Department of Biomedical Engineering, School of Biological Sciences, The University of Reading, Reading RG6 6AY, UK.
Biosensors (Basel). 2018 Mar 24;8(2):30. doi: 10.3390/bios8020030.
The present research proposes a novel emotion recognition framework for the computer prediction of human emotions using common wearable biosensors. Emotional perception promotes specific patterns of biological responses in the human body, and this can be sensed and used to predict emotions using only biomedical measurements. Based on theoretical and empirical psychophysiological research, the foundation of autonomic specificity facilitates the establishment of a strong background for recognising human emotions using machine learning on physiological patterning. However, a systematic way of choosing the physiological data covering the elicited emotional responses for recognising the target emotions is not obvious. The current study demonstrates through experimental measurements the coverage of emotion recognition using common off-the-shelf wearable biosensors based on the synchronisation between audiovisual stimuli and the corresponding physiological responses. The work forms the basis of validating the hypothesis for emotional state recognition in the literature and presents coverage of the use of common wearable biosensors coupled with a novel preprocessing algorithm to demonstrate the practical prediction of the emotional states of wearers.
本研究提出了一种新颖的情感识别框架，使用常见的可穿戴生物传感器来预测人类的情感。情感感知会促进人体产生特定的生物反应模式，而这些模式可以通过仅使用生物医学测量来感知和预测情感。基于理论和经验心理生理学研究，自主特异性的基础为使用机器学习对生理模式进行识别，从而为人类情感识别建立了强大的背景。然而，选择涵盖诱发情感反应的生理数据以识别目标情感的系统方法并不明显。本研究通过实验测量证明了使用常见的现成可穿戴生物传感器进行情感识别的覆盖范围，这些传感器基于视听刺激与相应的生理反应之间的同步。这项工作为文献中情感状态识别的假设提供了验证，并展示了常见可穿戴生物传感器的使用范围，以及一种新颖的预处理算法，以证明佩戴者情感状态的实际预测。
