title: An approach to determine myocardial ischemia by hidden Markov models.
abstract: A hidden Markov model (HMM) of electrocardiogram (ECG) signal is presented for detection of myocardial ischemia. The time domain signals that are recorded by the ECG before and during the episode of local ischemia were pre-processed to produce input sequences, which is needed for the model training. The model is also verified by test data, and the results show that the models have certain function for the detection of myocardial ischemia. The algorithm based on HMM provides a possible approach for the timely, rapid and automatic diagnosis of myocardial ischemia, and also can be used in portable medical diagnostic equipment in the future.
authors.affiliation: School of Life Science and Technology, Beijing Institute of Technology, Beijing 100081, P.R. China.
authors.forename: Xiaoying
authors.initials: X
authors.lastname: Tang
authors.forename: Li
authors.initials: L
authors.lastname: Xia
authors.forename: Weifeng
authors.initials: W
authors.lastname: Liu
authors.forename: Yuhua
authors.initials: Y
authors.lastname: Peng
authors.forename: Tianxin
authors.initials: T
authors.lastname: Gao
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D008390:Markov Chains; D008955:Models, Cardiovascular; D015233:Models, Statistical; D017202:Myocardial Ischemia / Q000175:diagnosis*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity