基于脑电信号评价情绪状态及听觉激励对改善情绪的研究
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国家自然科学青年基金(61501431)


Evaluation of emotional state based on EEG signals and improving emotionsby auditory stimulation
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    摘要:

    如何从脑活动数据中发现具有生物学意义的知识及规律,正成为当今神经信息学理论与实践研究的热点与难点.基于脑电的情绪识别和情绪及其脑机制的关联研究已经成为神经工程和生物医学工程领域的热门课题.本研究基于脑电信号评价情绪状态,尝试借助脑电耳机来监测"毫无头绪"的脑电波,重点开展了听觉激励对改善焦虑情绪状态的实验研究.借助特定中国古风纯音乐产生听觉信号激励,激发出被试者平静放松的情绪状态,从而改善焦虑,发现音乐和情绪之间可能存在的关系.将来在BCI技术研究的基础之上,情绪识别可以进一步满足患有特定疾病(ALS症、脑瘫、脑干中风、脊髓损伤等)的患者人群的某些更高级的需求,即通过脑电分析出其对事物的喜好度,比如音乐的选择,从而设计出更加友善和智能的BCI系统,在医疗康复领域具有很好的应用前景.

    Abstract:

    Identification of biological significance using brain activity data is a research hotspot in neuroscience theory and practice.The emotional recognition and study of the correlation between emotions and brain mechanisms based on electroencephalograms (EEGs) are important topics in the fields of neuroscience and biomedical engineering.In this study,the emotional state of a subject was evaluated using EEG signalscollected using the MindWave Mobile 2EEG headphone,and the "clueless" mind wave was monitored as well.An experimental study on improving the state of anxiety by auditory excitation was conducted.Auditory signal stimulation was achieved with specific antique Chinese pure music sets,which stimulated the emotional state of calm relaxation in the subjects.Thus,their anxiety was reduced,and the possible relationship between music and emotion was derived.In the future,brain-computer interface (BCI) technology can help meet the more advanced emotional recognition needs of patients with specific diseases (such as ALS,cerebral palsy,brainstem stroke,and spinal cord injury) via EEG analysis of their preferences for aspects such as choice of music.Thus,a more user-friendly and intelligent BCI system,with good application prospects in the field of medical rehabilitation,could be designed.

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王慧,邱义波,骆永乐.基于脑电信号评价情绪状态及听觉激励对改善情绪的研究[J].南京信息工程大学学报(自然科学版),2019,11(2):158-164
WANG Hui, QIU Yibo, LUO Yongle. Evaluation of emotional state based on EEG signals and improving emotionsby auditory stimulation[J]. Journal of Nanjing University of Information Science & Technology, 2019,11(2):158-164

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  • 收稿日期:2019-03-02
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  • 在线发布日期: 2019-04-25
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