Analysis and characterization of photo-plethysmographic signal

• Published in: IEEE transactions on biomedical engineering Vol. 48; no. 1; pp. 5 - 11
• Main Authors: Bhattacharya, J., Kanjilal, P.P., Muralidhar, V.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2001; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Aged; Algorithms; Biological and medical sciences; Blood pressure; Cardiology; Cardiovascular system; Covariance matrix; Data mining; Feature extraction; Fluctuations; Follow-Up Studies; Fourier Analysis; Heart rate variability; Hemodynamics; Herniorrhaphy; Humans; Information analysis; Investigative techniques, diagnostic techniques (general aspects); Ischemic Attack, Transient - diagnosis; Male; Medical imaging; Medical sciences; Middle Aged; Models, Cardiovascular; Noninvasive medical procedures; Nonlinear Dynamics; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Periodicity; Physiology; Plethysmography; Pulsatile flow; Pulse measurements; Reference Values; Signal analysis; Signal Processing, Computer-Assisted; Thoracotomy; Volume measurement; Human; Periodicity; Myocardium; Photoplethysmography; Blood pressure; Circulatory system; Hemodynamics; Dynamical system; Non linear system; Signal analysis; Singular value decomposition
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/10.900243

Qualitative assessment of the overall clinical status of the subject and characterization of complex cardiovascular dynamics from digital blood volume pulsations measured noninvasively using a photo-plethysmographic device is addressed. A novel concept is employed to detect the dominant nonsinusoidal periodicity embedded in the data series and to extract the associated periodic component. The detection and the extraction of periodic component is performed with moving window to accommodate the variations of the physiological oscillations. The covariance matrix formed by the gradually varying pattern is used as a simple measure of qualitative assessment. Further, the characterization of the underlying system in the light of nonlinear dynamical analysis is also presented. The stable subjects are shown to behave as a low-dimensional system whereas the diseased subjects exhibit comparatively high dimensional activity.