Effectiveness and safety of brain-computer interface technology in the treatment of poststroke motor disorders: a protocol for systematic review and meta-analysis

Quantitative assessment of thenar to evaluate hand function after stroke by Bayes discriminant

BACKGROUND

The incidence rate of stroke or cerebrovascular accidents ranks first in China. More than 85% of stroke patients have residual upper limb motor dysfunction, especially hand dysfunction. Normalizing the rehabilitation evaluation process and standard quantitative evaluation method is a complex and key point in rehabilitation therapy. The study aimed to establish a function model based on the Bayes discriminant by measuring the thenar stiffness with shear wave elastography (SWE) to quantitatively evaluate the hand motor function of hemiplegic patients after stroke.

METHODS

This study collected 60 patients diagnosed with hemiplegia after stroke from October 2021 to October 2022. Therapists used the Brunnstrom assessment (BA)scale to divide the patients into the stage. All the patients underwent the measurement of SWE examination of abductor pollicis brevis (APB), opponens pollicis (OP), flexor pollicis long tendon (FPLT), and flexor pollicis brevis (FPB) by two sonographers. The SWE change rate of four parts of the thenar area was calculated prospectively with the non-hemiplegic side as the reference, the function equation was established by the Bayes discriminant method, and the evaluation model was fitted according to the acquired training set data. Lastly, the model was verified by self-validation, cross-validation, and external data validation methods. The classification performance was evaluated regarding the area under the ROC curve (AUC), sensitivity, and specificity.

RESULTS

The median SWE values of the hemiplegic side of patients were lower than those of the non-hemiplegic side. According to the BA stage and SWER of APB, OP, FPLT, and FPB, our study established the Bayes discriminative model and validated it via self-validation and cross-validation methods. Then, the discriminant equation was used to validate 18 patients prospectively, the diagnostic coincidence rate was about 78.8%, and the misjudgment rate was approximately 21.2%. The AUC of the discriminant model for diagnosing BA stage I-VI was 0.928(95% CI: 0.839-1.0),0.858(95% CI: 0.748-0.969),1.0(95% CI: 1.0-1.0), 0.777(95% CI: 0.599-0.954),0.785(95% CI: 0.593-0.977) and 0.985(95% CI: 0.959-1.0), respectively.

CONCLUSION

This Bayes discriminant model built by measuring thenar stiffness was of diagnostic value and can provide an objective basis for evaluating clinical rehabilitation.

Identifying Thematics in a Brain-Computer Interface Research

This umbrella review is motivated to understand the shift in research themes on brain-computer interfacing (BCI) and it determined that a shift away from themes that focus on medical advancement and system development to applications that included education, marketing, gaming, safety, and security has occurred. The background of this review examined aspects of BCI categorisation, neuroimaging methods, brain control signal classification, applications, and ethics. The specific area of BCI software and hardware development was not examined. A search using One Search was undertaken and 92 BCI reviews were selected for inclusion. Publication demographics indicate the average number of authors on review papers considered was 4.2 ± 1.8. The results also indicate a rapid increase in the number of BCI reviews from 2003, with only three reviews before that period, two in 1972, and one in 1996. While BCI authors were predominantly Euro-American in early reviews, this shifted to a more global authorship, which China dominated by 2020-2022. The review revealed six disciplines associated with BCI systems: life sciences and biomedicine (n = 42), neurosciences and neurology (n = 35), and rehabilitation (n = 20); (2) the second domain centred on the theme of functionality: computer science (n = 20), engineering (n = 28) and technology (n = 38). There was a thematic shift from understanding brain function and modes of interfacing BCI systems to more applied research novel areas of research-identified surround artificial intelligence, including machine learning, pre-processing, and deep learning. As BCI systems become more invasive in the lives of "normal" individuals, it is expected that there will be a refocus and thematic shift towards increased research into ethical issues and the need for legal oversight in BCI application.

Effectiveness of Tai Chi Yunshou motor imagery training for hemiplegic upper extremity motor function in poststroke patients: study protocol for a randomized clinical trial

Background

Evidence concerning the effect of Tai Chi Yunshou motor imagery training (TCY-MIT) on upper extremity motor function (UE-MF) recovery in poststroke patients is lacking, and few studies have examined the neural mechanisms of MIT. The study was designed to assess the effectiveness of TCY-MIT and its possible neural mechanisms.

Methods/design

The study is an assessor-blinded, parallel, superiority, randomized clinical trial. A total of 78 eligible participants will be randomly assigned to 2 groups in a 1:1 ratio. Participants in the control group will receive (conventional rehabilitation therapies) CRTs for 40 min per day, 6 days per week, for 3 weeks. Participants in the intervention group will receive CRTs combined with TCY-MIT (30 min per day, 6 days per week, for 3 weeks). The primary outcome measure is the Fugl-Meyer Assessment of Upper Extremity. Secondary outcome measures are the Box and Block Test, muscle strength test, modified Barthel index, and Pearson correlation coefficients. All outcomes will be assessed at baseline, after completion of the intervention (1, 2, and 3 weeks), and at the end of follow-up (2 months). The outcome assessor will be blinded to the group allocation of the participants.

Discussion

We expect this assessor-blinded, parallel, superiority, randomized clinical trial to explore the effectiveness of TCY-MIT combined with CRTs compared with CRTs alone for UE-MF in poststroke patients.

Trial registration

Chinese Clinical Trial Registry ID: ChiCTR2100048868. Registered on 19 July 2021

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06283-z.