The clinical effects of brain–computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review

Qu, Hao; Zeng, Feixiang; Tang, Yongbin; Shi, Bin; Wang, Zhijun; Chen, Xiaokai; Wang, Jing

doi:10.1080/17483107.2022.2060354

Cited by 9 publications

(5 citation statements)

References 68 publications

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“…Traditional rehabilitation methods have shown limited success in restoring function fully. Syrebo's glove rehabilitation program offers a promising alternative approach [11][12][13][14]. This case study aims to evaluate the effectiveness of this program in MCAI patients, focusing on motor recovery and functional improvement.…”

Section: Discussionmentioning

confidence: 99%

Effectiveness of Syrebo’s Glove Rehabilitation Program in a Patient With Middle Cerebral Artery Infarct: A Case Report

Sharma,

Sharath,

Sasun

2024

Cureus

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In India, stroke is a significant health concern, with an estimated prevalence of around 1.54% in adults over 20 years old. The incidence of stroke in India varies regionally but is generally high due to factors like hypertension and lifestyle changes. Ischemic strokes comprise the majority, particularly in the middle cerebral artery (MCA) territory. MCA stroke presents with diverse symptoms such as weakness, speech difficulties, and vision problems, emphasizing the need for comprehensive rehabilitation. Physiotherapy plays a vital role in addressing these challenges, focusing on strength, coordination, mobility, and independence through tailored interventions. Additionally, soft robotic gloves, such as Syrebo's rehabilitation, offer promising advancements in neurorehabilitation by enhancing motor recovery and functional abilities, particularly in improving grip strength and hand functionality, thus improving outcomes for stroke patients. This case describes a 66-year-old female presenting with sudden left-sided weakness, slurred speech, and facial deviation indicative of bilateral MCA territory infarct. After admission requiring ventilation and medication, imaging confirmed the diagnosis. Following stabilization, she underwent neurophysiotherapy for rehabilitation. Neurological examination revealed deficits in muscle tone, reflexes, cranial nerve function, language, and swallowing. Outcome measures indicated progress in rehabilitation. The case underscores the significance of timely diagnosis and personalized rehabilitation in optimizing outcomes for MCA territory stroke patients.

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Section: Discussionmentioning

confidence: 99%

Effectiveness of Syrebo’s Glove Rehabilitation Program in a Patient With Middle Cerebral Artery Infarct: A Case Report

Sharma,

Sharath,

Sasun

2024

Cureus

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“…However, new evaluation criteria need to be established, with more objective biomechanical assessments to establish BCI's safe application. 102 BCI's could also to enhance metacognitive monitoring. A BCI-VR was able to evaluate the emotional responses of designers to their work, providing real-time, visual biofeedback of the responses.…”

Section: Outdoor Physical Activity Assistancementioning

confidence: 99%

Review—Smart Wearable Sensors for Health and Lifestyle Monitoring: Commercial and Emerging Solutions

Cusack,

Venkatraman,

Raza

et al. 2024

ECS Sens. Plus

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The rapid growth of urbanisation has brought about various health concerns for citizens living in urban environments. Sedentary lifestyles, increased pollution levels, and high levels of stress have become prevalent issues affecting the overall well-being of urban populations. In recent years, the emergence of smart wearable devices has offered a promising avenue to address these health concerns and promote healthier lifestyles. This review evaluatse the effectiveness of smart wearables in mitigating health concerns and improving the lifestyles of urban citizens. The review involves 50 relevant peer-reviewed smart wearable studies and supporting literature from electronic databases PubMed, Ovid, Web of Science, and Scopus. Results indicate that smart wearables have the potential to positively impact the health of urban citizens by promoting physical activity, tracking vital signs, monitoring sleep patterns, and providing personalised feedback and recommendations to promote physical activity levels. Furthermore, these devices can help individuals manage stress levels, enhance self-awareness, and foster healthier behaviours. However, the review also identifies several challenges, including the accuracy and reliability of wearable data, user engagement and adherence, and ethical considerations regarding data privacy and security.

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“…Thereby, BCI-NFT aims to fortify sensorimotor pathways, potentially fostering motor learning and neuroplasticity ( Behboodi et al, 2022 ). BCI-NFT has been used effectively for motor rehabilitation in those with neurological disorders, especially individuals with stroke, as demonstrated in multiple systematic reviews ( Monge-Pereira et al, 2017 ; Cervera et al, 2018 ; Bai et al, 2020 ; Kruse et al, 2020 ; Penev et al, 2023 ; Qu et al, 2024 ).…”

Section: Introductionmentioning

confidence: 99%

Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy

Behboodi,

Kline,

Gravunder

et al. 2024

Front. Hum. Neurosci.

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In the realm of motor rehabilitation, Brain-Computer Interface Neurofeedback Training (BCI-NFT) emerges as a promising strategy. This aims to utilize an individual’s brain activity to stimulate or assist movement, thereby strengthening sensorimotor pathways and promoting motor recovery. Employing various methodologies, BCI-NFT has been shown to be effective for enhancing motor function primarily of the upper limb in stroke, with very few studies reported in cerebral palsy (CP). Our main objective was to develop an electroencephalography (EEG)-based BCI-NFT system, employing an associative learning paradigm, to improve selective control of ankle dorsiflexion in CP and potentially other neurological populations. First, in a cohort of eight healthy volunteers, we successfully implemented a BCI-NFT system based on detection of slow movement-related cortical potentials (MRCP) from EEG generated by attempted dorsiflexion to simultaneously activate Neuromuscular Electrical Stimulation which assisted movement and served to enhance sensory feedback to the sensorimotor cortex. Participants also viewed a computer display that provided real-time visual feedback of ankle range of motion with an individualized target region displayed to encourage maximal effort. After evaluating several potential strategies, we employed a Long short-term memory (LSTM) neural network, a deep learning algorithm, to detect the motor intent prior to movement onset. We then evaluated the system in a 10-session ankle dorsiflexion training protocol on a child with CP. By employing transfer learning across sessions, we could significantly reduce the number of calibration trials from 50 to 20 without compromising detection accuracy, which was 80.8% on average. The participant was able to complete the required calibration trials and the 100 training trials per session for all 10 sessions and post-training demonstrated increased ankle dorsiflexion velocity, walking speed and step length. Based on exceptional system performance, feasibility and preliminary effectiveness in a child with CP, we are now pursuing a clinical trial in a larger cohort of children with CP.

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The clinical effects of brain–computer interface with robot on upper-limb function for post-stroke rehabilitation: a meta-analysis and systematic review

Cited by 9 publications

References 68 publications

Effectiveness of Syrebo’s Glove Rehabilitation Program in a Patient With Middle Cerebral Artery Infarct: A Case Report

Effectiveness of Syrebo’s Glove Rehabilitation Program in a Patient With Middle Cerebral Artery Infarct: A Case Report

Review—Smart Wearable Sensors for Health and Lifestyle Monitoring: Commercial and Emerging Solutions

Development and evaluation of a BCI-neurofeedback system with real-time EEG detection and electrical stimulation assistance during motor attempt for neurorehabilitation of children with cerebral palsy

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