrative review to explore the results of non‐randomized studies. The quality of included studies was assessed using Cochrane risk of bias tools, and the GRADE system was used to rate the certainty of evidence. Results Ten RCTs and 13 non‐randomized studies were included. The primary meta‐analysis on nine eligible RCTs indicated that although there is low confidence, EEG neurofeedback may have a clinically meaningful effect on pain intensity in short‐term. Removing the studies with high risk of bias from the primary meta‐analysis resulted in moderate confidence that there remained a clinically meaningful effect on pain intensity. We could not draw any conclusion from the findings of non‐randomized studies, as they were mostly non‐comparative trials or explorative case series. However, the extracted data indicated that the neurofeedback protocols in both RCTs and non‐randomized studies mainly involved the conventional EEG neurofeedback approach, which targeted reinforcing either alpha or sensorimotor rhythms and suppressing theta and/or beta bands on one brain region at a time. A posthoc analysis of RCTs utilizing the conventional approach resulted in a clinically meaningful effect estimate for pain intensity. Conclusion Although there is promising evidence on the analgesic effect of EEG neurofeedback, further studies with larger sample sizes and higher quality of evidence are required.