Clinical practice of Brain–Machine interfaces in neurological disorders
Neurological disorders, such as Parkinson’s disease, stroke, and spinal cord injury, present significant global health challenges, contributing to high morbidity, mortality, and loss of functional independence for afflicted patients. Brain–machine interfaces (BMIs) have emerged as a transformative t...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-09-01
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| Series: | EngMedicine |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2950489925000363 |
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| author | Kaishan Wang Penghu Wei Yongzhi Shan Guoguang Zhao |
| author_facet | Kaishan Wang Penghu Wei Yongzhi Shan Guoguang Zhao |
| author_sort | Kaishan Wang |
| collection | DOAJ |
| description | Neurological disorders, such as Parkinson’s disease, stroke, and spinal cord injury, present significant global health challenges, contributing to high morbidity, mortality, and loss of functional independence for afflicted patients. Brain–machine interfaces (BMIs) have emerged as a transformative technology with promising potential for the diagnosis, treatment, and management of these conditions. By creating a direct communication interface between the brain and external devices, BMIs allow patients with severe neurological impairments to regain partial motor function, engage in nonverbal communication, and restore control over lost physiological functions. This review provides a comprehensive overview of recent clinical advancements in BMI applications for neurological disorders, including motor, consciousness, and affective disorders. This study highlights the utility of BMIs in improving motor and sensory functions, enabling communication between severely disabled patients, and delivering targeted therapeutic interventions. Current challenges such as the complexity of neural signal decoding, ethical considerations, and limited accessibility are critically examined. The review outlines prospective future directions, underscoring the importance of integrating artificial intelligence, machine learning, and multimodal signal processing to enhance the precision, adaptability, and clinical efficacy of brain-machine interface technology. |
| format | Article |
| id | doaj-art-431b0a0098b14fd79e2a4e38b4e32c93 |
| institution | DOAJ |
| issn | 2950-4899 |
| language | English |
| publishDate | 2025-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | EngMedicine |
| spelling | doaj-art-431b0a0098b14fd79e2a4e38b4e32c932025-08-20T03:09:05ZengElsevierEngMedicine2950-48992025-09-012310009010.1016/j.engmed.2025.100090Clinical practice of Brain–Machine interfaces in neurological disordersKaishan Wang0Penghu Wei1Yongzhi Shan2Guoguang Zhao3Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China; Clinical Research Center for Epilepsy Capital Medical University, Beijing, 100053, China; Beijing Municipal Geriatric Medical Research Center, Beijing, 100053, ChinaDepartment of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China; Clinical Research Center for Epilepsy Capital Medical University, Beijing, 100053, China; Beijing Municipal Geriatric Medical Research Center, Beijing, 100053, China; Corresponding author. Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China; Clinical Research Center for Epilepsy Capital Medical University, Beijing, 100053, China; Corresponding author. Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.Department of Neurosurgery, Xuanwu Hospital Capital Medical University, Beijing, 100053, China; Clinical Research Center for Epilepsy Capital Medical University, Beijing, 100053, China; Beijing Municipal Geriatric Medical Research Center, Beijing, 100053, China; Corresponding author. Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, No. 45 Changchun Street, Xicheng District, Beijing, 100053, China.Neurological disorders, such as Parkinson’s disease, stroke, and spinal cord injury, present significant global health challenges, contributing to high morbidity, mortality, and loss of functional independence for afflicted patients. Brain–machine interfaces (BMIs) have emerged as a transformative technology with promising potential for the diagnosis, treatment, and management of these conditions. By creating a direct communication interface between the brain and external devices, BMIs allow patients with severe neurological impairments to regain partial motor function, engage in nonverbal communication, and restore control over lost physiological functions. This review provides a comprehensive overview of recent clinical advancements in BMI applications for neurological disorders, including motor, consciousness, and affective disorders. This study highlights the utility of BMIs in improving motor and sensory functions, enabling communication between severely disabled patients, and delivering targeted therapeutic interventions. Current challenges such as the complexity of neural signal decoding, ethical considerations, and limited accessibility are critically examined. The review outlines prospective future directions, underscoring the importance of integrating artificial intelligence, machine learning, and multimodal signal processing to enhance the precision, adaptability, and clinical efficacy of brain-machine interface technology.http://www.sciencedirect.com/science/article/pii/S2950489925000363Brain-machine interfacesEpilepsyParkinson’s diseaseAlzheimer’s diseaseNeurological conditionsNeurosurgery |
| spellingShingle | Kaishan Wang Penghu Wei Yongzhi Shan Guoguang Zhao Clinical practice of Brain–Machine interfaces in neurological disorders EngMedicine Brain-machine interfaces Epilepsy Parkinson’s disease Alzheimer’s disease Neurological conditions Neurosurgery |
| title | Clinical practice of Brain–Machine interfaces in neurological disorders |
| title_full | Clinical practice of Brain–Machine interfaces in neurological disorders |
| title_fullStr | Clinical practice of Brain–Machine interfaces in neurological disorders |
| title_full_unstemmed | Clinical practice of Brain–Machine interfaces in neurological disorders |
| title_short | Clinical practice of Brain–Machine interfaces in neurological disorders |
| title_sort | clinical practice of brain machine interfaces in neurological disorders |
| topic | Brain-machine interfaces Epilepsy Parkinson’s disease Alzheimer’s disease Neurological conditions Neurosurgery |
| url | http://www.sciencedirect.com/science/article/pii/S2950489925000363 |
| work_keys_str_mv | AT kaishanwang clinicalpracticeofbrainmachineinterfacesinneurologicaldisorders AT penghuwei clinicalpracticeofbrainmachineinterfacesinneurologicaldisorders AT yongzhishan clinicalpracticeofbrainmachineinterfacesinneurologicaldisorders AT guoguangzhao clinicalpracticeofbrainmachineinterfacesinneurologicaldisorders |