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Self-tuning behavioral analysis in AAL "FOOD" project pilot environments.
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![loading](/sites/all/modules/hf_eds/images/loading.gif)
- Author(s): Mora N;Mora N; Losardo A; Losardo A; De Munari I; De Munari I; Ciampolini P; Ciampolini P
- Source:
Studies in health technology and informatics [Stud Health Technol Inform] 2015; Vol. 217, pp. 295-9.- Publication Type:
Journal Article- Language:
English - Source:
- Additional Information
- Source: Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform
- Publication Information: Original Publication: Amsterdam ; Washington, DC : IOS Press, 1991-
- Subject Terms:
- Abstract: Behavioral analysis, based on unobtrusive monitoring through environmental sensors, is expected to increase health awareness of AAL systems. In this paper, techniques for assessing behavioral quantitative features are discussed, suitable for detecting behavioral anomalies in an unsupervised fashion, i.e., with no need of defining target reference behaviors and of tuning user-specific threshold parameters. Such technique is being exploited for analyzing data coming from a set of European pilot sites, in the framework of the EU/AAL-JP project "FOOD", specifically focused at kitchen activity. Simple results are illustrated, suitable for proof-of-concept validation.
- Publication Date: Date Created: 20150822 Date Completed: 20170419 Latest Revision: 20170419
- Publication Date: 20231215
- Accession Number: 26294487
- Source:
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