International Journal of Advances in Bio-Informatics and Bio-Technology
Author(s) : CHOI U-HOU, DONG MINGCHUI, FU BINBIN, GUO RAN, MA JIALI
Radial pulse waveform contains massive cardiovascular pathophysiological messages from the hemodynamic perspective, which makes it promising in intelligent monitoring of cardiovascular health status. However, the instability of signal sampling leads a series of morphologic distortion causing mistakes in further intelligent analysis. Towards wearable monitoring device to realize intelligent analysis of Sphygmogram (SPG) acquired from radial artery, a morphologic distortion percolator is purposed to obtain qualified SPG. The presented percolator takes advantage of waveform segmentation and similarity analysis through novel reverse order correlation method. 179 stored records of 83 subjects, including 13 normal people and 70 patients, which are collected from our research group and collaborative hospital, were used for evaluation. For the filtration result, the worst error rate and sensitivity of percolator were 11.53% and 96.15%, respectively.