Physiological Feature Extraction Sample Clauses

Physiological Feature Extraction. The physiological feature extraction methods can be di- vided into time-domain and frequency-domain methods, and they are not totally the same for different cardiovas- cular physiological signals. We demonstrate ECG, PPG and PCG feature extraction in this subsection. For the ECG signal, the physiological features can be extracted from the time domain after filtering the lower frequency by fast Fourier transform. Fiducial points include R peaks, S peaks, Q peaks, P peaks, T peaks, LP valleys, TP valleys, and QRS complex can be detected from ECG signals [49]. We can compute IPIs between these fiducial points and take them as physiological features. In addition, the amplitudes of R peaks, T peaks, P peaks can also be computed as physiological features. Photoplethysmography (PPG) is to measure the volume of tissue blood. The widely used physiological features are based on local marks of heart beats from the time domain, which include systolic peak, dicrotic notch, di- astolic peak, pulse interval, peak to peak, augmentation index, alternative augmentation index and a series of peak time. For the PCG signal, the physiological features can be extracted through frequency domain from the S1 tone (it has an average duration of 100ms-200ms and its spectrum is concentrated within 25Hz-45Hz) and S2 tone (it lasts for about 0.12s with a frequency less than 150Hz). First, the power spectral density of the signals is estimated with the Short Time Fourier Transform (STFT). Then, the magnitude of the spectral coefficients is passed through the Xxx-frequency filter and subjected to Linear Discriminant Analysis (LDA) in order to reduce dimensionality.
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