本文選題：腦機接口系統(tǒng) + 腦卒中后遺癥康復　； 參考：《上海交通大學》2014年碩士論文

【摘要】：腦卒中癥是近年來人類的高發(fā)病癥，其后遺癥所導致的腦神經(jīng)損傷，會嚴重影響患者日常生活�；谶\動想象的功能性電刺激康復系統(tǒng)能將患者的運動想象與實際的肢體運動建立起神經(jīng)回路，是近年來腦機接口系統(tǒng)領域研究的一個重要課題。在實際應用中，我們發(fā)現(xiàn)腦卒中患者的運動想象信號與正常人的信號有著許多不同，因此我們在正常人的腦電信號基礎上，根據(jù)腦卒中患者的信號特點，試圖采用動態(tài)模式識別的方法來識別腦卒中患者的腦電信號。本文設計了一個BCI康復系統(tǒng)，，并通過臨床試驗采集BCI康復數(shù)據(jù)。我們比較了腦卒中患者與正常成年人的運動想象信號，找出其異同點，并針對患者腦電特點，提取出符合其特點的動態(tài)特征。我們將這些動態(tài)特征應用于幾種流行的動態(tài)模式識別方法，通過比較找出適合患者腦電信號的模式，驗證患者腦電特點,并對這些動態(tài)識別方法進行比較。
[Abstract]:Stroke is a high incidence of human disease in recent years, its sequelae caused by the brain nerve damage, will seriously affect the daily life of patients. The functional electrical stimulation rehabilitation system based on motor imagination can establish neural circuits between patients' movement imagination and actual limb movement, which is an important subject in the field of brain-computer interface system in recent years. In practical application, we found that there are many differences between the signal of motion imagination of stroke patients and that of normal people, so we based on the EEG signals of normal people, according to the characteristics of the signals of stroke patients. This paper attempts to identify the EEG of stroke patients by dynamic pattern recognition. A BCI rehabilitation system is designed, and BCI rehabilitation data are collected through clinical trials. We compared the motor imagination signals between stroke patients and normal adults, found out the similarities and differences, and extracted the dynamic features according to the characteristics of EEG. We apply these dynamic features to several popular dynamic pattern recognition methods. By comparing and finding out suitable patterns for patients' EEG signals, we verify the characteristics of patients' EEG, and compare these dynamic recognition methods.
【學位授予單位】：上海交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN911.7;R743.3

【參考文獻】

相關期刊論文 前1條

1 張茂田,陳芷若,陶慶玲;腦梗死患者的腦電圖變化與有關因素——陽性診斷標準研究[J];臨床腦電學雜志;1999年01期

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