We study the statistical properties of facial behaviour altered by the regulation of brain arousal in the clinical domain of psychiatry. The underlying mechanism is linked to the empirical interpretation of the vigilance continuum as behavioral surrogate measurement for certain states of mind. We name the presented measurement in the sense of the classical scalp based obtrusive sensors Opto Electronic Encephalography (OEG) which relies solely on modern camera based real-time signal processing and computer vision. Based upon a stochastic representation as coherence of the face dynamics, reflecting the hemifacial asymmetry in emotion expressions, we demonstrate an almost flawless distinction between patients and healthy controls as well as between the mental disorders depression and schizophrenia and the symptom severity. In contrast to the standard diagnostic process, which is time-consuming, subjective and does not incorporate neurobiological data such as real-time face dynamics, the objective stochastic modeling of the affective responsiveness only requires a few minutes of video-based facial recordings. We also highlight the potential of the methodology as a causal inference model in transdiagnostic analysis to predict the outcome of pharmacological treatment. All results are obtained on a clinical longitudinal data collection with an amount of 100 patients and 50 controls.
翻译:我们研究在精神病学临床领域对大脑的振动进行调节所改变的面部行为的统计特性。基本机制与对警戒连续体作为某些心理状态的行为代谢测量的实验性解释有关。我们从古典头皮上侵扰感应器(OEG)的意义上,我们给出的测量方法,完全依赖基于现代相机的实时实时信号处理和计算机视觉。根据作为面部动态一致性的随机代表,反映情感表达中的血膜不对称,我们展示了病人与健康控制之间的几乎无懈可击的区别,以及精神失常抑郁和精神分裂症与精神分裂症和症状严重程度之间的几乎没有瑕疵的区别。与标准的诊断过程相比,该过程耗时、主观且不包含神经生物学数据,如实时面部动态,影响反应的客观透析模型只需要几分钟的视频面部位记录。我们还强调了该方法作为诊断模型在预测50个临床控制病人结果的跨诊断分析结果和50个临床治疗结果方面的因果关系模型的潜力。所有结果都是通过100个临床控制数据采集的。