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Analysis of electrical and magnetic ...

Yao, Bing.

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Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue./
Author:	Yao, Bing.
Description:	218 p.
Notes:	Source: Dissertation Abstracts International, Volume: 67-01, Section: B, page: 0328.
Contained By:	Dissertation Abstracts International67-01B.
Subject:	Physics, Electricity and Magnetism. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3205322
ISBN:	0542510464

Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue.
Yao, Bing.

Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue. - 218 p.

Source: Dissertation Abstracts International, Volume: 67-01, Section: B, page: 0328.

Thesis (Ph.D.)--Case Western Reserve University, 2006.

This dissertation reports findings centered principally on comprehensive research related to human bio-signals (EEG, MEG, EMG and fMRI) acquired during repetitive maximal voluntary contractions (MVC) that induced severe fatigue. Fatigue is a common experience that reduces productivity and quality of life and increases chances of injury. Although abundant information has been gained in the last several decades regarding muscular and spinal-level mechanisms of muscle fatigue, very little is known about how cortical centers control and respond to fatigue. The main purpose of this study was to examine the fatigue effects on the central nervous system by analyzing the bio-signals collected in the designed experiments. Healthy human subjects were asked to perform a series of repetitive handgrip MVCs with their dominant hand until exhaustion. Handgrip forces, electrical activity (EMG) from primary and non-primary muscles, and EEG, MEG, or fMRI signals from different locations of the brain were recorded simultaneously. The time series data were segmented into several physiologically meaningful epochs (time phases), from rest to preparation to movement execution/sustaining. A series of studies, including motor-related cortical potential (MRCP) analysis, power spectrum analysis, time-frequency (spectrogram) analysis of EEG, EEG source localization and nonlinear analysis (fractal dimension and largest Lyapunov exponent), and fMRI analysis, was applied to the data. We hypothesized that the fatigue effects would act differently on brain signals of different phases. The MRCP results showed that the negative potential (NP) related to motor task preparation only had minimal changes with fatigue. The power of all EEG frequencies did not alter significantly during the preparation phase but decreased significantly during the sustained phase of the contraction. The fractal dimension and the largest Lyapunov exponent decreased significantly during the sustained phase as fatigue progressed. On the other hand, the fMRI results only exhibited insignificant fatigue-related reductions of brain activation volume and no significant change of dipole strength derived from multi-channel EEG data. These results have been interpreted by a hypothetical neurophysiological model, in which two groups of cortical neurons (phasic and tonic) are preferentially activated in each physiological phase of the voluntary motor action.

ISBN: 0542510464Subjects--Topical Terms:

1019535
Physics, Electricity and Magnetism.

Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue.
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245 1 0 $a Analysis of electrical and magnetic bio-signals associated with motor performance and fatigue.
300 $a 218 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-01, Section: B, page: 0328.
500 $a Advisers: Robert W. Brown; Guang H. Yue; Jing Z. Liu.
502 $a Thesis (Ph.D.)--Case Western Reserve University, 2006.
520 $a This dissertation reports findings centered principally on comprehensive research related to human bio-signals (EEG, MEG, EMG and fMRI) acquired during repetitive maximal voluntary contractions (MVC) that induced severe fatigue. Fatigue is a common experience that reduces productivity and quality of life and increases chances of injury. Although abundant information has been gained in the last several decades regarding muscular and spinal-level mechanisms of muscle fatigue, very little is known about how cortical centers control and respond to fatigue. The main purpose of this study was to examine the fatigue effects on the central nervous system by analyzing the bio-signals collected in the designed experiments. Healthy human subjects were asked to perform a series of repetitive handgrip MVCs with their dominant hand until exhaustion. Handgrip forces, electrical activity (EMG) from primary and non-primary muscles, and EEG, MEG, or fMRI signals from different locations of the brain were recorded simultaneously. The time series data were segmented into several physiologically meaningful epochs (time phases), from rest to preparation to movement execution/sustaining. A series of studies, including motor-related cortical potential (MRCP) analysis, power spectrum analysis, time-frequency (spectrogram) analysis of EEG, EEG source localization and nonlinear analysis (fractal dimension and largest Lyapunov exponent), and fMRI analysis, was applied to the data. We hypothesized that the fatigue effects would act differently on brain signals of different phases. The MRCP results showed that the negative potential (NP) related to motor task preparation only had minimal changes with fatigue. The power of all EEG frequencies did not alter significantly during the preparation phase but decreased significantly during the sustained phase of the contraction. The fractal dimension and the largest Lyapunov exponent decreased significantly during the sustained phase as fatigue progressed. On the other hand, the fMRI results only exhibited insignificant fatigue-related reductions of brain activation volume and no significant change of dipole strength derived from multi-channel EEG data. These results have been interpreted by a hypothetical neurophysiological model, in which two groups of cortical neurons (phasic and tonic) are preferentially activated in each physiological phase of the voluntary motor action.
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