TY  - JOUR
A1  - Prakash, Subash
A1  - Unnikrishnan, Vishnu
A1  - Pryss, Rüdiger
A1  - Kraft, Robin
A1  - Schobel, Johannes
A1  - Hannemann, Ronny
A1  - Langguth, Berthold
A1  - Schlee, Winfried
A1  - Spiliopoulou, Myra
T1  - Interactive system for similarity-based inspection and assessment of the well-being of mHealth users
T2  - Entropy
N2  - Recent digitization technologies empower mHealth users to conveniently record their Ecological Momentary Assessments (EMA) through web applications, smartphones, and wearable devices. These recordings can help clinicians understand how the users' condition changes, but appropriate learning and visualization mechanisms are required for this purpose. We propose a web-based visual analytics tool, which processes clinical data as well as EMAs that were recorded through a mHealth application. The goals we pursue are (1) to predict the condition of the user in the near and the far future, while also identifying the clinical data that mostly contribute to EMA predictions, (2) to identify users with outlier EMA, and (3) to show to what extent the EMAs of a user are in line with or diverge from those users similar to him/her. We report our findings based on a pilot study on patient empowerment, involving tinnitus patients who recorded EMAs with the mHealth app TinnitusTips. To validate our method, we also derived synthetic data from the same pilot study. Based on this setting, results for different use cases are reported.
KW  - medical analytics
KW  - condition prediction
KW  - ecological momentary assessment
KW  - visual analytics
KW  - time series
Y1  - 2021
UR  - https://opus.bibliothek.uni-wuerzburg.de/frontdoor/index/index/docId/25233
UR  - https://nbn-resolving.org/urn:nbn:de:bvb:20-opus-252333
SN  - 1099-4300
VL  - 23
IS  - 12
ER  -