統計学輪講（第３５回）

日時      2011年01月11日(火)    15時00分～15時50分
場所      経済学部新棟３階第３教室
講演者    Pattara Rujeerapaiboon (情報理工M2)
演題      Statistical Model for Electrocardiogram

概要
Electrocardiogram (ECG) is a series of electrical signals produced by heart
pulses recorded by skin electrodes over a period of time. It captures
important information of the cardiac health and condition of patients. ECG
is usually analyzed and interpreted by medical practitioners to gain
information on the functioning of patients’ hearts, which are important in
cardiovascular diseases or cardiac condition diagnosis.

In this presentation, we will present a statistical generative model for
ECG signals based on a combination of time series analysis techniques and
Bayesian nonparametrics method.  Specifically speaking, we model ECG data
based on multivariate autoregressive model together with 2-level
hierarchical dirichlet hidden markov models .The model is hoped to enhance
effectiveness and efficiency of ECG data analysis.