title: Self-organizing arterial pressure pulse classification using neural networks: theoretical considerations and clinical applicability.
abstract: A self-organizing classification system for the arterial pressure pulse based on the ART2 (adaptive resonance theory) network was developed. The system consists of a preprocessor and an ART2 recognition network. The preprocessor removes the arterial pressure pulse servo component signals from Finapres, detects the systolic pressure points and divides the acquired signals into minimal cardiac cycles. The ART2 network input is the minimal cardiac cycle detected by the preprocessor. The classification results can be used to assist physicians in evaluating the signs of abnormal and normal autonomic control and has shown its clinical applicability for the examination of the autonomic nervous system.
authors.affiliation: Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan, ROC. chiuc@auto.fcu.edu.tw
authors.forename: C C
authors.initials: CC
authors.lastname: Chiu
authors.forename: S J
authors.initials: SJ
authors.lastname: Yeh
authors.forename: C H
authors.initials: CH
authors.lastname: Chen
mesh_terms: D016477:Artifacts; D003924:Diabetes Mellitus, Type 2 / Q000503:physiopathology; D006801:Humans; D008955:Models, Cardiovascular; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D017156:Photoplethysmography / Q000295:instrumentation; D011187:Posture; D011674:Pulse / Q000145:classification*; D012016:Reference Values