Emotion recognition from surface EMG signal using wavelet transform and neural network

2nd International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2008

Volumn , Issue , 2008, Pages 1363-1366

  Cheng, Bo ^a   Liu, Guangyuan ^b  

^a CHONGQING THREE GORGES UNIVERSITY   (China)

^b SOUTHWEST UNIVERSITY   (China)

Author keywords

Affective computing; BP Neural Network; EMG; Emotion recognition; Wavelet transform

Indexed keywords

BACKPROPAGATION ALGORITHMS; BIOCOMMUNICATIONS; BIOINFORMATICS; BIOMEDICAL ENGINEERING; COMPUTER NETWORKS; DISCRETE WAVELET TRANSFORMS; FACE RECOGNITION; IMAGE CLASSIFICATION; INFORMATION SCIENCE; NEURAL NETWORKS; SIGNAL PROCESSING;

AFFECTIVE COMPUTING; BP NEURAL NETWORK; EMG; EMOTION RECOGNITION; WAVELET TRANSFORM;

WAVELET TRANSFORMS;

EID: 50949116891     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICBBE.2008.670     Document Type: Conference Paper

References (14)

1. Sen-lin LUO , Li-min PAN. Theory and Technology on Affctive Computing[J].Systems Engineering and Electronics,2003, 25(7): 905-909.(In Chinese)
2. Guo-liang YANG, Zhi-liang WANG. A Survey of Affective Modeling[J].Techniques of Automation and Applications, 2004, 23(11):1-4.(In Chinese)
3. R Picard. Affective Computing[R].Perceptual Computing Technical Report, 1995, 8:321.
4. R Picard. Affective Computing [M].MIT Press, London, England, 1997.68.
5. Jing Zhai Barreto, A. Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables.Digital Signal Process. Proceedings of the 28th IEEE EMBS Annual International Conference New York City, USA,2006,8:1355-1358.
6. E Leon, G Clarke, F Sepulveda, V Callaghan. Optimised attribute selection for emotion classification using physiological signals. Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE, 2004, 1:184-187.
7. Ark, W, Dryer, D. C., and Lu, D. J. The emotion mouse, 8th Int. Conf. Human-computer Interaction, (1999) 453-458.
8. R W Picard, E V Yzas, J Healey. Toward Machine Emotional Intelligence: Analysis of Affective Physiological State [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001,23(10): 1175-1191.
9. K H Kim, S W Bang, S R Kim. Emotion Recognition System Using Short-term Monitoring of Physiological Signals [J]. Med Boil Eng Comput,2004,42:419-427.
10. ChungK Lee, SK Yoo, YoonJ Park, NamHyun Kim, KeeSam Jeong, ByungChae Lee. Using Neural Network to Recognize Human Emotions from Heart Rate Variability and Skin Resistance. Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference Shanghai, China, September 1-4,2005, 5523-5525.
11. Wagner J, Kim J, André E. From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification [J]. IEEE International Conference on Multimedia & Expo (ICME 2005).
12. D W Marquardt, An algorithm for least squares estimation of nonlinear parameters, J. Soc. Ind. Appl. Math. 11 (2) (1963) 431-441.
13. E Shwedyk, Etal.A Nonstationary Model for the Electromyogram. IEEE TransBiomed Eng,1977,24: 417-424.
14. R Reed, Pruning algorithms - a survey, IEEE Trans. Neural Networks 4 (5) (1993) 740-746.