Abstract
We describe stroke patients’ activity patterns and trends based on motion data acquired during their stay in an ambulatory day-care centre. Our aim was to explore and quantify intensity and development in the patients’ activity patterns as these may change during the rehabilitation process. We analyse motion data recordings from wearable inertial measurement units of eleven patients up to eleven days, totally 102 recording days. Using logic rules, we extract activity primitives, including affected arm move, sit, stand, walking, etc. from selected channels of the continuous median-filtered sensor data. Using relative duration of the activity primitives, we examine patient activity patterns regarding independence in mobility, distribution of walking over the days and trends in using the affected body side. Due to the heterogeneity of patients’ behaviour, we focused on analysing patient-specific activity patterns. Our exploration showed that the rule-based activity primitive analysis is beneficial to understand individual patient activity.
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Acknowledgements
We are thankful to the study participants and the therapists at the Reha Rheinfelden. This work was supported by the EU Marie Curie Network iCareNet, grant number 264738 and the Dutch Technology Foundation STW grant number 12184.
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Derungs, A., Seiter, J., Schuster-Amft, C., Amft, O. (2015). Activity Patterns in Stroke Patients - Is There a Trend in Behaviour During Rehabilitation?. In: Salah, A., Kröse, B., Cook, D. (eds) Human Behavior Understanding. Lecture Notes in Computer Science(), vol 9277. Springer, Cham. https://doi.org/10.1007/978-3-319-24195-1_11
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DOI: https://doi.org/10.1007/978-3-319-24195-1_11
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