Physiological-signal-based emotion recognition: An odyssey from methodology to philosophy

[1]  Luca Romeo,et al.  Multiple Instance Learning for Emotion Recognition Using Physiological Signals , 2022, IEEE Transactions on Affective Computing.

[2]  Huiguang He,et al.  Multisource Transfer Learning for Cross-Subject EEG Emotion Recognition , 2020, IEEE Transactions on Cybernetics.

[3]  S. Goel,et al.  Emotion recognition using fourier transform and genetic programming , 2020 .

[4]  Changde Du,et al.  Domain Adaptation for EEG Emotion Recognition Based on Latent Representation Similarity , 2020, IEEE Transactions on Cognitive and Developmental Systems.

[5]  Fatma Patlar Akbulut,et al.  Bimodal affect recognition based on autoregressive hidden Markov models from physiological signals , 2020, Comput. Methods Programs Biomed..

[6]  Yonghong Tan,et al.  Strengthen EEG-based emotion recognition using firefly integrated optimization algorithm , 2020, Appl. Soft Comput..

[7]  Tong Zhang,et al.  Emotion Recognition From Multimodal Physiological Signals Using a Regularized Deep Fusion of Kernel Machine , 2020, IEEE Transactions on Cybernetics.

[8]  Chao Li,et al.  Exploring temporal representations by leveraging attention-based bidirectional LSTM-RNNs for multi-modal emotion recognition , 2020, Inf. Process. Manag..

[9]  Pradip Sircar,et al.  Automated emotion recognition based on higher order statistics and deep learning algorithm , 2020, Biomed. Signal Process. Control..

[10]  Dong-dong Li,et al.  EEG-based emotion recognition using simple recurrent units network and ensemble learning , 2020, Biomed. Signal Process. Control..

[11]  Yi Cao,et al.  EEG-Based Emotion Classification Using Spiking Neural Networks , 2020, IEEE Access.

[12]  Dongmei Jiang,et al.  Emotion recognition from spatiotemporal EEG representations with hybrid convolutional recurrent neural networks via wearable multi-channel headset , 2020, Comput. Commun..

[13]  Md. Foisal Hossain,et al.  Employing PCA and t-statistical approach for feature extraction and classification of emotion from multichannel EEG signal , 2020 .

[14]  Dong Keun Kim,et al.  The Design of CNN Architectures for Optimal Six Basic Emotion Classification Using Multiple Physiological Signals , 2020, Sensors.

[15]  Hyeran Byun,et al.  Subject-Independent EEG-based Emotion Recognition using Adversarial Learning , 2020, 2020 8th International Winter Conference on Brain-Computer Interface (BCI).

[16]  Qin Li,et al.  Wearable Emotion Recognition Using Heart Rate Data from a Smart Bracelet , 2020, Sensors.

[17]  Xiao-Nei Zhang,et al.  Odor-induced emotion recognition based on average frequency band division of EEG signals , 2020, Journal of Neuroscience Methods.

[18]  Mustafa E. Kamasak,et al.  Emotion Recognition from Multimodal Physiological Signals for Emotion Aware Healthcare Systems , 2020, Journal of Medical and Biological Engineering.

[19]  Yu-Liang Hsu,et al.  Automatic ECG-Based Emotion Recognition in Music Listening , 2020, IEEE Transactions on Affective Computing.

[20]  Mitul Kumar Ahirwal,et al.  Audio-visual stimulation based emotion classification by correlated EEG channels , 2019, Health and Technology.

[21]  Yuan Zong,et al.  Sparse Graphic Attention LSTM for EEG Emotion Recognition , 2019, ICONIP.

[22]  H. Byun,et al.  Learning CNN features from DE features for EEG-based emotion recognition , 2019, Pattern Analysis and Applications.

[23]  A. Goshvarpour,et al.  A Novel Approach for EEG Electrode Selection in Automated Emotion Recognition Based on Lagged Poincare’s Indices and sLORETA , 2019, Cognitive Computation.

[24]  Yong Zhang,et al.  Multi-Channel Physiological Signal Emotion Recognition Based on ReliefF Feature Selection , 2019, 2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS).

[25]  Haibin Wang,et al.  Research on EEG Channel Selection Method for Emotion Recognition , 2019, 2019 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[26]  A. Goshvarpour,et al.  The potential of photoplethysmogram and galvanic skin response in emotion recognition using nonlinear features , 2019, Physical and Engineering Sciences in Medicine.

[27]  K. R. Seeja,et al.  Subject independent emotion recognition from EEG using VMD and deep learning , 2019, J. King Saud Univ. Comput. Inf. Sci..

