Real-time Analysis of Heart Rate Variability for a Mobile Human Emotion Recognition System

Chairman: Shih-Chung ChenPresenter: Chung-Yi LiAdvisor: Dr. Chun-Ju HouDate:2015/10/7

JUN JO, YONGKWI LEE, and HYUN SOON SHIN Recent Advances in Electrical and Computer Engineering,2013

OutlineIntroductionSystem DescriptionAnalytic IssueComputational ResultsConclusionReferences

IntroductionHuman 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.

IntroductionThe 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.

IntroductionDeveloped a wristwatch-type PPG sensor

module for a mobile emotion recognition system.

System DescriptionA wristwatch-type PPG sensor module

PPG, GSR, Skin Temperature, HumidityAnalog-to-digital converter

Sampling rate: 200HzResolution: 12 bits

An embedded DSP moduleNoise filtering: 5Hz FIR low-pass soft filterPPG peak detectionReal-time FFT

ConclusionRRI 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.

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.

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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.

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