Upper Limb Stroke Rehabilitation Using Surface Electromyography: A Systematic Review and Meta-Analysis

Performance in myoelectric pattern recognition improves with transcranial direct current stimulation

Sensorimotor impairments, resulting from conditions like stroke and amputations, can profoundly impact an individual's functional abilities and overall quality of life. Assistive and rehabilitation devices such as prostheses, exo-skeletons, and serious gaming in virtual environments can help to restore some degree of function and alleviate pain after sensorimotor impairments. Myoelectric pattern recognition (MPR) has gained popularity in the past decades as it provides superior control over said devices, and therefore efforts to facilitate and improve performance in MPR can result in better rehabilitation outcomes. One possibility to enhance MPR is to employ transcranial direct current stimulation (tDCS) to facilitate motor learning. Twelve healthy able-bodied individuals participated in this crossover study to determine the effect of tDCS on MPR performance. Baseline training was followed by two sessions of either sham or anodal tDCS using the dominant and non-dominant arms. Assignments were randomized, and the MPR task consisted of 11 different hand/wrist movements, including rest or no movement. Surface electrodes were used to record EMG and the MPR open-source platform, BioPatRec, was used for decoding motor volition in real-time. The motion test was used to evaluate performance. We hypothesized that using anodal tDCS to increase the excitability of the primary motor cortex associated with non-dominant side in able-bodied individuals, will improve motor learning and thus MPR performance. Overall, we found that tDCS enhanced MPR performance, particularly in the non-dominant side. We were able to reject the null hypothesis and improvements in the motion test's completion rate during tDCS (28% change, p-value: 0.023) indicate its potential as an adjunctive tool to enhance MPR and motor learning. tDCS appears promising as a tool to enhance the learning phase of using assistive devices using MPR, such as myoelectric prostheses.

A novel scoring approach for the Wolf Motor Function Test in stroke survivors using motion-sensing technology and machine learning: A preliminary study

BACKGROUND AND OBJECTIVE

Human-administered clinical scales, such as the Functional Ability Scale of the Wolf Motor Function Test (WMFT-FAS), are widely utilized to evaluate upper-limb motor function in stroke survivors. However, these scales are generally subjective and labor-intensive. To end this, we proposed a novel scoring approach for the motor function assessment.

METHODS

The proposed novel scoring approach mainly contained one Microsoft Kinect v2, one customized motion tracking system, and one customized intelligent scoring system. Specifically, the Kinect v2 was used to capture stroke survivors' functional movements, the motion tracking system was developed for recording the gathered movement data, and the intelligent scoring system (kernel: feed-forward neural network, FFNN) was developed to evaluate movement quality and provide corresponding WMFT-FAS scores. Several methods have been applied to enhance the approach's usability, such as singular spectrum analysis and multi-ReliefF method.

RESULTS

Sixteen stroke survivors and ten healthy subjects were recruited for validation. Inspiring results of the proposed approach were achieved when compared with the clinical scores provided by a physiotherapist: 0.924 ± 0.027 for accuracy, 0.875 ± 0.063 for F1-score, 0.915 ± 0.051 for sensitivity, 0.969 ± 0.013 for specificity, 0.952 ± 0.038 for AUC, 0.098 ± 0.037 for mean absolute error, and 0.214 ± 0.078 for root mean squared error.

CONCLUSIONS

The results indicate that the proposed novel scoring approach can provide objective and accurate assessment scores, which can help physiotherapists make individualized treatment decisions.

Surface-Electromyography-Based Co-Contraction Index for Monitoring Upper Limb Improvements in Post-Stroke Rehabilitation: A Pilot Randomized Controlled Trial Secondary Analysis

