Stationary wavelet transform and principal component analysis application on capacitive electrocardiography
作者： Eduardo Pinheiro , Octavian Postolache , Pedro Girão , None
DOI:
关键词: Data processing 、 Signal 、 Capacitive sensing 、 Engineering 、 Noise (signal processing) 、 Artificial intelligence 、 Principal component analysis 、 Process (computing) 、 Computer vision 、 Wavelet transform 、 Stationary wavelet transform
摘要: The gradual aging and the prevalence of cardiac pathologies in society has motivated an increase research homecare technologies. Capacitive sensing electrocardiogram (ECG) allows unobtrusively monitoring most well-known physiological signal. However, this measurement process is relentlessly superimposed with interferences noise, namely movement artifacts which nearly erase This work presents a system implementing new data processing technique, based on stationary wavelet transform together principal component analysis. approach successful, as it able to characterize motion artifacts, improve quality ECG acquired without subject's knowledge.
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