The Aging phenomenon entails increased costs to health care systems worldwide. Prevention and self-management of age-related conditions receive high priority in public health research. Multidimensionality of impairments should be considered when designing interventions targeting the older population. Detection of slow or fast changes in daily functioning can enable interventions that counteract the decline, e.g. through behavior change support. Technology facilitates unobtrusive monitoring of daily living, allowing continuous and real-time assessment of the health status. Sensing outdoors remains a challenge especially for non physiological parameters. In this paper we present the results of a pilot study on monitoring physical functioning using an accelerometer and experience sampling method on a smartphone. We analyzed the relation between daily physical activity level and a number of different properties of daily living (location, social component, activity type and the weekday). Five healthy older adults participated in the study during approximately one month. Our results show that location, social interactions, type of activities and day of the week influence significantly the daily activity level of the participants. Results from this study will be used in the further development of an unobtrusive monitoring and coaching system to encourage active behavior on a daily basis.
|Name||CEUR workshop proceedings|
|Publisher||R. Piskac c/o Redaktion Sun SITE, Informatik V, RWTH Aachen|
|Workshop||International Workshop on Personalization and Adaptation in Technology for Health 2015 (PATH 2015)|
|Abbreviated title||PATH 2015|
|Period||30/06/15 → 30/06/15|
|Other||held in conjunction with the 23rd Conference on User Modelling, Adaptation and Personalisation (UMAP 2015)|