title: Tunnel morph model for time frequency bio-signal waveform processing.
abstract: In this paper, we proposed a tunnel morph model for bio-signal waveform in measuring their similarity. Firstly, the formal specifications of bio-signal waveforms are given. And then, a series of model establishing related definitions are presented. These definitions contain waveform segmentation; waveforms distance measurement, and tunnel width computation. Moreover, on the base of the model, a similarity measuring strategy which takes the curve feature of bio-signal into account was presented. In the end, the strategy was compared with other similarity measurement methods by AECG (Ambulatory Electrocardiogram) waveform data. The data are adopted from MIT/BIH arrhythmia database. Experiment results show that the sensitivity and the positive predictivity of the strategy based on tunnel morph model are prior to other strategies.
authors.affiliation: Laboratory of Biological Signal and Intelligent Processing, Tianjin University of Technology, 300119, China. kenneth_zheng@vip.163.com
authors.forename: Gang
authors.initials: G
authors.lastname: Zheng
authors.forename: Shiliu
authors.initials: S
authors.lastname: Lian
authors.forename: Shanling
authors.initials: S
authors.lastname: Mou
authors.forename: Jia
authors.initials: J
authors.lastname: Qi
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D015716:Electrocardiography, Ambulatory / Q000379:methods*; D006801:Humans; D008955:Models, Cardiovascular; D012815:Signal Processing, Computer-Assisted