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Computer-aided psychoterapy based on multimodal elicitation, estimation and regulation of emotion


Ćosić, Krešimir; Popović, Siniša; Horvat, Marko; Kukolja, Davor; Dropuljić, Branimir; Kovač, Bernard; Jakovljević, Miro
Computer-aided psychoterapy based on multimodal elicitation, estimation and regulation of emotion // 1st International Conference on Creative Psychopharmacotherapy
Dubrovnik, Hrvatska, 2013. (pozvano predavanje, nije recenziran, neobjavljeni rad, znanstveni)


Naslov
Computer-aided psychoterapy based on multimodal elicitation, estimation and regulation of emotion

Autori
Ćosić, Krešimir ; Popović, Siniša ; Horvat, Marko ; Kukolja, Davor ; Dropuljić, Branimir ; Kovač, Bernard ; Jakovljević, Miro

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, neobjavljeni rad, znanstveni

Izvornik
1st International Conference on Creative Psychopharmacotherapy / - , 2013

Skup
1st International Conference on Creative Psychopharmacotherapy

Mjesto i datum
Dubrovnik, Hrvatska, 25-28.09.2013

Vrsta sudjelovanja
Pozvano predavanje

Vrsta recenzije
Nije recenziran

Ključne riječi
Emotion elicitation; multimodal stimulation; cognitive appraisal; multimodal features; emotion estimation; physiological; acoustic; linguistic; facial features

Sažetak
Contemporary psychiatry is looking at affective sciences to understand human behavior, cognition and the mind in health and disease. Since it has been recognized that emotions have a pivotal role for the human mind, an ever increasing number of laboratories and research centers are interested in affective sciences, affective neuroscience, affective psychology and affective psychopathology. Therefore, this paper presents multidisciplinary research results of Laboratory for Interactive Simulation System at Faculty of Electrical Engineering and Computing, University of Zagreb in the stress resilience. Patient’s distortion in emotional processing of multimodal input stimuli is predominantly consequence of his/her cognitive deficit which is result of their individual mental health disorders. These emotional distortions in patient’s multimodal physiological, facial, acoustic, and linguistic features related to presented stimulation can be used as indicator of patient’s mental illness. Real-time processing and analysis of patient’s multimodal response related to annotated input stimuli is based on appropriate machine learning methods from computer science. Comprehensive longitudinal multimodal analysis of patient’s emotion, mood, feelings, attention, motivation, decision-making, and working memory in synchronization with multimodal stimuli provides extremely valuable big database for data mining, machine learning and machine reasoning. Presented multimedia stimuli sequence includes personalized images, movies and sounds, as well as semantically congruent narratives. Simultaneously, with stimuli presentation patient provides subjective emotional ratings of presented stimuli in terms of subjective units of discomfort/distress, discrete emotions, or valence and arousal. These subjective emotional ratings of input stimuli and corresponding physiological, speech, and facial output features provides enough information for evaluation of patient’s cognitive appraisal deficit. Aggregated real-time visualization of this information provides valuable assistance in patient mental state diagnostics enabling therapist deeper and broader insights into dynamics and progress of the psychotherapy.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Kliničke medicinske znanosti



POVEZANOST RADA


Projekt / tema
036-0000000-2029 - Adaptivno upravljanje scenarijima u VR terapiji PTSP-a (Krešimir Ćosić, )
108-1080037-0323 - Multidimenzionalna analiza bioloških pokazatelja u duševnim poremećajima (Miro Jakovljević, )

Ustanove
Fakultet elektrotehnike i računarstva, Zagreb,
Medicinski fakultet, Zagreb