Int J Health Geogr - Detecting activity locations from raw GPS data: a novel kernel-based algorithm.

Tópicos

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Resumo

CKGROUND: Health studies and mHealth applications are increasingly resorting to tracking technologies such as Global Positioning Systems (GPS) to study the relation between mobility, exposures, and health. GPS tracking generates large sets of geographic data that need to be transformed to be useful for health research. This paper proposes a method to test the performance of activity place detection algorithms, and compares the performance of a novel kernel-based algorithm with a more traditional time-distance cluster detection method.METHODS: A set of 750 artificial GPS tracks containing three stops each were generated, with various levels of noise.. A total of 9,000 tracks were processed to measure the algorithms' capacity to detect stop locations and estimate stop durations, with varying GPS noise and algorithm parameters.RESULTS: The proposed kernel-based algorithm outperformed the traditional algorithm on most criteria associated to activity place detection, and offered a stronger resilience to GPS noise, managing to detect up to 92.3% of actual stops, and estimating stop duration within 5% error margins at all tested noise levels.CONCLUSIONS: Capacity to detect activity locations is an important feature in a context of increasing use of GPS devices in health and place research. While further testing with real-life tracks is recommended, testing algorithms' performance with artificial track sets for which characteristics are controlled is useful. The proposed novel algorithm outperformed the traditional algorithm under these conditions.

Resumo Limpo

ckground health studi mhealth applic increas resort track technolog global posit system gps studi relat mobil exposur health gps track generat larg set geograph data need transform use health research paper propos method test perform activ place detect algorithm compar perform novel kernelbas algorithm tradit timedist cluster detect methodmethod set artifici gps track contain three stop generat various level nois total track process measur algorithm capac detect stop locat estim stop durat vari gps nois algorithm parametersresult propos kernelbas algorithm outperform tradit algorithm criteria associ activ place detect offer stronger resili gps nois manag detect actual stop estim stop durat within error margin test nois levelsconclus capac detect activ locat import featur context increas use gps devic health place research test reallif track recommend test algorithm perform artifici track set characterist control use propos novel algorithm outperform tradit algorithm condit

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