Escuela Politécnica Nacional, Facultad de Ingeniería de Sistemas, Departamento de Informática y Ciencias de la Computación, Quito, Ecuador.
Pontificia Universidad Católica del Ecuador; Quito, Ecuador.
Sensors (Basel). 2020 Sep 7;20(18):5083. doi: 10.3390/s20185083.
Affecting computing is an artificial intelligence area of study that recognizes, interprets, processes, and simulates human affects. The user's emotional states can be sensed through electroencephalography (EEG)-based Brain Computer Interfaces (BCI) devices. Research in emotion recognition using these tools is a rapidly growing field with multiple inter-disciplinary applications. This article performs a survey of the pertinent scientific literature from 2015 to 2020. It presents trends and a comparative analysis of algorithm applications in new implementations from a computer science perspective. Our survey gives an overview of datasets, emotion elicitation methods, feature extraction and selection, classification algorithms, and performance evaluation. Lastly, we provide insights for future developments.
情感计算是人工智能研究的一个领域，旨在识别、解释、处理和模拟人类的情感。通过基于脑电图（EEG）的脑机接口（BCI）设备可以感知用户的情绪状态。使用这些工具进行情感识别的研究是一个快速发展的领域，具有多种跨学科的应用。本文对 2015 年至 2020 年的相关科学文献进行了调查。从计算机科学的角度介绍了新实现中算法应用的趋势和比较分析。我们的调查概述了数据集、情感激发方法、特征提取和选择、分类算法以及性能评估。最后，我们为未来的发展提供了一些见解。
