Self-administered Psycho-TherApy-SystemS: Data Analytics and Prescription for SELFPASS
01.12.2016 – 31.05.2020
For the therapy of patients with depression, SELFPASS can quantify and record symptoms by offering self-assessment of the severity of the mental strain on the patient (1) and stored evaluation algorithms (2). Furthermore, SELFPASS offers hands-on steps for self-management (3) taking into account integrated biosignal data (4) of the individual patient as well as relevant location-dependent environmental information (5). This way the patient is provided with individualized instructions for self-management and specific situation-dependent therapy, e.g. for biofeedback training for crisis management. Because of integrated feedback loops, SELFPASS is also a self-learning system (6), which provides personalized support to the participating patient.
To this end, we aim to improve and newly develop automatic methods for the analysis and classification of data from various sources. Secondly, the goal is to develop a system, that provides therapy adapted to the individual patient. Thirdly, generic procedures for the definition and execution of rules and processes based on the data are to be developed, which can trigger automated reactions by the system. For this purpose, external data sources (e.g. environmental information or vital parameters (via wearables)) are to be integrated.
As part of the extension of the project, the application will be supplemented by a virtual reality environment for the treatment of anxiety disorders often associated with depression using exposure therapy.
SELFPASS is funded by the German Federal Ministry of Education and Research within the scope of the action field „Gesundheitswirtschaft im Rahmenprogramm Gesundheitsforschung“