Wireless sensor networks are becoming popular in the field of ambient assisted living. In this paper we report our study on the relationship between a functional health metric and features derived from the sensor data. Sensor systems are installed in the houses of nine people who are also quarterly visited by an occupational therapist for functional health assessments. Different features are extracted and these are correlated with a metric of functional health (the AMPS). Though the sample is small, the results indicate that some features are better in describing the functional health in the population, but individual differences should also be taken into account when developing a sensor system for functional health assessment.
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This paper describes a participatory design-oriented study of an ambient assisted living system for monitoring the daily activities of elderly residents. The work presented addresses these questions 1) What daily activities the elderly participants like to be monitored, 2) With whom they would want to share this monitored data and 3) How a monitoring system for the elderly should be designed. For this purpose, this paper discusses the study results and participatory design techniques used to exemplify and understand desired ambient-assisted living scenarios and information sharing needs. Particularly, an interactive dollhouse is presented as a method for including the elderly in the design and requirements gathering process for residential monitoring. The study results indicate the importance of exemplifying ambient-assisted living scenarios to involve the elderly and so to increase acceptance and utility of such systems. The preliminary studies presented show that the participants were willing to have most of their daily activities monitored. However, they mostly wanted to keep control over their own data and share this information with medical specialists and particularly not with their fellow elderly neighbours.
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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.
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