An advanced solution based on machine learning for remote EMDR therapy
Description
For this work, a preliminary study proposed virtual interfaces for remote psychotherapy and psychology practices. This study aimed to verify the efficacy of such approaches in obtaining results comparable to in-presence psychotherapy, when the therapist is physically present in the room. In particular, we implemented several joint machine-learning techniques for distance detection, camera calibration and eye tracking, assembled to create a full virtual environment for the execution of a psychological protocol for a self-induced mindfulness meditative state. Notably, such a protocol is also applicable for the desensitization phase of EMDR therapy. This preliminary study has proven that, compared to a simple control task, such as filling in a questionnaire, the application of the mindfulness protocol in a fully virtual setting greatly improves concentration and lowers stress for the subjects it has been tested on, therefore proving the efficacy of a remote approach when compared to an in-presence one. This opens up the possibility of deepening the study, to create a fully working interface which will be applicable in various on-field applications of psychotherapy where the presence of the therapist cannot be always guaranteed.
Format
Journal
Language
English
Original Work Citation
Fiani, F., Russo, S., & Napoli, C. (2023). An advanced solution based on machine learning for remote EMDR therapy. Technologies, 11(6), 172. doi:10.3390/technologies11060172
Citation
“An advanced solution based on machine learning for remote EMDR therapy,” Francine Shapiro Library, accessed May 17, 2024, https://francineshapirolibrary.omeka.net/items/show/28539.