A Wearable In-Ear EEG Device for Emotion Monitoring
A Wearable In-Ear EEG Device for Emotion Monitoring
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DOI：
10.3390/s19184014
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发表时间：
2019-09-02
期刊：
影响因子：
3.9
通讯作者：
Israsena, Pasin
中科院分区：
文献类型：
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作者：
Athavipach, Chanavit;Pan-ngum, Setha;Israsena, Pasin
未来的医疗保健应用越来越多地转向院外或家庭护理模式，因此远程、持续有效地监测患者状况的能力是必不可少的。其中，情绪状态是医生或护理人员可能感兴趣的条件之一。本文讨论了开发一种低成本、单通道、干接触、适合非侵入式监测的耳内式脑电图可穿戴设备的初步研究。通过应用机器学习进行情感分类，涵盖了设计，工程和实验的各个方面。基于效价和唤醒情绪模型的基本情绪分类准确率分别为71.07%（效价）、72.89%（唤醒）和53.72%（全部四种情绪）。结果与在T7和T8头皮位置使用更传统的脑电图耳机所测得的结果相当。这些结果，再加上它类似耳机的可穿戴性，表明了它的潜在用途，特别是在未来的医疗保健应用中，如预期的家庭或远程监控系统。
For future healthcare applications, which are increasingly moving towards out-of-hospital or home-based caring models, the ability to remotely and continuously monitor patients' conditions effectively are imperative. Among others, emotional state is one of the conditions that could be of interest to doctors or caregivers. This paper discusses a preliminary study to develop a wearable device that is a low cost, single channel, dry contact, in-ear EEG suitable for non-intrusive monitoring. All aspects of the designs, engineering, and experimenting by applying machine learning for emotion classification, are covered. Based on the valence and arousal emotion model, the device is able to classify basic emotion with 71.07% accuracy (valence), 72.89% accuracy (arousal), and 53.72% (all four emotions). The results are comparable to those measured from the more conventional EEG headsets at T7 and T8 scalp positions. These results, together with its earphone-like wearability, suggest its potential usage especially for future healthcare applications, such as home-based or tele-monitoring systems as intended.