Morphological processing of physiological signals for feature extraction.
The paper proposes a novel method of extracting features from physiological signals using intrinsic mode decomposition (IMD) and morphological signal processing (MSP). The complex, nonlinear and non-stationary biomedical signals are first decomposed into intrinsic mode functions (IMF). Next each IMF is subjected to MSP for extracting features, namely, pattern spectrum entropy, that characterize the shape-size complexity of the component signals. These along with other features like energy and sample entropy are extracted from the individual IMF as well as the cumulative sums of IMF for characterizing the signals. The procedure is illustrated using heart sound signals digitally recorded during cardiac auscultation representing different cardiac conditions.
Samanta
B
B
Department of Mechanical Engineering, Villanova University, Villanova, PA 10985, USA. biswanath.samanta@villanova.edu
D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006326:Heart Auscultation / Q000379:methods*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted