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Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-8461-0089
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).ORCID iD: 0000-0002-4261-281X
Oxford Univ Hosp NHS Fdn Trust, Oxford OX3 7JX, England..
Oxford Univ Hosp NHS Fdn Trust, Oxford OX3 7JX, England..
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2024 (English)In: Sensors, E-ISSN 1424-8220, Vol. 24, no 8, article id 2632Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI, 2024. Vol. 24, no 8, article id 2632
Keywords [en]
6MWT, distance estimation, data reliability, physical assessment
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mau:diva-67314DOI: 10.3390/s24082632ISI: 001210676000001PubMedID: 38676249Scopus ID: 2-s2.0-85191480367OAI: oai:DiVA.org:mau-67314DiVA, id: diva2:1859057
Available from: 2024-05-20 Created: 2024-05-20 Last updated: 2024-05-20Bibliographically approved

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Caramaschi, SaraOlsson, Carl MagnusSalvi, Dario

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