Scalable Integration of Multiple Health Sensor Data for Observing Medical Patterns

• Type: Article in International Conference Proceedings Book
• Date: 2012

Authors

Hugo Sereno Ferreira (Author) FEUP; Sousa, TB (Author) Other; Martins, A (Author) Other

Conference proceedings International

Title: COOPERATIVE DESIGN, VISUALIZATION, AND ENGINEERING (CDVE)

Pages: 78-84

9th Annual International Conference on Cooperative Design, Visualization, and Engineering (CDVE)

Osaka, JAPAN, SEP 02-05, 2012

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 3 Citations

Other information

Authenticus ID: P-002-E8T

DOI: 10.1007/978-3-642-32609-7_11

Abstract (EN): With an aging global population, Ambient Assisted Living (AAL) attempts to improve life expectancy and quality of life through the remote monitoring of various health signals using personal and home-based sensors. Possible medical conditions can be early ascertained by observable patterns over the patients' health data. However, aggregating multiple raw signals and matching against medical protocols can be computational and bandwidth intensive. Moreover, adding new protocols requires non-trivial expertise to define necessary rules. This paper describes a lightweight, scalable, and composable mechanism that captures, processes and infers possible health problems from raw data obtained from multiple sensors.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7