SAPhyRA: Stream analysis for physiological risk assessment

被引：1

作者：

Apiletti, Daniele ^{[1
]}

Baralis, Elena ^{[1
]}

Bruno, Giulia ^{[1
]}

Cerquitelli, Tania ^{[1
]}

机构：

[1] Politecn Torino, Corso Abruzzi 24, Turin, Italy

来源：

TWENTIETH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS | 2007年

关键词：

D O I：

10.1109/CBMS.2007.95

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Advances in technology allow the continuous physiological monitoring of people using non-invasive sensors. An important issue in this context is the real-time analysis of physiological signals performed on mobile devices, which requires optimized power consumption and short processing response time. The SAPhyRA framework performs real-time stream analysis for physiological risk assessment. To this aim, the framework evaluates people's health conditions by analyzing different clinical signals in a sliding time window. Given historical physiological measures, different models of patients and diseases are built. The most suitable model for the current monitored patient is exploited in the real nine stream classification phase. Preliminary experiments performed on public physiological data show the effectiveness and flexibility of the proposed approach.

引用

页码：193 / +

页数：2