Development of Cognitive and Emotional Biomarkers Using Biosignals Processing and Virtual Environments: Application to Clinical Psychology and Neurodevelopmental Disorders

Current clinical assessment procedures mostly rely on subjective evaluations made by expert clinicians regarding the presence or absence of clinical symptoms. The primary method for screening clinical disorders is the clinical interview, wherein expert clinicians pose questions to investigate the mental and cognitive state of patients and check for specific symptom configurations. Despite its widespread use, this approach has limitations, including the absence of objective neurobiological measures that extend beyond patients' self-reports, as well as a lack of ecological procedures in the testing environments. Over the last decades, human biosignals have gained interest in research as scientific measures that convey neurobiological information beyond subjective awareness. They have the potential to enhance the objectivity of clinical assessment procedures through the automatic detection of emotional and cognitive biomarkers of disorders. The current proposal is to objectively record biosignals during the ecological stimulation of the patient, and apply artificial intelligence models to these biosignals to automatically detect clinical disorders. To achieve ecological validity in stimulation, virtual reality (VR) is gaining consensus due to its ability to provide realistic situations where users act as they would in the real world. VR can also provide safe and controlled environments for patient evaluations. The main objective of this doctoral thesis is to overcome the limitations of current clinical assessment procedures by using, on one side, biosignal recording and automatic biomarker detection to enhance assessment objectivity, and, on the other side, VR to provide ecological stimulations that resemble real-life environments where users can act as if they were not undergoing a clinical evaluation. Autism spectrum disorder (ASD)