Ding Yaohan, Ertugrul Itir Onal, Darzi Ali, Provenza Nicole, Jeni László A, Borton David, Goodman Wayne, Cohn Jeffrey
University of Pittsburgh, Pittsburgh, U.S.A.
Tilburg University, Tilburg, Netherlands.
Companion Publ 2020 Int Conf Multimodal Interact. 2020 Oct;2020:354-356. doi: 10.1145/3395035.3425354.
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 are 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 post-DBS adjustment. Using SVM and XGBoost, participant's pre- and post-adjustment appearances were differentiated with 1 of 0.76, which suggests feasibility of objective measurement of mirth response.
对腹侧纹状体(VS)进行连续深部脑刺激(DBS)是治疗严重的、难治性强迫症(OCD)的有效方法。最佳参数设置由强烈积极情绪的欢笑反应发出信号,临床医生通过主观判断来识别这些反应。主观判断因人而异且难以标准化。为了客观测量欢笑反应,我们在对一名接受DBS治疗的患者进行的一系列纵向评估中使用了自动面部表情识别(AFAR)技术。使用统计和机器学习方法对DBS调整前后进行了比较。DBS调整后积极情绪显著更高。使用支持向量机(SVM)和极端梯度提升(XGBoost),参与者调整前后的外貌区分度为0.76,这表明客观测量欢笑反应是可行的。