Integrative neurorehabilitation using brain-computer interface: From motor function to mental health after stroke DOI Open Access
Yanan Ma,

Kenji Karako,

Peipei Song

и другие.

BioScience Trends, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Stroke remains a leading cause of mortality and long-term disability worldwide, frequently resulting in impairments motor control, cognition, emotional regulation. Conventional rehabilitation approaches, while partially effective, often lack individualization yield suboptimal outcomes. In recent years, brain-computer interface (BCI) technology has emerged as promising neurorehabilitation tool by decoding neural signals providing real-time feedback to enhance neuroplasticity. This review systematically explores the use BCI systems post-stroke rehabilitation, focusing on three core domains: function, cognitive capacity, outlines neurophysiological principles underpinning BCI-based including neurofeedback training, Hebbian plasticity, multimodal strategies. It then examines advances upper limb gait recovery using integrated with functional electrical stimulation (FES), robotics, virtual reality (VR). Moreover, it highlights BCI's potential language through EEG-based integration artificial intelligence (AI) immersive VR environments. addition, discusses role monitoring regulating disorders via closed-loop systems. While promising, technologies face challenges related signal accuracy, device portability, clinical validation. Future research should prioritize integration, AI-driven personalization, large-scale randomized trials establish efficacy. underscores transformative delivering intelligent, personalized, cross-domain solutions for stroke survivors.

Язык: Английский

Integrative neurorehabilitation using brain-computer interface: From motor function to mental health after stroke DOI Open Access
Yanan Ma,

Kenji Karako,

Peipei Song

и другие.

BioScience Trends, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Stroke remains a leading cause of mortality and long-term disability worldwide, frequently resulting in impairments motor control, cognition, emotional regulation. Conventional rehabilitation approaches, while partially effective, often lack individualization yield suboptimal outcomes. In recent years, brain-computer interface (BCI) technology has emerged as promising neurorehabilitation tool by decoding neural signals providing real-time feedback to enhance neuroplasticity. This review systematically explores the use BCI systems post-stroke rehabilitation, focusing on three core domains: function, cognitive capacity, outlines neurophysiological principles underpinning BCI-based including neurofeedback training, Hebbian plasticity, multimodal strategies. It then examines advances upper limb gait recovery using integrated with functional electrical stimulation (FES), robotics, virtual reality (VR). Moreover, it highlights BCI's potential language through EEG-based integration artificial intelligence (AI) immersive VR environments. addition, discusses role monitoring regulating disorders via closed-loop systems. While promising, technologies face challenges related signal accuracy, device portability, clinical validation. Future research should prioritize integration, AI-driven personalization, large-scale randomized trials establish efficacy. underscores transformative delivering intelligent, personalized, cross-domain solutions for stroke survivors.

Язык: Английский

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