Subproject D02
Subproject D02
Empatho-Kinaesthetic Sensor Technology for Biofeedback in Depressed Patients
The D02 project focuses on utilizing facial expressions as a biomarker in smartphone-based reappraisal training for psychological assessment. The project aims to understand the relationship between cognition, facial expressions, and affect as underlying mechanisms for the development and maintenance of depression. It highlights the lack of empirical studies on facial expressions and the need for quantifying and modifying them. The project presents a feasibility study on smartphone-based biofeedback Training for reducing depressive mood and suggests that this training could be a useful tool for individuals with depressive symptoms. It also proposes the establishment of empathokinaesthetic sensor technology and machine learning methods for the automatic detection and modification of Depression-associated facial expressions, posture, and movement. The mutual activation of depressogenic evaluation processes and depression-associated kinaesthesia is a significant factor in psychological information processing theories. It emphasizes the importance of understanding these underlying mechanisms in developing effective interventions for depression. Overall, the project provides insights into the potential of smartphone-based biofeedback training and machine-learning algorithms in detecting and treating depression.
Contacts
Prof. Dr. Matthias Berking
Principal Investigator
Prof. Dr. Björn Eskofier
Principal Investigator
Marie Keinert, M. Sc.
Doctoral Candidate
Lydia Rupp
Doctoral Candidate
Misha Sadeghi, M. Sc.
Doctoral Candidate
Amirreza Asemanrafat, M. Sc.
Associated Doctoral Candidate
Malin Hager, M.Sc.
Associate Doctoral Candidate
Farnaz Rahimi, M. Sc.
Associate Doctoral Candidate
Additional Information
- Brückner S, Weber J, Michler F, Shanin N, Schober R, Hagelauer A, Weigel R, Gaßner H, Winkler J, Eskofier B, Vossiek M: A Wireless Joint Communication and Localization EMG-Sensing Concept for Movement Disorder Assessment IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology (2023)