[28]  Xiao Huang,et al.  Individual Similarity Guided Transfer Modeling for EEG-based Emotion Recognition , 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[29]  Giancarlo Fortino,et al.  Human emotion recognition using deep belief network architecture , 2019, Inf. Fusion.

[30]  Jose L. Contreras-Vidal,et al.  Emotion Recognition by Point Process Characterization of Heartbeat Dynamics , 2019, 2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT).

[31]  Celia López-Ongil,et al.  Toward Fear Detection using Affect Recognition , 2019, 2019 XXXIV Conference on Design of Circuits and Integrated Systems (DCIS).

[32]  Rose T. Faghih,et al.  Facial Expression-Based Emotion Classification using Electrocardiogram and Respiration Signals , 2019, 2019 IEEE Healthcare Innovations and Point of Care Technologies, (HI-POCT).

[33]  Yazhou Zhang,et al.  Variational Autoencoder based Latent Factor Decoding of Multichannel EEG for Emotion Recognition , 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[34]  Jiaming Zhang,et al.  EEG Emotion Classification Using an Improved SincNet-Based Deep Learning Model , 2019, Brain sciences.

[35]  Hao Tang,et al.  Emotion Recognition using Multimodal Residual LSTM Network , 2019, ACM Multimedia.

[36]  Usman Akram,et al.  Emotion Charting Using Real-time Monitoring of Physiological Signals , 2019, 2019 International Conference on Robotics and Automation in Industry (ICRAI).

[37]  Wai-Chi Fang,et al.  An Edge AI System-on-Chip Design with Customized Convolutional-Neural-Network Architecture for Real-time EEG-Based Affective Computing System , 2019, 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS).

[38]  Kyung-Ah Sohn,et al.  An Exploration of Machine Learning Methods for Robust Boredom Classification Using EEG and GSR Data , 2019, Sensors.

[39]  Abdulmotaleb El Saddik,et al.  Toward User-Independent Emotion Recognition Using Physiological Signals , 2019, IEEE Sensors Journal.

[40]  M. Daliri,et al.  Statistical algorithms for emotion classification via functional connectivity. , 2019, Journal of integrative neuroscience.

[41]  Fuji Ren,et al.  Convolutional Neural Networks on EEG-Based Emotion Recognition , 2019, Big Data.

[42]  Minho Lee,et al.  ICA-Evolution Based Data Augmentation with Ensemble Deep Neural Networks Using Time and Frequency Kernels for Emotion Recognition from EEG-Data , 2019, IEEE Transactions on Affective Computing.

[43]  Mauridhi Hery Purnomo,et al.  Human Emotion Classification Based on EEG Signals Using Naïve Bayes Method , 2019, 2019 International Seminar on Application for Technology of Information and Communication (iSemantic).

[44]  Pasin Israsena,et al.  A Wearable In-Ear EEG Device for Emotion Monitoring , 2019, Sensors.

[45]  Anterpreet Kaur Bedi,et al.  Merged LSTM Model for emotion classification using EEG signals , 2019, 2019 International Conference on Data Science and Engineering (ICDSE).

[46]  T. Ganchev,et al.  Spectral Features of EEG Signals for the Automated Recognition of Negative Emotional States , 2019, 2019 IEEE XXVIII International Scientific Conference Electronics (ET).

[47]  Manolis Tsiknakis,et al.  A novel multi-kernel 1D convolutional neural network for stress recognition from ECG , 2019, 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW).

[48]  Sonali Agarwal,et al.  Classification of Physiological Signals for Emotion Recognition using IoT , 2019, 2019 6th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI).

[49]  Xingcong Zhao,et al.  Multi-method Fusion of Cross-Subject Emotion Recognition Based on High-Dimensional EEG Features , 2019, Front. Comput. Neurosci..

[50]  Yahui Zhang,et al.  Cross-Subject EEG-Based Emotion Recognition with Deep Domain Confusion , 2019, ICIRA.

[51]  Ren-Guey Lee,et al.  Artificial neural networks-based classification of emotions using wristband heart rate monitor data , 2019, Medicine.

[52]  Raini Hassan,et al.  Emotional profiling through supervised machine learning of interrupted EEG interpolation , 2019, International Journal of Advanced Computer Research.

[53]  F. Yang,et al.  Emotional State Classification using Pulse Rate Variability , 2019, 2019 IEEE 4th International Conference on Signal and Image Processing (ICSIP).

