Longitudinal Ambient Sensor Monitoring for Functional Health Assessments: A Case Study
| Autor: | Ben Kröse, Margriet Pol, Saskia Robben |
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| Přispěvatelé: | Amsterdam Machine Learning lab (IVI, FNWI) |
| Jazyk: | angličtina |
| Rok vydání: | 2014 |
| Předmět: | |
| Zdroj: | UbiComp'14 adjunct: proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: September 13-17, 2014, Seattle, WA, USA, 1209-1216 STARTPAGE=1209;ENDPAGE=1216;TITLE=UbiComp'14 adjunct: proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: September 13-17, 2014, Seattle, WA, USA UbiComp Adjunct |
| Popis: | Ambient monitoring systems offer great possibilities for health trend analysis in addition to anomaly detection. Health trend analysis helps care professionals to evaluate someones functional health and direct or evaluate the choice of interventions. This paper presents one case study of a person that was followed with an ambient monitoring system for almost three years and another of a person that was followed for over a year. A simple algorithm is applied to make a location based data representation. This data is visualized for care professionals, and used for inspecting the regularity of the pattern with means of principal component analysis (PCA). This paper provides a set of tools for analyzing longitudinal behavioral data for health assessments. We advocate a standardized data collection procedure, particularly the health metrics that could be used to validate health focused sensor data analyses. |
| Databáze: | OpenAIRE |
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