ProjectSSTeP-KiZ – Smarte Sensorik bei Telepsychotherapie von Kindern und Jugendlichen mit Zwangsstörungen
Basic data
Acronym:
SSTeP-KiZ
Title:
Smarte Sensorik bei Telepsychotherapie von Kindern und Jugendlichen mit Zwangsstörungen
Duration:
01/04/2020 to 30/09/2022
Abstract / short description:
Through the use of sensors that can be worn in everyday life and an intelligent analysis of multi-modal sensor data, SSTeP-KiZ aims to significantly improve the treatment options for mentally ill children and adolescents with obsessive-compulsive disorders. The aim is to support telepsychotherapeutic treatment of affected children and adolescents in their home environment by integrating data collected via sensors. SSTeP-KiZ will use a combination of movement data, image acquisition, eye tracking and physiological markers such as heart rate, heart rate variability and pupillometry to draw conclusions about the emotional state and stress reactions to symptom-triggering stimuli and further on the progress of therapy.
By integrating the various data modalities, multivariate analysis procedures with machine learning can be used to objectify stimuli with regard to their significance for the disease. The extraction and integration of sensor data from the ecologically valid home environment enables a considerable improvement in therapy planning and implementation, especially for children and adolescents, since the independent feedback on symptom complexes required in the previous therapeutic approach is often limited due to developmental and disease-related factors. In addition, in the medium term, SSTeP-KiZ should also enable the use of data on anxiety and stress levels (pupillometry, heart rate, eye tracking) in real time by the therapist while still in the therapy session. Thus, even under the conditions of telepsychotherapy, the individual intensity of the therapy sessions can be directly adjusted and the compliance of the patients during the accompanied therapy tasks can be directly promoted. Furthermore, within the framework of SSTEP-KiZ, the data obtained will be processed in a suitable form for the children and adolescents concerned and their relatives and, in the sense of therapeutic feedback, will be visualized in a suitable way to form an additional component of the therapy.
By integrating the various data modalities, multivariate analysis procedures with machine learning can be used to objectify stimuli with regard to their significance for the disease. The extraction and integration of sensor data from the ecologically valid home environment enables a considerable improvement in therapy planning and implementation, especially for children and adolescents, since the independent feedback on symptom complexes required in the previous therapeutic approach is often limited due to developmental and disease-related factors. In addition, in the medium term, SSTeP-KiZ should also enable the use of data on anxiety and stress levels (pupillometry, heart rate, eye tracking) in real time by the therapist while still in the therapy session. Thus, even under the conditions of telepsychotherapy, the individual intensity of the therapy sessions can be directly adjusted and the compliance of the patients during the accompanied therapy tasks can be directly promoted. Furthermore, within the framework of SSTEP-KiZ, the data obtained will be processed in a suitable form for the children and adolescents concerned and their relatives and, in the sense of therapeutic feedback, will be visualized in a suitable way to form an additional component of the therapy.
Keywords:
eye tracking
Eye-Tracking
Multimodale Sensorinformation
Ferntherapie
Involved staff
Managers
Department of Informatics
Faculty of Science
Faculty of Science
Local organizational units
Department of Informatics
Faculty of Science
University of Tübingen
University of Tübingen
Funders
Bonn, Nordrhein-Westfalen, Germany