[54]  Jinpeng Li,et al.  EEG-Based Emotion Recognition with Similarity Learning Network , 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[55]  Gnana Keerthi Priya Veeramallu,et al.  EEG based automatic emotion recognition using EMD and Random forest classifier , 2019, 2019 10th International Conference on Computing, Communication and Networking Technologies (ICCCNT).

[56]  Benyamin Kusumoputro,et al.  The Back-propagation Neural Network Classification of EEG Signal Using Time Frequency Domain Feature Extraction , 2019, 2019 16th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering.

[57]  Yue Gao,et al.  Emotion Recognition from Physiological Signals using Multi-Hypergraph Neural Networks , 2019, 2019 IEEE International Conference on Multimedia and Expo (ICME).

[58]  Ibrahim Abe M. Elfadel,et al.  EEG-based Emotion Detection Using Unsupervised Transfer Learning , 2019, Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[59]  Jinpeng Li,et al.  EEG-Based Emotion Recognition with Prototype-Based Data Representation , 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[60]  Zhenqi Li,et al.  SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG , 2019, Front. Neurorobot..

[61]  Seyed Kamaledin Setarehdan,et al.  Emotion recognition through EEG phase space dynamics and Dempster-Shafer theory. , 2019, Medical hypotheses.

[62]  Yuan Ma,et al.  Intrinsic Prior Knowledge Driven CICA fMRI Data Analysis for Emotion Recognition Classification , 2019, IEEE Access.

[63]  Liuqing Yang,et al.  EEG-Based Emotion Recognition Using Temporal Convolutional Network , 2019, 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS).

[64]  Xiangmin Xu,et al.  A Convolutional Neural Network Feature Fusion Framework with Ensemble Learning for EEG-based Emotion Classification , 2019, 2019 IEEE MTT-S International Microwave Biomedical Conference (IMBioC).

[65]  Varun Bajaj,et al.  Emotion recognition from single-channel EEG signals using a two-stage correlation and instantaneous frequency-based filtering method , 2019, Comput. Methods Programs Biomed..

[66]  Sten Hanke,et al.  Emotion Recognition from Physiological Signal Analysis: A Review , 2019, BRAINS/WS-AFFIN@AmI.

[67]  Yue Wang,et al.  Heart sound signals can be used for emotion recognition , 2019, Scientific Reports.

[68]  C. Im,et al.  fNIRS Evidence for Recognizably Different Positive Emotions , 2019, Front. Hum. Neurosci..

[69]  Reddy Koya Jeevan,et al.  EEG-based emotion recognition using LSTM-RNN machine learning algorithm , 2019, 2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT).

[70]  Y. F. Huang,et al.  Accurate EEG-Based Emotion Recognition on Combined Features Using Deep Convolutional Neural Networks , 2019, IEEE Access.

[71]  Agata Manolova,et al.  ECG-Based Human Emotion Recognition Across Multiple Subjects , 2019, FABULOUS.

[72]  Ram Bilas Pachori,et al.  Cross-Subject Emotion Recognition Using Flexible Analytic Wavelet Transform From EEG Signals , 2019, IEEE Sensors Journal.

[73]  Arif Mahmood,et al.  Internal Emotion Classification Using EEG Signal With Sparse Discriminative Ensemble , 2019, IEEE Access.

[74]  Indronil Mazumder,et al.  An Analytical Approach of EEG Analysis for Emotion Recognition , 2019, 2019 Devices for Integrated Circuit (DevIC).

[75]  Luca Benini,et al.  Hyperdimensional Computing-based Multimodality Emotion Recognition with Physiological Signals , 2019, 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS).

[76]  Wenming Zheng,et al.  MPED: A Multi-Modal Physiological Emotion Database for Discrete Emotion Recognition , 2019, IEEE Access.

[77]  Masashi Sugiyama,et al.  ECG-Based Concentration Recognition With Multi-Task Regression , 2019, IEEE Transactions on Biomedical Engineering.

[78]  K. R. Seeja,et al.  Subject-Independent Emotion Detection from EEG Signals Using Deep Neural Network , 2018, International Conference on Innovative Computing and Communications.

[79]  Sapan H. Mankad,et al.  Emotion Recognition from Sensory and Bio-Signals: A Survey , 2018, Proceedings of the 2nd International Conference on Data Engineering and Communication Technology.

[80]  Kristof Van Laerhoven,et al.  Introducing WESAD, a Multimodal Dataset for Wearable Stress and Affect Detection , 2018, ICMI.

[81]  Aydin Akan,et al.  Emotion recognition based on time-frequency distribution of EEG signals using multivariate synchrosqueezing transform , 2018, Digit. Signal Process..

