现代仪器与医疗

基于EEG的非侵入式脑机接口常用手部不同运动任务的脑网络特征研究

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蒋泽武 ¹ , 林奕芳 ² , 胡一夏 ¹ , 李一伊 ³ , 陈树耿 ²^,^* , 贾杰 ²

现代仪器与医疗 | 专栏 2025,31(5): 16-29

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现代仪器与医疗 |专栏 2025 , 31 (5) : 16 -29

基于EEG的非侵入式脑机接口常用手部不同运动任务的脑网络特征研究

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蒋泽武¹, 林奕芳², 胡一夏¹, 李一伊³, 陈树耿²^,^*, 贾杰²

作者信息

^1.上海交通大学医学院附属仁济医院康复医学科，上海　200127

^2.复旦大学附属华山医院康复医学科，上海　200040

^3.同济大学医学院，上海　200090

通讯作者:

陈树耿，男，博士研究生，主管治疗师，研究方向：脑机接口与神经康复

作者简介:

蒋泽武，男，硕士研究生，住院医师，研究方向：脑机接口与神经康复

Study on brain network characteristics of common hand movement tasks in EEG-based non-invasive BCI

Zewu Jiang¹, Yifang Lin², Yixia Hu¹, Yiyi Li³, Shugeng Chen²^,^*, Jie Jia²

Affiliations

^1.Department of Rehabilitation Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China

^2.Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, Shanghai 200040, China

^3.School of Medicine, Tongji University, Shanghai 200090, China

出版时间: 2025-10-10 doi: 10.11876/mimt202505003

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摘要

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目的

基于脑电图技术比较受试者手部主动、想象和被动握拳任务下脑网络功能连接和拓扑属性，以探索脑机接口解析运动意图以辅助偏瘫康复的新方法。

方法

研究纳入15例健康成人受试者及19例脑卒中患者。受试者在主动运动、运动想象和被动运动3种任务模式下采集实时脑电图。通过功能连接分析方法比较脑卒中组与健康对照组的任务态脑网络功能连接的强度；采用图论比较组间的脑网络拓扑属性的改变。

结果

功能连接分析显示，脑卒中组与健康对照组在额叶、顶叶和枕叶的连接存在显著的相互作用。脑卒中患者的感觉运动网络对比健康受试者呈现出更高的连接强度。脑网络图论分析显示，脑卒中组的聚类系数显著低于健康对照组，特征路径长度普遍高于健康对照组，小世界系数显著低于健康对照组。

结论

脑卒中患者上肢功能恢复与脑网络功能连接的代偿性调节有关，具体包括强化患者运动感觉有关的感觉运动网络及高级运动皮层如额顶叶网络的连接强度。图论分析表明脑卒中后大脑表现出具有较低的聚类系数和较长的特征路径长度，验证脑卒中发生后脑网络的结构、功能被破坏，全局效率显著降低，信息传输效率下降，并在静息状态大脑网络中观察到向随机网络的转变。

关键词

脑机接口 / 脑卒中 / 脑电图 / 功能连接 / 任务相干性 / 脑网络拓扑

Abstract

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Objective

To compare the functional connections and topological properties of brain networks under subjects' active, imaginary and passive hand clenching tasks based on electroencephalography technology, in order to explore new methods for brain-computer interfaces to analyze movement intentions to assist in hemiplegia rehabilitation.

Methods

The study included 15 healthy adult subjects and 19 stroke patients. The subjects collected real-time EEG in three task modes: active movement, motor imagination and passive movement. Functional connection analysis was used to compare the strength of task-state brain network functional connections between stroke groups and healthy controls; graph theory was used to compare changes in brain network topological properties between groups.

Results

Functional connectivity analysis showed significant interactions between the stroke group and healthy controls in the frontal, parietal, and occipital lobes. The sensorimotor network of stroke patients showed higher connection strength than that of healthy subjects. Brain network graph theory analysis showed that the clustering coefficient of the stroke group was significantly lower than that of the healthy control group, the characteristic path length was generally higher than that of the healthy control group, and the small-world coefficient was significantly lower than that of the healthy control group.

Conclusion

The recovery of upper limb function in stroke patients is related to the compensatory adjustment of brain network functional connections, which specifically includes strengthening the connection strength of the sensorimotor network related to the patient's movement sensation and the high-level motor cortex such as the fronto-parietal network. Graph theory analysis shows that the brain after stroke has a lower clustering coefficient and a longer characteristic path length, verifying that the structure and function of the brain network are destroyed after stroke, the global efficiency is significantly reduced, the information transmission efficiency decreases, and a transformation to a random network is observed in the resting state brain network.

Key words

Brain computer interface / Stroke / Electroencephalography / Functional connectivity / Task-related coherence / Brain network topology

引用本文

蒋泽武, 林奕芳, 胡一夏, 李一伊, 陈树耿, 贾杰. 基于EEG的非侵入式脑机接口常用手部不同运动任务的脑网络特征研究. 现代仪器与医疗, 2025 , 31 (5) : 16 -29 . DOI: 10.11876/mimt202505003

Zewu Jiang, Yifang Lin, Yixia Hu, Yiyi Li, Shugeng Chen, Jie Jia. Study on brain network characteristics of common hand movement tasks in EEG-based non-invasive BCI[J]. Modern Instruments & Medical Treatment, 2025 , 31 (5) : 16 -29 . DOI: 10.11876/mimt202505003

基金

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国家自然科学基金资助项目(82202798)
上海扬帆专项(22YF1404200)
上海市养老科技专项(24YL1900202)

参考文献

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2025年第31卷第5期

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文章信息

doi: 10.11876/mimt202505003

首发时间：2026-10-23
出版时间：2025-10-10

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出版历史

基金

国家自然科学基金资助项目(82202798)

上海扬帆专项(22YF1404200)

上海市养老科技专项(24YL1900202)

作者信息

^1.上海交通大学医学院附属仁济医院康复医学科，上海　200127

^2.复旦大学附属华山医院康复医学科，上海　200040

^3.同济大学医学院，上海　200090

通讯作者:

陈树耿，男，博士研究生，主管治疗师，研究方向：脑机接口与神经康复

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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