Sayeh Bayat 1, Gary Naglie 2, Mark Rapoport 3, Bing Ye 4, Elaine Stasiulis 5, Alex Mihailidis 6
1 Institute of Biomaterials and Biomedical Engineering, University of Toronto,
2 Baycrest Health Sciences, University of Toronto
3 Sunnybrook Research Institute, University of Toronto
4 Toronto Rehabilitation Institute
5 Baycrest Health Sciences
6 University of Toronto
Worldwide, around 50 million people have dementia and this number is projected to rise to 82 million in 2030 and 152 in 2050 . Persons with dementia (PWD) must eventually stop driving, which poses challenges to maintaining their mobility. Out-of-home mobility is frequently measured in terms of life-space, defined as the spatial area through which a person moves . Life-space is traditionally self-reported using questionnaires or travel diaries and is thus subject to inaccuracies.
The aim of this study is to develop and validate GPS-based life-space measures, assess the feasibility of using GPS technology to measure different dimensions of mobility, and compare mobility patterns between PWD and controls.
In the first of this two-phase study, two dyads of PWD and their caregivers and two controls carried the GPS device when traveling outside their homes for 4 weeks. Spatial and temporal features of mobility, including area, perimeter, and frequency of trips, were measured from the GPS trajectories. Participants’ points of interest were extracted and transportation modes were detected from the GPS data.
Moderate agreements were observed between the results from the algorithms and travel diaries for stay locations, duration of trips, and transportation modes. The PWD visited fewer points of interest compared to control participants (75 ± 15 vs. 113.5 ± 24.5). The PWD also demonstrated smaller life-space compared to control participants in terms of frequency of daily trips away from home (1.15 ± 0.15 vs. 1.85 ± 0.05). Finally, the PWD showed a preference for car commutes over other transportation forms.
The new GPS-based construct shows much promise in objectively and accurately measuring life-space, which is valuable for long-term monitoring of older adults’ out-of-home mobility behaviours. Next steps involve validation of algorithms with a larger sample of participants.
- Alzheimer’s Association, “2016 Alzheimer’s disease facts and figures,” Alzheimer’s & Dementia, vol. 12, no. 4, 2016
- J. Pucher and J. L. Renne, “Rural mobility and mode choice: Evidence from the 2001 National Household Travel Survey,” Transportation, vol. 32, no. 2, pp. 165-186, 2005.