通过在家中进行概率生命体征监测来辅助生活

D. Clifton, Lei A. Clifton, Mohsan S. Alvi, S. Khalid, D. Meredith, J. Price, P. Watkinson, L. Tarassenko
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引用次数: 1

摘要

本文介绍了一种可靠的多传感器数据融合系统的开发,用于监测家庭患者的生命体征。最初的调查工作是在牛津癌症医院的流动医院病人中进行的。我们的监测方法是基于从高风险患者的代表性群体中获得的生命体征数据集中学习到的正常概率模型。每当病人的生命体征相对于正常模式被认为“异常”时,就会向护理人员发出警报。我们展示了这种方法如何正确检测目标患者群体的生理恶化的例子,并描述了在家庭监测应用中进一步验证该技术的未来工作。(6页)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards assisted living via probabilistic vital-sign monitoring in the home
This paper describes the development of a reliable multi-sensor data fusion system for monitoring patient vital-signs in the home. Initial investigatory work has taken place using ambulatory hospital patients, in the Oxford Cancer Hospital. Our monitoring approach is based on a probabilistic model of normality learned from a data-set of vital signs acquired from a representative group of high-risk patients. Alerts are provided to carers whenever patient vital signs are deemed "abnormal" with respect to the model of normality. We show examples of how this approach correctly detects physiological deterioration in the target patient group, and describe future work in further validation of the technology in home monitoring applications. (6 pages)
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