Finding Tinnitus Patients with Similar Evolution of Their Ecological Momentary Assessments

Creators: Muniandi, Lakshmi Prasath and Schlee, Winfried and Pryss, Rüdiger and Reichert, Manfred and Schobel, Johannes and Kraft, Robin and Spiliopoulou, Myra
Title: Finding Tinnitus Patients with Similar Evolution of Their Ecological Momentary Assessments
Item Type: Conference or Workshop Item
Event Title: (Proceedings of the) 31st IEEE International Symposium on Computer-Based Medical Systems (CBMS 2018)
Event Location: Karlstad, Sweden
Event Dates: June, 18-21, 2018
Projects: DigiHealth
Page Range: pp. 112-117
Date: June 2018
Divisions: Gesundheitsmanagement
Abstract (ENG): Mobile applications can help patients with a chronical disease to record their Ecological Momentary Assessments (EMA) and to get a more precise impression of how their disease manifests itself during day and night and over longer time periods. Such crowdsensing applications contribute to patient empowerment, in which patients monitor their disease and, sometimes, learn to cope better with it. An open question is whether physicians can also be helped in assisting their patients, by understanding similarities and differences in the patients' evolution. We study the EMA of patients with the chronical disease tinnitus, as recorded with the mobile crowdsensing application Track Your Tinnitus. We propose a method that captures similarities in patient evolution, taking account of the differences in the frequency of each patient's EMA recordings. We incorporate this method into a complete workflow that encompasses following components: an algorithm that captures similarities among patients on the basis of their registration data, a method that juxtaposes static patient similarity to EMA-based patient similarity, and a method that identifies those subspaces of the static feature space and those of the EMA-based feature space, which are mainly contributing to patient similarity. We report on our results for the time period recordings from 2014 till 2017 of 450 tinnitus patients from TrackYourTinnitus mobile application.
Forthcoming: No
Language: English
Uncontrolled Keywords: crowdsensing; ecological momentary assessments; patient evolution; patient similarity; timeseries; subspace discovery; tinnitus; medical mining
Link eMedia: Download
Citation:

Muniandi, Lakshmi Prasath and Schlee, Winfried and Pryss, Rüdiger and Reichert, Manfred and Schobel, Johannes and Kraft, Robin and Spiliopoulou, Myra (2018) Finding Tinnitus Patients with Similar Evolution of Their Ecological Momentary Assessments. In: (Proceedings of the) 31st IEEE International Symposium on Computer-Based Medical Systems (CBMS 2018), June, 18-21, 2018, Karlstad, Sweden, pp. 112-117. ISBN 9781538660614

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