文件名称:filterECG
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this file proposes the use of independent
component analysis (ICA) for removing ECG contamination EMG and compared it with other procedures previously developed to decontaminate EMG. To mimic realistic contamination while having uncontaminated reference signals, we employed EMG recordings peripheral muscles with different
activation patterns and superimposed distinct ECG signals that were recorded during rest at conventional locations for trunk muscle EMG. ICA decomposition was performed with and without a separately collected ECG signal as part of the data set and contaminated ICA modes representing ECG were identified automatically.-this file proposes the use of independent
component analysis (ICA) for removing ECG contamination EMG and compared it with other procedures previously developed to decontaminate EMG. To mimic realistic contamination while having uncontaminated reference signals, we employed EMG recordings peripheral muscles with different
activation patterns and superimposed distinct ECG signals that were recorded during rest at conventional locations for trunk muscle EMG. ICA decomposition was performed with and without a separately collected ECG signal as part of the data set and contaminated ICA modes representing ECG were identified automatically.
component analysis (ICA) for removing ECG contamination EMG and compared it with other procedures previously developed to decontaminate EMG. To mimic realistic contamination while having uncontaminated reference signals, we employed EMG recordings peripheral muscles with different
activation patterns and superimposed distinct ECG signals that were recorded during rest at conventional locations for trunk muscle EMG. ICA decomposition was performed with and without a separately collected ECG signal as part of the data set and contaminated ICA modes representing ECG were identified automatically.-this file proposes the use of independent
component analysis (ICA) for removing ECG contamination EMG and compared it with other procedures previously developed to decontaminate EMG. To mimic realistic contamination while having uncontaminated reference signals, we employed EMG recordings peripheral muscles with different
activation patterns and superimposed distinct ECG signals that were recorded during rest at conventional locations for trunk muscle EMG. ICA decomposition was performed with and without a separately collected ECG signal as part of the data set and contaminated ICA modes representing ECG were identified automatically.
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下载文件列表
DemoData.mat
__MACOSX/
__MACOSX/._DemoData.mat
filterECG.m
__MACOSX/._filterECG.m
testECGfilter.m
__MACOSX/
__MACOSX/._DemoData.mat
filterECG.m
__MACOSX/._filterECG.m
testECGfilter.m
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