Signal analysis in a new optical pulse waveform profiler for cardiovascular applications

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Pereira, T (Author) Other; Oliveira, T (Author) Other; Cabeleira, M (Author) Other; Matos, P (Author) Other; Pereira, HC (Author) Other; Almeida, V (Author) Other; Borges, E (Author) Other; Santos, H (Author) Other; Pereira, T (Author) Other; Cardoso, J (Author) Other; Correia, C (Author) Other

Conference proceedings International

Title: Proceedings of the IASTED International Conference on Signal and Image Processing and Applications, SIPA 2011

Pages: 19-25

IASTED International Conference on Signal and Image Processing and Applications, SIPA 2011

Crete, 22 June 2011 through 24 June 2011

Indexing

Scopus - 12 Citations

Other information

Authenticus ID: P-008-BKC

DOI: 10.2316/p.2011.738-067

Abstract (EN): Sub-millimetre distension waveforms (0.7 mm, max) are assessed using two new optical probes. The probes differ on the type of photo-detector used: planar photodiodes (PPD), in one case, and avalanche photodiodes (APD), in the other. Performance of the probes is evaluated in an especially developed test setup and in vivo, at the carotid site of humans. In the latter case, distension (associated to the pressure wave generated by the left ventricle contraction that propagates through the arterial system) carries clinically relevant information that can be extracted if, as will be shown, the waveforms are accurate and have enough resolution. An ultrasound image system, Vivid" e, was used as source of reference data for comparison. Along with the probes, a set of software routines was also developed to extract artefact-free data and evaluate the error. Results from the test setup demonstrate the possibility of waveform distension measurements with less than 6% error for both optical probes in this study. In comparison with an ultrasound system, the optical sensors allow the reproduction of the arterial waveform with a higher resolution, adequate to feed feature extraction algorithms.

Language: English

Type (Professor's evaluation): Scientific