{"title":"机器人辅助下肢康复中的脑功能检测技术现状。","authors":"Duojin Wang, Yihe Wu, Hongliu Yu","doi":"10.1089/brain.2024.0005","DOIUrl":null,"url":null,"abstract":"<p><p><b><i>Background:</i></b> With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). <b><i>Objective:</i></b> This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity. <b><i>Methods:</i></b> Sixty-five articles in the field of RALLR were selected and tested using three brain function detection technologies. <b><i>Results:</i></b> Most studies have focused on changes in activity in various regions of the cerebral cortex during different lower limb rehabilitation tasks but have also increasingly focused on functional changes in other cortical and deep subcortical structures. Our analysis also revealed a neglect of certain task types. <b><i>Conclusion:</i></b> We identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different RALLR tasks. Impact Statement The evaluation of robot-assisted lower limb rehabilitation based on brain function detection technology can assess the neurological changes of patients in the rehabilitation process by monitoring brain activities and can also provide more accurate guidance for robot-assisted lower limb rehabilitation. By monitoring the patient's brain activity, the robot can adjust according to the real-time status of the patient to achieve more effective rehabilitation training. This has potential impact on improving the rehabilitation effect and speeding up the rehabilitation process of patients.</p>","PeriodicalId":9155,"journal":{"name":"Brain connectivity","volume":" ","pages":"401-417"},"PeriodicalIF":2.4000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.\",\"authors\":\"Duojin Wang, Yihe Wu, Hongliu Yu\",\"doi\":\"10.1089/brain.2024.0005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b><i>Background:</i></b> With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). <b><i>Objective:</i></b> This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity. <b><i>Methods:</i></b> Sixty-five articles in the field of RALLR were selected and tested using three brain function detection technologies. <b><i>Results:</i></b> Most studies have focused on changes in activity in various regions of the cerebral cortex during different lower limb rehabilitation tasks but have also increasingly focused on functional changes in other cortical and deep subcortical structures. Our analysis also revealed a neglect of certain task types. <b><i>Conclusion:</i></b> We identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different RALLR tasks. Impact Statement The evaluation of robot-assisted lower limb rehabilitation based on brain function detection technology can assess the neurological changes of patients in the rehabilitation process by monitoring brain activities and can also provide more accurate guidance for robot-assisted lower limb rehabilitation. By monitoring the patient's brain activity, the robot can adjust according to the real-time status of the patient to achieve more effective rehabilitation training. This has potential impact on improving the rehabilitation effect and speeding up the rehabilitation process of patients.</p>\",\"PeriodicalId\":9155,\"journal\":{\"name\":\"Brain connectivity\",\"volume\":\" \",\"pages\":\"401-417\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brain connectivity\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1089/brain.2024.0005\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/1 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"NEUROSCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain connectivity","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/brain.2024.0005","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/1 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
State of the Art of Brain Function Detection Technologies in Robot-Assisted Lower Limb Rehabilitation.
Background: With an aging population, the prevalence of neurological disorders is increasing, leading to a rise in lower limb movement disorders and, in turn, a growing need for rehabilitation training. Previous neuroimaging studies have shown a growing scientific interest in the study of brain mechanisms in robot-assisted lower limb rehabilitation (RALLR). Objective: This review aimed to determine differences in neural activity patterns during different RALLR tasks and the impact on neurofunctional plasticity. Methods: Sixty-five articles in the field of RALLR were selected and tested using three brain function detection technologies. Results: Most studies have focused on changes in activity in various regions of the cerebral cortex during different lower limb rehabilitation tasks but have also increasingly focused on functional changes in other cortical and deep subcortical structures. Our analysis also revealed a neglect of certain task types. Conclusion: We identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different RALLR tasks. Impact Statement The evaluation of robot-assisted lower limb rehabilitation based on brain function detection technology can assess the neurological changes of patients in the rehabilitation process by monitoring brain activities and can also provide more accurate guidance for robot-assisted lower limb rehabilitation. By monitoring the patient's brain activity, the robot can adjust according to the real-time status of the patient to achieve more effective rehabilitation training. This has potential impact on improving the rehabilitation effect and speeding up the rehabilitation process of patients.
期刊介绍:
Brain Connectivity provides groundbreaking findings in the rapidly advancing field of connectivity research at the systems and network levels. The Journal disseminates information on brain mapping, modeling, novel research techniques, new imaging modalities, preclinical animal studies, and the translation of research discoveries from the laboratory to the clinic.
This essential journal fosters the application of basic biological discoveries and contributes to the development of novel diagnostic and therapeutic interventions to recognize and treat a broad range of neurodegenerative and psychiatric disorders such as: Alzheimer’s disease, attention-deficit hyperactivity disorder, posttraumatic stress disorder, epilepsy, traumatic brain injury, stroke, dementia, and depression.