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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: 2025-04-03Bibliographically approved
In thesis
1. Digital health technologies for unsupervised physical activity testing and monitoring
Open this publication in new window or tab >>Digital health technologies for unsupervised physical activity testing and monitoring
2025 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Monitoring physical activity, function and capacity through Digital Health Technology (DHT) has a high potential to benefit healthcare providers and patients. Current practices of observing physical function and capacity use standard tests such as the 6-Minute Walk Test (6MWT) or the Timed Up and Go, which collect momentary information on the patient’s health status. The use of DHT is demonstrated to enhance these types of assessments, from the instrumentation of physical tests with technology to the analysis of digital biomarkers collected during one’s daily life. Research at national and international levels investigates these topics on a large scale; however, it often lacks transparency and details in regards to used algorithms and data quality. These aspects are crucial when implementing technology for health-related purposes, where data quality and methods accuracy are fundamental for impacting clinical practices. This thesis investigates how DHT can support physical testing in ecological or community environments, answering three main research questions related to data collection and quality, algorithms, and the association between daily life physical activity and physical tests. Throughout six articles, this work investigates methods for inferring walked distance during the 6MWT in indoor and outdoor conditions, highlighting the importance of data quality collected through DHT. It shares a publicly available dataset providing inertial and localization information of patients and healthy volunteers. Lastly, it reports on insights and common procedures regarding DHT used during everyday life and its relation with physical tests. Foundations are laid for future work in this domain.   

Place, publisher, year, edition, pages
Malmö: Malmö University Press, 2025. p. 40
Series
Studies in Computer Science ; 36
Keywords
Digital Health Technology, Physical Activity, 6-Minute Walk Test, Data quality, Real-world Assessment
National Category
Medical Engineering
Identifiers
urn:nbn:se:mau:diva-75110 (URN)10.24834/isbn.9789178775958 (DOI)978-91-7877-594-1 (ISBN)978-91-7877-595-8 (ISBN)
Presentation
2025-04-07, Auditorium B1, Niagara, Malmö, 10:15 (English)
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Note

Paper 5 and 6 i dissertation as manuscript. Not included in the full text online. 

Available from: 2025-04-03 Created: 2025-04-03 Last updated: 2026-02-24Bibliographically approved

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Caramaschi, SaraOlsson, Carl MagnusSalvi, Dario

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