Sensors, Vol. 24, Pages 2632: Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT

Sensors, Vol. 24, Pages 2632: Assessing the Effect of Data Quality on Distance Estimation in Smartphone-Based Outdoor 6MWT Sensors doi: 10.3390/s24082632 Authors: Sara Caramaschi Carl Magnus Olsson Elizabeth Orchard Jackson Molloy Dario Salvi 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 classif...
Source: Sensors - Category: Biotechnology Authors: Tags: Article Source Type: research
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