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The Effect Of Grip Strength And Mission Status In The FMRI Environment On Brain Activity

Posted on:2018-03-06Degree:MasterType:Thesis
Country:ChinaCandidate:X B ZhangFull Text:PDF
GTID:2358330518460453Subject:Control engineering
Abstract/Summary:PDF Full Text Request
Current studies brain-machine interface is mainly concentrated in more field technology for complex multimodal fusion research,a variety of movement rate to the size of the study of both the BCI,also have task state FMRI environment affect brain activity,while a lot of research work has been out of the laboratory,even for the industrialization development,however,a lot of work is not fine.This paper discusses the grip strength with speed and task state FMRI environment influence on brain activity,received good results,is eeg and FMRI fusion technology for the future form significance.The main content of the paper is as follows:mainly in the following several aspects of research,and obtained a certain result:(1)Based on brain-computer interface study grip strength and imagine the modulation mechanism of brain activity,with the right hand grip strength and imagine is speed three task status further confirmed with speed and imagination of brain electrical activity can be divided,and the size of the grip strength value will also affect brain electrical values.By CSP feature extraction,the SVM classification and brain network analysis method with the recognition speed movement and imagination is effective,especially the SVM classification maximum of the SVM classification,the highest can amount to 92%,grip strength and imagine important impact on the movement of the contralateral brain regions,will be important influence on brain electrical fine control.(2)Based on brain-computer interface study speed and imagine the modulation mechanism of brain activity,by both practical with speed and imagination with speed of three types of task status further confirmed with speed and imagination of brain electrical activity can be divided,and grasp the size of the speed value will also affect brain electrical values.By the way of CSP feature extraction,the SVM classification and brain network analysis method with the recognition speed movement and imagination is effective,especially the SVM classification of up to 93%,with speed and imagine important impact on the movement of the contralateral brain regions,the research ideas and methods are expected to do the follow-up related research(3)Comprehensive the basis of forefathers' research,summarizes the FMRI research on modulation of brain activity,has been clear about the FMRI can provide a more direct and more accurate measurement of rapid changes in brain activity,which would be helpful to the development of BCI,put forward more used to study the function of the brain regions activated distribution of nuclear magnetic resonance(NMR)environment and brain network connection to grip the ball.
Keywords/Search Tags:Dynamic brain network, ELM, FMRI, Fibre optical sensors
PDF Full Text Request
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