贝叶斯心率模型揭示实时生理信息

2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom) Pub Date : 2012-12-13 DOI:10.1109/HealthCom.2012.6379412

Giorgio Quer, R. Rao

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引用次数: 5

摘要

人的心率受到身体不同内部系统的影响，可以揭示有关健康和疾病状况的宝贵信息。在本文中，我们使用贝叶斯方法分析瞬时心率信号，实时推断出近似于该信号真实分布的概率分布。在我们的框架内对收集的实际数据进行实验分析后，选择最佳模型。这种分布的参数可以实时揭示自主神经系统(ANS)交感神经和副交感神经分裂的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Bayesian model of heart rate to reveal real-time physiological information

The human heart rate is influenced by different internal systems of the body and can reveal valuable information about health and disease conditions. In this paper, we analyze the instantaneous heart rate signal using a Bayesian method, inferring in real time a probabilistic distribution that approximates the real distribution of this signal. The best model is chosen after an experimental analysis of real data collected within our framework. The parameters of this distribution can reveal interesting insights on the influences of the sympathetic and parasympathetic divisions of the autonomic nervous system (ANS) in real time.

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来源期刊

2012 IEEE 14th International Conference on e-Health Networking, Applications and Services (Healthcom)

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