EMG biofeedback combined with rehabilitation training may be the best physical therapy for improving upper limb motor function and relieving pain in patients with the post-stroke shoulder-hand syndrome: A Bayesian network meta-analysis

Advancing clinical understanding of surface electromyography biofeedback: bridging research, teaching, and commercial applications

INTRODUCTION

Expanding the use of surface electromyography-biofeedback (EMG-BF) devices in different therapeutic settings highlights the gradually evolving role of visualizing muscle activity in the rehabilitation process. This review evaluates their concepts, uses, and trends, combining evidence-based research.

AREAS COVERED

This review dissects the anatomy of EMG-BF systems, emphasizing their transformative integration with machine-learning (ML) and deep-learning (DL) paradigms. Advances such as the application of sophisticated DL architectures for high-density EMG data interpretation, optimization techniques for heightened DL model performance, and the fusion of EMG with electroencephalogram (EEG) signals have been spotlighted for enhancing biomechanical analyses in rehabilitation. The literature survey also categorizes EMG-BF devices based on functionality and clinical usage, supported by insights from commercial sectors.

EXPERT OPINION

The current landscape of EMG-BF is rapidly evolving, chiefly propelled by innovations in artificial intelligence (AI). The incorporation of ML and DL into EMG-BF systems augments their accuracy, reliability, and scope, marking a leap in patient care. Despite challenges in model interpretability and signal noise, ongoing research promises to address these complexities, refining biofeedback modalities. The integration of AI not only predicts patient-specific recovery timelines but also tailors therapeutic interventions, heralding a new era of personalized medicine in rehabilitation and emotional detection.

Assessing the effectiveness of biofeedback therapy in the rehabilitation of limb motor dysfunction after stroke and the influencing factors of disease-related shame

OBJECTIVE

To evaluate the effectiveness of biofeedback therapy in the rehabilitation of limb motor dysfunction after stroke and the factors influencing disease-related shame.

METHODS

Medical records of 118 patients with limb motor dysfunction after stroke, treated in 521 Hospital of the Norinco Group from October 2019 to November 2022, were collected. The 56 patients in control group received conventional rehabilitation training, while the other 62 patients in observation group received electromyographic biofeedback therapy in addition to conventional treatment. The therapeutic effects of both groups were evaluated and compared after 4 weeks of treatment. Changes in FMA (Fugl-Meyer Motor Function Assessment Scale), mRS (Modified Rankin Scale), ADL (Activities of Daily Living Scale), and SSS (Stroke Stigma Scale) were compared before and after treatment. Multivariate logistic regression analysis was used to analyze the factors influencing disease-related shame after treatment. The effectiveness of risk factors in predicting disease-related shame was analyzed using receiver operating characteristic (ROC) curves.

RESULTS

Upon intervention, significant gains were noted in FMA and ADL scores, with reductions in mRS and SSS (P<0.0001). After 4 weeks, the observation group showed higher FMA and ADL scores and lower mRS and SSS (P<0.0001 for FMA and ADL; P<0.05 for mRS and SSS). Logistic regression identified age ≥60 (OR 8.045, P<0.001), income <4000 yuan (OR 0.187, P=0.002), and pretreatment ADL (OR 0.047, P<0.001) as predictors of disease-related shame. The AUC for age, household monthly income, and pretreatment ADL score were 0.595 (P=0.089), 0.608 (P=0.053), and 0.750 (P<0.001), respectively, demonstrating pretreatment ADL score as the most accurate predictor of disease-related shame.

CONCLUSIONS

Electromyographic biofeedback therapy has a significant effect on the rehabilitation of stroke patients, especially on motor recovery and activities of daily living. Age, monthly family income and pre-treatment ADL scores are key factors influencing disease-related shame.

