Institute of Biomedical Engineering, University of Toronto, Toronto, ON, Canada.
KITE Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, ON, Canada.
J Neuroeng Rehabil. 2023 Aug 15;20(1):107. doi: 10.1186/s12984-023-01217-5.
Anger dyscontrol is a common issue after traumatic brain injury (TBI). With the growth of wearable physiological sensors, there is new potential to facilitate the rehabilitation of such anger in the context of daily life. This potential, however, depends on how well physiological markers can distinguish changing emotional states and for such markers to generalize to real-world settings. Our study explores how wearable photoplethysmography (PPG), one of the most widely available physiological sensors, could be used detect anger within a heterogeneous population.
This study collected the TRIEP (Toronto Rehabilitation Institute Emotion-Physiology) dataset, which comprised of 32 individuals (10 TBI), exposed to a variety of elicitation material (film, pictures, self-statements, personal recall), over two day sessions. This complex dataset allowed for exploration into how the emotion-PPG relationship varied over changes in individuals, endogenous/exogenous drivers of emotion, and day-to-day differences. A multi-stage analysis was conducted looking at: (1) times-series visual clustering, (2) discriminative time-interval features of anger, and (3) out-of-sample anger classification.
Characteristics of PPG are largely dominated by inter-subject (between individuals) differences first, then intra-subject (day-to-day) changes, before differentiation into emotion. Both TBI and non-TBI individuals showed evidence of linear separable features that could differentiate anger from non-anger classes within time-interval analysis. However, what is more challenging is that these separable features for anger have various degrees of stability across individuals and days.
This work highlights how there are contextual, non-stationary challenges to the emotion-physiology relationship that must be accounted for before emotion regulation technology can perform in real-world scenarios. It also affirms the need for a larger breadth of emotional sampling when building classification models.
愤怒失控是创伤性脑损伤（TBI）后的常见问题。随着可穿戴生理传感器的发展，在日常生活中为这种愤怒的康复提供新的潜力。然而，这种潜力取决于生理标记物在多大程度上能够区分不断变化的情绪状态，以及这些标记物在多大程度上能够推广到真实环境中。我们的研究探讨了可穿戴光电容积脉搏波（PPG）作为最广泛使用的生理传感器之一，如何在异质人群中检测愤怒。
本研究收集了多伦多康复研究所情绪生理（TRIEP）数据集，该数据集由 32 名个体（10 名 TBI）组成，他们在两天的时间里暴露于各种诱发材料（电影、图片、自我陈述、个人回忆）中。这个复杂的数据集允许探索情绪-PPG 关系如何随个体、情绪的内源性/外源性驱动因素以及日常差异而变化。进行了多阶段分析，研究了：（1）时间序列视觉聚类，（2）愤怒的判别时间间隔特征，（3）样本外愤怒分类。
PPG 的特征主要首先由个体间（个体之间）差异主导，然后是个体内（每日）变化，然后才分化为情绪。TBI 和非 TBI 个体都表现出线性可分离特征的证据，这些特征可在时间间隔分析中区分愤怒和非愤怒类。然而，更具挑战性的是，这些愤怒的可分离特征在个体和天数之间具有不同程度的稳定性。
这项工作强调了情绪-生理关系存在上下文、非平稳性挑战，在情绪调节技术能够在现实场景中发挥作用之前，必须对这些挑战进行考虑。它还肯定了在构建分类模型时需要更广泛的情感采样。
