Literature DB >> 17281504

Using neural network to recognize human emotions from heart rate variability and skin resistance.

Chung Lee1, S K Yoo, Yoonj Park, Namhyun Kim, Keesam Jeong, Byungchae Lee.   

Abstract

The purpose of this paper is to estimate emotions using Neural network and the changes in activities of autonomic nervous system(ANS). Since ANS cannot be controlled artificially, we presumed that the changes in emotions would be reflected to the changes in ANS. In order to observe those changes, we provided the subjects with some video clips which can induce a variety of emotions and measured the changes in ANS, especially in Heart Rate Variability(HRV) and in Galvanic Skin Response(GSR). With those analyzed results from the experiments, we established an algorithm based on Neural network, finally we could reach the estimating rate of 80.2%

Entities:  

Year:  2005        PMID: 17281504     DOI: 10.1109/IEMBS.2005.1615734

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  10 in total

1.  Measuring the sympathetic skin response on body and using as diagnosis-purposed for lung cancer patients by artificial neural networks.

Authors:  Ozhan Ozkan; Murat Yildiz; Süleyman Bilgin; Etem Köklükaya
Journal:  J Med Syst       Date:  2010-06       Impact factor: 4.460

2.  The correlation of laboratory tests and Sympathetic Skin Response parameters by using artificial neural networks in fibromyalgia patients.

Authors:  Ozhan Ozkan; Murat Yildiz; Etem Köklükaya
Journal:  J Med Syst       Date:  2011-01-05       Impact factor: 4.460

3.  EEG and autonomic responses during performance of matching and non-matching to sample working memory tasks with emotional content.

Authors:  Ana Garcia; Carlos Enrique Uribe; Maria Clotilde H Tavares; Carlos Tomaz
Journal:  Front Behav Neurosci       Date:  2011-12-21       Impact factor: 3.558

4.  Frequency Band Analysis of Electrocardiogram (ECG) Signals for Human Emotional State Classification Using Discrete Wavelet Transform (DWT).

Authors:  Murugappan Murugappan; Subbulakshmi Murugappan; Bong Siao Zheng
Journal:  J Phys Ther Sci       Date:  2013-08-20

5.  Autonomic nervous system responses can reveal visual fatigue induced by 3D displays.

Authors:  Chi Jung Kim; Sangin Park; Myeung Ju Won; Mincheol Whang; Eui Chul Lee
Journal:  Sensors (Basel)       Date:  2013-09-26       Impact factor: 3.576

6.  A Wrapper Feature Selection Algorithm: An Emotional Assessment Using Physiological Recordings from Wearable Sensors.

Authors:  Inma Mohino-Herranz; Roberto Gil-Pita; Joaquín García-Gómez; Manuel Rosa-Zurera; Fernando Seoane
Journal:  Sensors (Basel)       Date:  2020-01-06       Impact factor: 3.576

7.  Physiological Sensors Based Emotion Recognition While Experiencing Tactile Enhanced Multimedia.

Authors:  Aasim Raheel; Muhammad Majid; Majdi Alnowami; Syed Muhammad Anwar
Journal:  Sensors (Basel)       Date:  2020-07-21       Impact factor: 3.576

8.  Heart Rate Information-Based Machine Learning Prediction of Emotions Among Pregnant Women.

Authors:  Xue Li; Chiaki Ono; Noriko Warita; Tomoka Shoji; Takashi Nakagawa; Hitomi Usukura; Zhiqian Yu; Yuta Takahashi; Kei Ichiji; Norihiro Sugita; Natsuko Kobayashi; Saya Kikuchi; Yasuto Kunii; Keiko Murakami; Mami Ishikuro; Taku Obara; Tomohiro Nakamura; Fuji Nagami; Takako Takai; Soichi Ogishima; Junichi Sugawara; Tetsuro Hoshiai; Masatoshi Saito; Gen Tamiya; Nobuo Fuse; Shinichi Kuriyama; Masayuki Yamamoto; Nobuo Yaegashi; Noriyasu Homma; Hiroaki Tomita
Journal:  Front Psychiatry       Date:  2022-01-27       Impact factor: 4.157

9.  Assessment of Mental, Emotional and Physical Stress through Analysis of Physiological Signals Using Smartphones.

Authors:  Inma Mohino-Herranz; Roberto Gil-Pita; Javier Ferreira; Manuel Rosa-Zurera; Fernando Seoane
Journal:  Sensors (Basel)       Date:  2015-10-08       Impact factor: 3.576

10.  Emotion recognition from multichannel EEG signals using K-nearest neighbor classification.

Authors:  Mi Li; Hongpei Xu; Xingwang Liu; Shengfu Lu
Journal:  Technol Health Care       Date:  2018       Impact factor: 1.285

  10 in total

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