Persons post-stroke experience excessive muscle co-contraction, and consequently the arm functions are compromised during the activities of daily living. Therefore, identifying instrumental outcome measures able to detect the motor strategy adopted after a stroke is a primary clinical goal. Accordingly, this study aims at verifying whether the surface electromyography (sEMG)-based co-contraction index (CCI) could be a new clinically feasible approach for assessing and monitoring patients' motor performance. Thirty-four persons post-stroke underwent clinical assessment and upper extremity kinematic analysis, including sEMG recordings. The participants were randomized into two treatment groups (robot and usual care groups). Ten healthy subjects provided a normative reference (NR). Frost's CCI was used to quantify the muscle co-contraction of three different agonist/antagonist muscle pairs during an object-placing task. Persons post-stroke showed excessive muscle co-contraction (mean (95% CI): anterior/posterior deltoid CCI: 0.38 (0.34-0.41) p = 0.03; triceps/biceps CCI: 0.46 (0.41-0.50) p = 0.01) compared to NR (anterior/posterior deltoid CCI: 0.29 (0.21-0.36); triceps/biceps CCI: 0.34 (0.30-0.39)). After robot therapy, persons post-stroke exhibited a greater improvement (i.e., reduced CCI) in proximal motor control (anterior/posterior deltoid change score of CCI: -0.02 (-0.07-0.02) p = 0.05) compared to usual care therapy (0.04 (0.00-0.09)). Finally, the findings of the present study indicate that the sEMG-based CCI could be a valuable tool in clinical practice.

Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study

After stroke, upper limb motor impairment is one of the most common consequences that compromises the level of the autonomy of patients. In a neurorehabilitation setting, the implementation of wearable sensors provides new possibilities for enhancing hand motor recovery. In our study, we tested an innovative wearable (REMO^®) that detected the residual surface-electromyography of forearm muscles to control a rehabilitative PC interface. The aim of this study was to define the clinical features of stroke survivors able to perform ten, five, or no hand movements for rehabilitation training. 117 stroke patients were tested: 65% of patients were able to control ten movements, 19% of patients could control nine to one movement, and 16% could control no movements. Results indicated that mild upper limb motor impairment (Fugl-Meyer Upper Extremity ≥ 18 points) predicted the control of ten movements and no flexor carpi muscle spasticity predicted the control of five movements. Finally, severe impairment of upper limb motor function (Fugl-Meyer Upper Extremity > 10 points) combined with no pain and no restrictions of upper limb joints predicted the control of at least one movement. In conclusion, the residual motor function, pain and joints restriction, and spasticity at the upper limb are the most important clinical features to use for a wearable REMO^® for hand rehabilitation training.

Acupuncture combined with repeated transcranial magnetic stimulation for upper limb motor function after stroke: A systematic review and meta-analysis

BACKGROUND

Upper limb motor dysfunction after stroke is an important factor affecting patients' motor function and daily life. Acupuncture and repetitive transcranial magnetic stimulation are effective methods for stroke rehabilitation. However, a systematic and comprehensive overview of the combined efficacy of the two is lacking.

OBJECTIVE

Through a systematic review and meta-analysis of randomized controlled trials, this study aimed to assess the effectiveness of acupuncture combined with repetitive transcranial magnetic stimulation on upper extremity motor function in post-stroke patients.

METHODS

The relevant randomized controlled trials on acupuncture combined with repetitive transcranial magnetic stimulation in the treatment of upper limb motor disorders after stroke were searched in PubMed, Embase, Cochrane Library, Web of Science CNKI, VIP, Wanfang, and CBM databases. After screening clinical trials that met the inclusion criteria, data extraction was conducted independently by two investigators. Meta-analysis was performed using RevMan 5.4 software.

RESULTS

After the screening, 18 articles were included, with a total of 1083 subjects. The results of meta-analysis showed that combination therapy could effectively improve the patients' upper limb motor function (MD = 7.77, 95%CI [6.32, 9.22], P < 0.05), ability of daily living (MD = 8.53, 95%CI [6.28, 10.79], P < 0.05), and hemiplegic shoulder pain (MD = - 1.72, 95%CI [- 2.26, - 1.18], P < 0.05). Meanwhile, for neurophysiological indexes, combined treatment could significantly shorten the latency of motor evoked potential and central motor conduction time (MD = - 1.42, 95%CI [- 2.14, - 0.71], P < 0.05); (MD = - 0.47, 95%CI [- 0.66, - 0.29], P < 0.05), and also could increase the amplitude of motor evoked potential (SMD = 0.71, 95%CI [0.28, 1.14], P < 0.05).

CONCLUSION

According to the results of the meta-analysis, we can conclude that acupuncture combined with repeated transcranial magnetic stimulation can significantly improve the upper limb motor function and daily living ability of stroke patients.