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Motivating Patients with Depression for Gender-sensitive Cognitive Training Using a Socially Assistive Robot with Bio-signal Driven Pause Management

Martin Pszeida, Alfred Häussl, Julia Zuschnegg, Michael Macher, Sandra Draxler, Thomas Orgel, Michael Schneeberger, Wolfgang Weiss, Jochen A. Mosbacher, Anna Schultz, Dominik Steindl, Silvia Russegger, Regina Roller Wirnsberger, Nina Dalkner, Sandra Schüssler, Eva Z. Reininghaus, Lucas Paletta

Year
2025
Citations
1

Abstract

Depression affects approximately 280 million people worldwide and is often associated with chronic symptoms and cognitive impairments. This study aimed to enhance cognitive function and motivation in individuals with chronic depression using a gender-sensitive Social Assisting Robotic (SAR) system. A humanoid robot (‘Pepper’) was equipped with a tablet delivering interactive cognitive training, including visual, auditory, and stress-adaptive content. In a randomized controlled trial (N = 32), 16 patients received robot-based training, while 16 used tablet-only training. Stress responses were recorded via wearable biosignal sensors and eye tracking. Results include digital stress indicators and responses on the application of short mindfulness exercises within the training session. This is the first study to examine psychophysiological effects of SAR-supported pause management in psychiatric care using biosignal sensor data. The findings support future development of adaptive SAR systems for mental health interventions.

Keywords

Depression (economics)Applied psychologyRobotComputer scienceHuman–computer interactionPsychologySIGNAL (programming language)CognitionArtificial intelligencePsychiatry

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