1. Chairman: Shih-Chung Chen Presenter: Chung-Yi Li Advisor: Dr. Chun-Ju Hou Date:2015/10/7 JUN JO, YONGKWI LEE, and HYUN SOON SHIN Recent Advances in Electrical and Computer Engineering,2013

2. Outline Introduction System Description Analytic Issue Computational Results Conclusion References

3. Introduction Human emotion recognition has been studied long time. Brain wave has been considered as a most suitable bio-signal for emotion recognition; but the acquisition of brain wave with EEG is difficult and not adequate to mobile environment.

4. Introduction The cardio signal is a proper alternative. Since the cardio signal is usually acquired from ECG, we have employed PPG sensor in order to promote user convenience.

5. Introduction Developed a wristwatch-type PPG sensor module for a mobile emotion recognition system.

6. System Description A wristwatch-type PPG sensor module PPG, GSR, Skin Temperature, Humidity Analog-to-digital converter Sampling rate: 200Hz Resolution: 12 bits An embedded DSP module Noise filtering: 5Hz FIR low-pass soft filter PPG peak detection Real-time FFT

7. Conclusion RRI sampling rate and the number of FFT points results good performance in real-time HRV analysis. Increase in FFT points employing zero-padding is not recommendable. There remains a study of proof that real-time HRV is able to reflect human emotion properly.

8. References [1] Y. Lee, H.S. Shin, and J. Jo, “Development of a PPG array sensor module”, Proc. Institute of Electronics Engineers of Korea (IEEK) Summer Conference, Seoul, Korea, 2010, pp.1368-1370. [2] Y. Lee, H.S. Shin, J. Jo, and Y-K. Lee, “Development of a Wristwatch-Type PPG Array Sensor Module”, Proc. IEEE ICCE-Berlin, 2011, pp.170-173. [3] Y-K. Lee, O-W. Kwon, H.S. Shin, J. Jo, and Y. Lee, “Noise reduction of PPG signals using a particle filter for robust emotion recognition”, Proc. IEEE ICCE- Berlin, 2011, pp.202-205. [4] Y-K. Lee, J. Jo, Y. Lee, H.S. Shin, and O-W. Kwon, ‘Particle Filter-Based Noise Reduction of PPG Signals for Robust Emotion Recognition”, Proc. IEEE ICCE2012, USA, 2012, pp.602-603. [5] Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, “Heart rate variability”, European Heart Journal, vol. 17, 1996, pp.354-381.

9. References [6] BM. Appelhans, LJ. Luecken, “Heart rate variability as an index of regulated emotional responding”, Rev Gen Psychol vol. 10, 2006, pp.229–240. [7] F. Riganello, A. Candelieri et al., “Heart rate variability: An index of brain processing in vegetative state? A artificial intelligence, data mining study”, Clinical Neurophysiology, vol. 121, 2010, pp. 2024-2034. [8] P. Janssen, “Lactate Threshold Training”, Human Kinetics Publishers, 2001.

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