Tan Zou , Ning Liu , Wenfeng Wang , Qinbiao Li , Lingguo Bu
{"title":"应用fNIRS技术对被动训练对脑卒中康复效果的纵向评价","authors":"Tan Zou , Ning Liu , Wenfeng Wang , Qinbiao Li , Lingguo Bu","doi":"10.1016/j.ijhcs.2023.103202","DOIUrl":null,"url":null,"abstract":"<div><p>For patients with severe conditions such as stroke, passive exercise is commonly used in the early stages of their rehabilitation training. This study aimed to assess the effect of passive training on stroke rehabilitation and track brain function changes and the patient's rehabilitation progress, by employing a robot glove to perform a passive flexion-extension task. Specifically, functional near-infrared spectroscopy data from 26 patients under resting and right-hand passive interactions (task state) were recorded before and after a one-week interval, respectively, to explore the variations in the brain network of the patients. The results showed a stronger functional connectivity in both states of the two experiments in the left and right homotopic brain regions (p < 0.01). The effective connectivity network between brain regions maintained a consistent trend during the same test. Changes in functional connectivity and effective connectivity networks may represent the advantages of motor rehabilitation tasks and patient treatment duration, providing a perspective for an easy understanding of the mechanisms of stroke-related brain changes. This study demonstrates the feasibility of passive training strategies in the field of intelligent rehabilitation by applying neuroscientific diagnostic methods based on physiological data to the field of human-computer interaction.</p></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Longitudinal assessment of the effects of passive training on stroke rehabilitation using fNIRS technology\",\"authors\":\"Tan Zou , Ning Liu , Wenfeng Wang , Qinbiao Li , Lingguo Bu\",\"doi\":\"10.1016/j.ijhcs.2023.103202\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>For patients with severe conditions such as stroke, passive exercise is commonly used in the early stages of their rehabilitation training. This study aimed to assess the effect of passive training on stroke rehabilitation and track brain function changes and the patient's rehabilitation progress, by employing a robot glove to perform a passive flexion-extension task. Specifically, functional near-infrared spectroscopy data from 26 patients under resting and right-hand passive interactions (task state) were recorded before and after a one-week interval, respectively, to explore the variations in the brain network of the patients. The results showed a stronger functional connectivity in both states of the two experiments in the left and right homotopic brain regions (p < 0.01). The effective connectivity network between brain regions maintained a consistent trend during the same test. Changes in functional connectivity and effective connectivity networks may represent the advantages of motor rehabilitation tasks and patient treatment duration, providing a perspective for an easy understanding of the mechanisms of stroke-related brain changes. This study demonstrates the feasibility of passive training strategies in the field of intelligent rehabilitation by applying neuroscientific diagnostic methods based on physiological data to the field of human-computer interaction.</p></div>\",\"PeriodicalId\":54955,\"journal\":{\"name\":\"International Journal of Human-Computer Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2023-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Human-Computer Studies\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1071581923002112\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human-Computer Studies","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071581923002112","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Longitudinal assessment of the effects of passive training on stroke rehabilitation using fNIRS technology
For patients with severe conditions such as stroke, passive exercise is commonly used in the early stages of their rehabilitation training. This study aimed to assess the effect of passive training on stroke rehabilitation and track brain function changes and the patient's rehabilitation progress, by employing a robot glove to perform a passive flexion-extension task. Specifically, functional near-infrared spectroscopy data from 26 patients under resting and right-hand passive interactions (task state) were recorded before and after a one-week interval, respectively, to explore the variations in the brain network of the patients. The results showed a stronger functional connectivity in both states of the two experiments in the left and right homotopic brain regions (p < 0.01). The effective connectivity network between brain regions maintained a consistent trend during the same test. Changes in functional connectivity and effective connectivity networks may represent the advantages of motor rehabilitation tasks and patient treatment duration, providing a perspective for an easy understanding of the mechanisms of stroke-related brain changes. This study demonstrates the feasibility of passive training strategies in the field of intelligent rehabilitation by applying neuroscientific diagnostic methods based on physiological data to the field of human-computer interaction.
期刊介绍:
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
• Innovative interaction techniques
• Multimodal interaction
• Speech interaction
• Graphic interaction
• Natural language interaction
• Interaction in mobile and embedded systems
• Interface design and evaluation methodologies
• Design and evaluation of innovative interactive systems
• User interface prototyping and management systems
• Ubiquitous computing
• Wearable computers
• Pervasive computing
• Affective computing
• Empirical studies of user behaviour
• Empirical studies of programming and software engineering
• Computer supported cooperative work
• Computer mediated communication
• Virtual reality
• Mixed and augmented Reality
• Intelligent user interfaces
• Presence
...