{"title":"神经系统疾病异常运动模式的智能评估技术:应用与进展。","authors":"Yunjun Bao, Ronghua Hong, Wenting Qin, Zhuang Wu, Yunping Song, Lingjing Jin","doi":"10.1155/bn/6006064","DOIUrl":null,"url":null,"abstract":"<p><p>Neurological disorders frequently result in diverse forms of abnormal movement. Conventional clinical assessment approaches often lack the precision and objectivity needed to evaluate muscle involvement and associated functional limitations. With the development of various intelligent assessment devices, technologies such as wearable sensors, motion capture, radar, and imaging technology, which are based on myoelectricity, kinematics, mechanics, and optics, combined with mathematical models and algorithms, have been widely used for abnormal movement recognition. These technologies further improve the accuracy and validity of clinical evaluation. In this paper, we review the latest advances in intelligent technologies that help clinicians qualitatively and quantitatively assess abnormal movement patterns and carry out personalized rehabilitation treatment. Our work was also aimed at summarizing the research and application of intelligent assessment techniques.</p>","PeriodicalId":50733,"journal":{"name":"Behavioural Neurology","volume":"2025 ","pages":"6006064"},"PeriodicalIF":2.3000,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12515573/pdf/","citationCount":"0","resultStr":"{\"title\":\"Intelligent Assessment Techniques for Abnormal Movement Patterns in Neurological Disorders: Applications and Advances.\",\"authors\":\"Yunjun Bao, Ronghua Hong, Wenting Qin, Zhuang Wu, Yunping Song, Lingjing Jin\",\"doi\":\"10.1155/bn/6006064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Neurological disorders frequently result in diverse forms of abnormal movement. Conventional clinical assessment approaches often lack the precision and objectivity needed to evaluate muscle involvement and associated functional limitations. With the development of various intelligent assessment devices, technologies such as wearable sensors, motion capture, radar, and imaging technology, which are based on myoelectricity, kinematics, mechanics, and optics, combined with mathematical models and algorithms, have been widely used for abnormal movement recognition. These technologies further improve the accuracy and validity of clinical evaluation. In this paper, we review the latest advances in intelligent technologies that help clinicians qualitatively and quantitatively assess abnormal movement patterns and carry out personalized rehabilitation treatment. Our work was also aimed at summarizing the research and application of intelligent assessment techniques.</p>\",\"PeriodicalId\":50733,\"journal\":{\"name\":\"Behavioural Neurology\",\"volume\":\"2025 \",\"pages\":\"6006064\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12515573/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Behavioural Neurology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1155/bn/6006064\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Behavioural Neurology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1155/bn/6006064","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Intelligent Assessment Techniques for Abnormal Movement Patterns in Neurological Disorders: Applications and Advances.
Neurological disorders frequently result in diverse forms of abnormal movement. Conventional clinical assessment approaches often lack the precision and objectivity needed to evaluate muscle involvement and associated functional limitations. With the development of various intelligent assessment devices, technologies such as wearable sensors, motion capture, radar, and imaging technology, which are based on myoelectricity, kinematics, mechanics, and optics, combined with mathematical models and algorithms, have been widely used for abnormal movement recognition. These technologies further improve the accuracy and validity of clinical evaluation. In this paper, we review the latest advances in intelligent technologies that help clinicians qualitatively and quantitatively assess abnormal movement patterns and carry out personalized rehabilitation treatment. Our work was also aimed at summarizing the research and application of intelligent assessment techniques.
期刊介绍:
Behavioural Neurology is a peer-reviewed, Open Access journal which publishes original research articles, review articles and clinical studies based on various diseases and syndromes in behavioural neurology. The aim of the journal is to provide a platform for researchers and clinicians working in various fields of neurology including cognitive neuroscience, neuropsychology and neuropsychiatry.
Topics of interest include:
ADHD
Aphasia
Autism
Alzheimer’s Disease
Behavioural Disorders
Dementia
Epilepsy
Multiple Sclerosis
Parkinson’s Disease
Psychosis
Stroke
Traumatic brain injury.