Do We Walk Differently at Home? A Context-Aware Gait Analysis System in Continuous Real-World Environments

Driven by the advancements of wearable sensors and signal processing algorithms, studies on continuous real-world monitoring are of major interest in the field of clinical gait and motion analysis. While real-world studies enable a more detailed and realistic insight into various mobility parameters...

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Bibliographic Details
Published in:2021 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2021; pp. 1932 - 1935
Main Authors: Roth, Nils, Wieland, Georg P., Kuderle, Arne, Ullrich, Martin, Gladow, Till, Marxreiter, Franz, Klucken, Jochen, Eskofier, Bjoern M., Kluge, Felix
Format: Conference Proceeding Journal Article
Language:English
Published: United States IEEE 01.11.2021
Subjects:
Biology
Bluetooth
Environmental factors
Gait
Gait Analysis
Humans
Legged locomotion
Motion analysis
Parkinson Disease
Signal processing algorithms
Walking
Walking Speed
Wearable sensors
ISSN:2694-0604, 2694-0604
Online Access:Get full text
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Summary:Driven by the advancements of wearable sensors and signal processing algorithms, studies on continuous real-world monitoring are of major interest in the field of clinical gait and motion analysis. While real-world studies enable a more detailed and realistic insight into various mobility parameters such as walking speed, confounding and environmental factors might skew those digital mobility outcomes (DMOs), making the interpretation of results challenging. To consider confounding factors, context information needs to be included in the analysis. In this work, we present a context-aware mobile gait analysis system that can distinguish between gait recorded at home and not at home based on Bluetooth proximity information. The system was evaluated on 9 healthy subjects and 6 Parkinsons disease (PD) patients. The classification of the at home/not at home context reached an average F1-score of 98.2 ± 3.2 %. A context-aware analysis of gait parameters revealed different walking bout length distributions between the two environmental conditions. Furthermore, a reduction of gait speed within the at home context compared to walking not at home of 8.9 ± 9.4 % and 8.7 ±5.9 % on average for healthy and PD subjects was found, respectively. Our results indicate the influence of the recording environment on DMOs and, therefore, emphasize the importance of context in the analysis of continuous motion data. Hence, the presented work contributes to a better understanding of confounding factors for future real-world studies.
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ISSN:2694-0604
2694-0604
DOI:10.1109/EMBC46164.2021.9630378