ArticleJMIR aging2020
Inferring Destinations and Activity Types of Older Adults From GPS Data: Algorithm Development and Validation.
Article in JMIR aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Wearable and Portable GPS Solutions for Monitoring Mobility in Dementia: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Driving the neural exposome: Latent mobility states from naturalistic GPS data in older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Toward an understanding of real-world mobility in Parkinson's: insights from enhanced contextualisation using GPS-derived location and data-driven modeling of walking speed.Frontiers in aging neuroscience · 2026Article
- Elderly Activity Life-Space Envelopes (EASE): Development and Feasibility of a Comprehensive, Integrated Protocol for Life-Space Mobility Research in Population Health.JMIR research protocols · 2025Article
- The neighbourhood built environment affects driving behaviours of older adults: a combined geographic information systems and machine learning method.Cities & health · 2025Article
- Examination of Naturalistic Driving Behavior and Risk Events Across Concussion Recovery.Transportation research. Part F, Traffic psychology and behaviour · 2025Article
- Outdoor life in dementia: How predictable are people with dementia in their mobility?Alzheimer's & dementia (Amsterdam, Netherlands) · 2021Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundOutdoor mobility is an important aspect of older adults' functional status. GPS has been used to create indicators reflecting the spatiotemporal dimensions of outdoor mobility for applications in health and aging. However, outdoor mobility is a multidimensional construct. There is, as of yet, no classification algorithm that groups and characterizes older adults' outdoor mobility based on its semantic aspects (ie, mobility intentions and motivations) by integrating geographic and domain knowledge.
objectiveThis study assesses the feasibility of using GPS to determine semantic dimensions of older adults' outdoor mobility, including destinations and activity types.
methodsA total of 5 healthy individuals, aged 65 years or older, carried a GPS device when traveling outside their homes for 4 weeks. The participants were also given a travel diary to record details of all excursions from their homes, including date, time, and destination information. We first designed and implemented an algorithm to extract destinations and infer activity types (eg, food, shopping, and sport) from the GPS data. We then evaluated the performance of the GPS-derived destination and activity information against the traditional diary method.
resultsOur results detected the stop locations of older adults from their GPS data with an F1 score of 87%. On average, the extracted home locations were within a 40.18-meter (SD 1.18) distance of the actual home locations. For the activity-inference algorithm, our results reached an F1 score of 86% for all participants, suggesting a reasonable accuracy against the travel diary recordings. Our results also suggest that the activity inference's accuracy measure differed by neighborhood characteristics (ie, Walk Score).
conclusionsWe conclude that GPS technology is accurate for determining semantic dimensions of outdoor mobility. However, further improvements may be needed to develop a robust application of this system that can be adopted in clinical practice.
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