Automated Detection of Optimal DBS Device Settings
Abstract
Continuous deep brain stimulation (DBS) of the ventral striatum (VS) is an effective treatment for severe, treatment-refractory obsessive-compulsive disorder (OCD). Optimal parameter settings are signaled by a mirth response of intense positive affect, which is subjectively identified by clinicians. Subjective judgments are idiosyncratic and difficult to standardize. To objectively measure mirth responses, we used Automatic Facial Affect Recognition (AFAR) in a series of longitudinal assessments of a patient treated with DBS. Pre- and post-adjustment DBS were compared using both statistical and machine learning approaches. Positive affect was significantly higher after DBS adjustment. Using XGBoost and SVM, the participant's pre- and post-adjustment responses were differentiated with accuracy values of 0.76 and 0.75, which suggest feasibility of objective measurement of mirth response.
BibTeX
@conference{Ding-2020-125824,author = {Yaohan Ding and Itir Onal Ertugrul and Ali Darzi and Nicole Provenza and Laszlo A. Jeni and David Borton and Wayne Goodman and Jeffrey Cohn},
title = {Automated Detection of Optimal DBS Device Settings},
booktitle = {Proceedings of Companion Publication of the 2020 International Conference on Multimodal Interaction (ICMI '20)},
year = {2020},
month = {October},
pages = {354 - 356},
}