基于功能性近红外光谱技术识别情绪状态 下载: 679次
姜劲, 焦学军, 潘津津, 张朕, 曹勇, 肖毅. 基于功能性近红外光谱技术识别情绪状态[J]. 光学学报, 2016, 36(3): 0317002.
Jiang Jin, Jiao Xuejun, Pan Jinjin, Zhang Zhen, Cao Yong, Xiao Yi. Emotional State Recognition Based on Functional Near-Infrared Spectroscopy[J]. Acta Optica Sinica, 2016, 36(3): 0317002.
[1] Tuscan L A, Herbert J D, Forman E M, et al.. Exploring frontal asymmetry using functional near-infrared spectroscopy: A preliminary study of the effects of social anxiety during interaction and performance tasks[J]. Brain Imaging & Behavior, 2013, 7(2): 140-153.
[2] Boas D A, Elwell C E, Ferrari M, et al.. Twenty years of functional near-infrared spectroscopy: Introduction for the special issue[J]. NeuroImage, 2014, 85(2): 1-5.
[3] Ferrari M, Quaresima V. A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application[J]. NeuroImage, 2012, 63(2): 921-935.
[4] Doi H, Nishitani S, Shinohara K. NIRS as a tool for assaying emotional function in the prefrontal cortex[J]. Frontiers in Human Neuroscience, 2013, 7(1): 56-67.
[5] Davidson R J, Putnam K M, Larson C L. Dysfunction in the neural circuitry of emotion regulation — a possible prelude to violence[J]. Science, 2000, 289(5479): 591-594.
[6] Balconi M, Lucchiari C. Consciousness and arousal effects on emotional face processing as revealed by brain oscillations. A gamma band analysis[J]. International Journal of Psychophysiology, 2008, 67(1): 41-46.
[7] Balconi M, Grippa E, Vanutelli M E. What hemodynamic (fNIRS), electrophysiological (EEG) and autonomic integrated measures can tell us about emotional processing[J]. Brain & Cognition, 2015, 95: 67-76.
[8] 熊洋, 司民真, 高飞, 等. 基于NIR-SERS光谱技术分析宫颈癌氧合血红蛋白[J]. 中国激光, 2015, 42(1): 0115001.
[9] 张永, 陈斌, 李东. 一种模拟生物组织内光传播的三维几何蒙特卡洛方法[J]. 中国激光, 2015, 42(1): 0104003.
[10] 吴春阳, 卢启鹏, 丁海泉, 等. 利用人体组织液进行近红外无创血糖测量[J]. 光学学报, 2013, 33(11): 1117001.
[11] Hoshi Y, Huang J, Kohri S, et al.. Recognition of human emotions from cerebral blood flow changes in the frontal region: A study with event-related near-infrared spectroscopy[J]. Journal of Neuroimaging, 2009, 21(2): 94-101.
[12] 潘津津, 焦学军, 焦典, 等. 利用功能性近红外光谱法研究大脑皮层血氧情况随任务特征变化规律[J]. 光学学报, 2015, 35(8): 0817001.
[13] Dieler A C, Plichta M M, Sler T, et al.. Suppression of emotional words in the Think/No-Think paradigm investigated with functional near-infrared spectroscopy[J]. International Journal of Psychophysiology, 2010, 78(2): 129-135.
[14] Sourina O, Wang Q, Liu Y, et al.. A real-time fractal-based brain state recognition from EEG and its applications[C]. Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing, Rome, 2011: 82-90.
[15] Lischke A, Berger C, Prehn K, et al.. Intranasal oxytocin enhances emotion recognition from dynamic facial expressions and leaves eyegaze unaffected[J]. Psychoneuroendocrinology, 2012, 37(4): 475-481.
[16] Khalili Z, Moradi M H. Emotion recognition system using brain and peripheral signals: Using correlation dimension to improve the results of EEG[C]. IEEE International Joint Conference on Neural Networks, 2009: 1571-1575.
[17] Hoshi Y, Huang J, Kohri S, et al.. Recognition of human emotions from cerebral blood flow changes in the frontal region: A study with event-related near-infrared spectroscopy[J]. Journal of Neuroimaging, 2009, 21(2): 94-101.
[18] Liu Y, Sourina O, Nguyen M K. Real-time EEG-based emotion recognition and its applications[M]. //Transactions on Computational Science XII, 2011, 6670: 256-277.
[19] Lang P J, Bradley M M, Cuthbert B N. International affective picture system (IAPS): Affective ratings of pictures and instruction manual [R]. University of Florida, 2008, Technical Report A-8.
[20] Bradley M M, Lang P J. Measuring emotion: The self-assessment manikin and the semantic differential[J]. Journal of Behavior Therapy & Experimental Psychiatry, 1994, 25(1): 49-59.
[21] Hu T Y, Xie X, Li J. Negative or positive The effect of emotion and mood on risky driving[J]. Transportation Research Part F: Traffic Psychology & Behaviour, 2013, 16: 29-40.
[22] Jeon M, Walker B N, Yim J B. Effects of specific emotions on subjective judgment, driving performance, and perceived workload[J]. Transportation Research Part F: Traffic Psychology & Behaviour, 2014, 24: 197-209.
[23] Kirilina E, Jelzow A, Heine A, et al.. The physiological origin of task-evoked systemic artefacts in functional near infrared spectroscopy [J]. NeuroImage, 2012, 61(1): 70-81.
[24] 潘津津, 焦学军, 姜劲, 等. 利用功能性近红外光谱成像方法评估脑力负荷[J]. 光学学报, 2014, 34(11): 1130002.
[25] Haeussinger F B, Sler T, Heinzel S, et al.. Reconstructing functional near-infrared spectroscopy (fNIRS) signals impaired by extra-cranial confounds: An easy-to-use filter method[J]. NeuroImage, 2014, 95(8): 69-79.
[26] Cui X, Bray S, Reiss A L. Functional near infrared spectroscopy (NIRS) signal improvement based on negative correlation between oxygenated and deoxygenated hemoglobin dynamics[J]. NeuroImage, 2010, 49(4): 3039-3046.
[27] 周振宇, 杨宏宇, 龚辉, 等. 基于希尔伯特黄变换的近红外脑功能成像信号分析[J]. 光学学报, 2007, 27(2): 307-312.
[28] 彭明金, 李智. 基于希尔伯特-黄变换的激光微多普勒信号分析与特征提取[J]. 中国激光, 2013, 40(8): 0809004.
[29] 许露. 基于SVM-RFE 和粒子群算法的特征选择算法研究[D]. 长沙:湖南师范大学, 2014: 63-75.
Xu Lu. A Study on Feature Selection Algorithm based on SVM-RFE and Particle Swarm Optimization[D]. Changsha: Hunan Normal University, 2014: 63-75.
[30] Naseer N, Hong K S. Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain-computer interface[J]. Neuroscience Letters, 2013, 553(8): 84-89.
[31] Kaiser V, Bauernfeind G, Kreilinger A, et al.. Cortical effects of user training in a motor imagery based brain-computer interface measured by fNIRS and EEG[J]. NeuroImage, 2014, 85(1): 432-444.
姜劲, 焦学军, 潘津津, 张朕, 曹勇, 肖毅. 基于功能性近红外光谱技术识别情绪状态[J]. 光学学报, 2016, 36(3): 0317002. Jiang Jin, Jiao Xuejun, Pan Jinjin, Zhang Zhen, Cao Yong, Xiao Yi. Emotional State Recognition Based on Functional Near-Infrared Spectroscopy[J]. Acta Optica Sinica, 2016, 36(3): 0317002.