MS Pattern Explorer: interactive visual exploration of temporal activity patterns for multiple sclerosis

Morgenshtern, Gabriela; Rutishauser, Yves; Haag, Christina; von Wyl, Viktor; Bernard, Jürgen

doi:10.5167/uzh-265720

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Morgenshtern, G., Rutishauser, Y., Haag, C., von Wyl, V., & Bernard, J. (2024). MS Pattern Explorer: interactive visual exploration of temporal activity patterns for multiple sclerosis. Journal of the American Medical Informatics Association (JAMIA), 31, 2496–2506. https://doi.org/10.1093/jamia/ocae230

Abstract

This article describes the design and evaluation of MS Pattern Explorer, a novel visual tool that uses interactive machine learning to analyze fitness wearables’ data. Applied to a clinical study of multiple sclerosis (MS) patients, the tool addresses key challenges: managing activity signals, accelerating insight generation, and rapidly contextualizing identified patterns. By analyzing sensor measurements, it aims to enhance understanding of MS symptomatology and improve the broader problem of clinical exploratory sensor data analysi