Effectiveness of acupuncture for pain relief in shoulder-hand syndrome after stroke: a systematic evaluation and Bayesian network meta-analysis

Background

Shoulder-hand syndrome (SHS) is a common complication after stroke, and SHS-induced pain significantly hampers patients' overall recovery. As an alternative therapy for pain relief, acupuncture has certain advantages in alleviating pain caused by SHS after stroke. However, choosing the best treatment plan from a variety of acupuncture options is still a serious challenge in clinical practice. Therefore, we conducted this Bayesian network meta-analysis to comprehensively compare the effectiveness of various acupuncture treatment methods.

Methods

We systematically searched for randomized controlled trials (RCTs) of acupuncture treatment in patients with post-stroke SHS published in PubMed, Embase, Cochrane, and Web of Science until 9 March 2023. We used the Cochrane bias risk assessment tool to assess the bias risk in the included original studies.

Results

A total of 50 RCTs involving 3,999 subjects were included, comprising 19 types of effective acupuncture interventions. Compared to single rehabilitation training, the top three interventions for VAS improvement were floating needle [VAS = -2.54 (95% CI: -4.37 to -0.69)], rehabilitation + catgut embedding [VAS = -2.51 (95% CI: -4.33 to -0.68)], and other multi-needle acupuncture combinations [VAS = -2.32 (95% CI: -3.68 to -0.94)]. The top three interventions for improving the Fugl-Meyer score were eye acupuncture [Meyer = 15.73 (95% CI: 3.4627.95)], other multi-needle acupuncture combinations [Meyer = 12.22 (95% CI: 5.1919.34)], and traditional western medicine + acupuncture + traditional Chinese medicine [Meyer = 11.96 (95% CI: -0.59 to 24.63)].

Conclusion

Multiple acupuncture methods are significantly effective in improving pain and upper limb motor function in post-stroke SHS, with relatively few adverse events; thus, acupuncture can be promoted.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, CRD42023410957.

Effect of different modalities of artificial intelligence rehabilitation techniques on patients with upper limb dysfunction after stroke-A network meta-analysis of randomized controlled trials

Background

This study aimed to observe the effects of six different types of AI rehabilitation techniques (RR, IR, RT, RT + VR, VR and BCI) on upper limb shoulder-elbow and wrist motor function, overall upper limb function (grip, grasp, pinch and gross motor) and daily living ability in subjects with stroke. Direct and indirect comparisons were drawn to conclude which AI rehabilitation techniques were most effective in improving the above functions.

Methods

From establishment to 5 September 2022, we systematically searched PubMed, EMBASE, the Cochrane Library, Web of Science, CNKI, VIP and Wanfang. Only randomized controlled trials (RCTs) that met the inclusion criteria were included. The risk of bias in studies was evaluated using the Cochrane Collaborative Risk of Bias Assessment Tool. A cumulative ranking analysis by SUCRA was performed to compare the effectiveness of different AI rehabilitation techniques for patients with stroke and upper limb dysfunction.

Results

We included 101 publications involving 4,702 subjects. According to the results of the SUCRA curves, RT + VR (SUCRA = 84.8%, 74.1%, 99.6%) was most effective in improving FMA-UE-Distal, FMA-UE-Proximal and ARAT function for subjects with upper limb dysfunction and stroke, respectively. IR (SUCRA = 70.5%) ranked highest in improving FMA-UE-Total with upper limb motor function amongst subjects with stroke. The BCI (SUCRA = 73.6%) also had the most significant advantage in improving their MBI daily living ability.

Conclusions

The network meta-analysis (NMA) results and SUCRA rankings suggest RT + VR appears to have a greater advantage compared with other interventions in improving upper limb motor function amongst subjects with stroke in FMA-UE-Proximal and FMA-UE-Distal and ARAT. Similarly, IR had shown the most significant advantage over other interventions in improving the FMA-UE-Total upper limb motor function score of subjects with stroke. The BCI also had the most significant advantage in improving their MBI daily living ability. Future studies should consider and report on key patient characteristics, such as stroke severity, degree of upper limb impairment, and treatment intensity/frequency and duration.

Systematic review registration

www.crd.york.ac.uk/prospero/#recordDetail, identifier: CRD42022337776.