Advances and challenges in sensor-based research in mobility, health, and place

Kim, Eun Kyeong; Conrow, Lindsey; Röcke, Christina; Chaix, Basile; Weibel, Robert; Perchoux, Camille

doi:10.1016/j.healthplace.2023.102972

Cited by 6 publications

(2 citation statements)

References 75 publications

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“…A total of 255 publications progressed to full-text screening by reviewers (figure 1). Next, bibliographies of excluded review manuscripts [33][34][35][36][37][38][39][40][41][42][43][44][45][46] were checked and methods cited in included manuscripts were checked for possible inclusion. This process yielded an additional 36 manuscripts that were reviewed in full.…”

Section: Study Selection Processmentioning

confidence: 99%

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Pearson,

Tribby,

Brown

et al. 2024

BMJ Open

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Global Positioning System (GPS) technology is increasingly used in health research to capture individual mobility and contextual and environmental exposures. However, the tools, techniques and decisions for using GPS data vary from study to study, making comparisons and reproducibility challenging.ObjectivesThe objectives of this systematic review were to (1) identify best practices for GPS data collection and processing; (2) quantify reporting of best practices in published studies; and (3) discuss examples found in reviewed manuscripts that future researchers may employ for reporting GPS data usage, processing and linkage of GPS data in health studies.DesignA systematic review.Data sourcesElectronic databases searched (24 October 2023) were PubMed, Scopus and Web of Science (PROSPERO ID: CRD42022322166).Eligibility criteriaIncluded peer-reviewed studies published in English met at least one of the criteria: (1) protocols involving GPS for exposure/context and human health research purposes and containing empirical data; (2) linkage of GPS data to other data intended for research on contextual influences on health; (3) associations between GPS-measured mobility or exposures and health; (4) derived variable methods using GPS data in health research; or (5) comparison of GPS tracking with other methods (eg, travel diary).Data extraction and synthesisWe examined 157 manuscripts for reporting of best practices including wear time, sampling frequency, data validity, noise/signal loss and data linkage to assess risk of bias.ResultsWe found that 6% of the studies did not disclose the GPS device model used, only 12.1% reported the per cent of GPS data lost by signal loss, only 15.7% reported the per cent of GPS data considered to be noise and only 68.2% reported the inclusion criteria for their data.ConclusionsOur recommendations for reporting on GPS usage, processing and linkage may be transferrable to other geospatial devices, with the hope of promoting transparency and reproducibility in this research.PROSPERO registration numberCRD42022322166.

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Section: Study Selection Processmentioning

confidence: 99%

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Pearson,

Tribby,

Brown

et al. 2024

BMJ Open

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“…Additionally, it requires environmental conditions, such as an obstacle-free hallway, preferably at least 30 m long, which is not always accessible. Thanks to technological advances in sensors and mobile devices these tests can be performed remotely and in patients’ homes or communities [ 7 ]. Such remote 6MWTs reduces the required effort for patients and clinical staff, which promotes more frequent and, therefore, more robust monitoring of patients [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT

Caramaschi,

Olsson,

Orchard

et al. 2024

Sensors

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As a result of technological advancements, functional capacity assessments, such as the 6-minute walk test, can be performed remotely, at home and in the community. Current studies, however, tend to overlook the crucial aspect of data quality, often limiting their focus to idealised scenarios. Challenging conditions may arise when performing a test given the risk of collecting poor-quality GNSS signal, which can undermine the reliability of the results. This work shows the impact of applying filtering rules to avoid noisy samples in common algorithms that compute the walked distance from positioning data. Then, based on signal features, we assess the reliability of the distance estimation using logistic regression from the following two perspectives: error-based analysis, which relates to the estimated distance error, and user-based analysis, which distinguishes conventional from unconventional tests based on users’ previous annotations. We highlight the impact of features associated with walked path irregularity and direction changes to establish data quality. We evaluate features within a binary classification task and reach an F1-score of 0.93 and an area under the curve of 0.97 for the user-based classification. Identifying unreliable tests is helpful to clinicians, who receive the recorded test results accompanied by quality assessments, and to patients, who can be given the opportunity to repeat tests classified as not following the instructions.

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How mobility pattern shapes the association between static green space and dynamic green space exposure

Zheng,

Kwan,

Liu

et al. 2024

Environmental Research

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Advances and challenges in sensor-based research in mobility, health, and place

Cited by 6 publications

References 75 publications

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Systematic review of best practices for GPS data usage, processing, and linkage in health, exposure science and environmental context research

Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT

How mobility pattern shapes the association between static green space and dynamic green space exposure

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