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Mobility is one of the key factors for maintaining health up to an old age. Using GPS, individuals' daily-life mobility can be tracked with high resolution in space and time. But how to extract meaningful indicators for the multidimensional nature of mobility?
Mobility, defined as the movement through space between destinations, allows us to reach services and to maintain social activities. It gives us a sense of autonomy and independence and is thus associated with our psychological wellbeing. Finally, the way we move is related to more or less active and thus more or less healthy lifestyles.
Thanks to technological progress, it is nowadays becoming increasingly easy to track individuals' daily-life mobility with high spatio-temporal resolution using GPS. But which mobility indicators should be derived from the raw GPS data in order to represent mobility? And particularly, indicators must not reflect similar aspects of an individual's mobility. This study empirically established a minimum set of mobility indicators which does justice to the multidimensional character of GPS-derived mobility.
First, a mobility classification framework is proposed that systematically organizes the aspects of mobility that can be derived from GPS data. Second, 20 mobility indicators were computed that cover all of the characteristic aspects of the proposed classification framework. Finally, the study uses dimension-reduction technique, to reduce the number of suggested indicators to the minimum number of dimensions that is necessary to represent a full picture of an individual's average mobility behavior.
"This is the first study on how to operationalize daily mobility based on GPS in such a comprehensive way", says Michelle Fillekes, first author, "it will enable further insights into how mobility can help to facilitate healthy aging in the future."
Fillekes, Michelle Pasquale; Giannouli, Eleftheria; Kim, Eun-Kyeong; Zijlstra, Wiebren; Weibel, Robert (2019). Towards a comprehensive set of GPS-based indicators reflecting the multidimensional nature of daily mobility for applications in health and aging research. International Journal of Health Geographics, 18(1):17.