[82]  Sachin Taran,et al.  Emotion classification using flexible analytic wavelet transform for electroencephalogram signals , 2018, Health Information Science and Systems.

[83]  Enzo Pasquale Scilingo,et al.  Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors , 2018, Scientific Reports.

[84]  Atefeh Goshvarpour,et al.  Poincaré's section analysis for PPG-based automatic emotion recognition , 2018, Chaos, Solitons & Fractals.

[85]  Jian Shen,et al.  Emotion Recognition Based on Electroencephalogram Using a Multiple Instance Learning Framework , 2018, ICIC.

[86]  Humera Farooq,et al.  Multimodal Paradigm for Emotion Recognition Based on EEG Signals , 2018, HCI.

[87]  Mauridhi Hery Purnomo,et al.  Emotion Recognition in Elderly Based on SpO2 and Pulse Rate Signals Using Support Vector Machine , 2018, 2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS).

[88]  Deok-Hwan Kim,et al.  Inner Emotion Recognition Using Multi Bio-Signals , 2018, 2018 IEEE International Conference on Consumer Electronics - Asia (ICCE-Asia).

[89]  Zheng Li,et al.  Intersession Instability in fNIRS-Based Emotion Recognition , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[90]  Xiangmin Xu,et al.  WT Feature Based Emotion Recognition from Multi-channel Physiological Signals with Decision Fusion , 2018, 2018 First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia).

[91]  S. Soares,et al.  Biometric and Emotion Identification: An ECG Compression Based Method , 2018, Front. Psychol..

[92]  Stefan Winkler,et al.  ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors , 2018, IEEE Transactions on Affective Computing.

[93]  Zhigang Zhu,et al.  Emotion Analysis Using Audio/Video, EMG and EEG: A Dataset and Comparison Study , 2018, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).

[94]  V. Clemente-Suárez,et al.  Use of Psychophysiological Portable Devices to Analyse Stress Response in Different Experienced Soldiers , 2018, Journal of Medical Systems.

[95]  Satoshi Nakamura,et al.  Detecting suppression of negative emotion by time series change of cerebral blood flow using fNIRS , 2018, 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

[96]  Yan Liu,et al.  Data Augmentation for EEG-Based Emotion Recognition with Deep Convolutional Neural Networks , 2018, MMM.

[97]  Hyeoncheol Kim,et al.  Emotion extraction based on multi bio-signal using back-propagation neural network , 2018, Multimedia Tools and Applications.

[98]  Aydin Akan,et al.  Emotion recognition from EEG signals by using multivariate empirical mode decomposition , 2018, Pattern Analysis and Applications.

[99]  E. Schröger,et al.  Emotion lies in the eye of the listener: Emotional arousal to novel sounds is reflected in the sympathetic contribution to the pupil dilation response and the P3 , 2018, Biological Psychology.

[100]  Amit Konar,et al.  Music-Induced Emotion Classification from the Prefrontal Hemodynamics , 2017, PReMI.

[101]  C. L. Philip Chen,et al.  A novel ECG-based real-time detection method of negative emotions in wearable applications , 2017, 2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC).

[102]  K. N. Minhad,et al.  Happy-anger emotions classifications from electrocardiogram signal for automobile driving safety and awareness , 2017 .

[103]  Atefeh Goshvarpour,et al.  An accurate emotion recognition system using ECG and GSR signals and matching pursuit method , 2017, Biomedical journal.

[104]  Xianxiang Chen,et al.  Respiration-based emotion recognition with deep learning , 2017, Comput. Ind..

[105]  Vahab Youssofzadeh,et al.  An automated framework for emotional fMRI data analysis using covariance matrix , 2017, 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[106]  Zhenqi Li,et al.  Emotion Recognition from EEG Using RASM and LSTM , 2017, ICIMCS.

[107]  Javad Frounchi,et al.  Wavelet-based emotion recognition system using EEG signal , 2017, Neural Computing and Applications.

[108]  Ruoyu Du,et al.  Optimal Feature Selection and Deep Learning Ensembles Method for Emotion Recognition From Human Brain EEG Sensors , 2017, IEEE Access.

[109]  A. Goshvarpour,et al.  Fusion of heart rate variability and pulse rate variability for emotion recognition using lagged poincare plots , 2017, Australasian Physical & Engineering Sciences in Medicine.

[110]  Vangelis Metsis,et al.  Classification of Emotional Arousal During Multimedia Exposure , 2017, PETRA.

[111]  Chengyu Liu,et al.  Differences of Heart Rate Variability Between Happiness and Sadness Emotion States: A Pilot Study , 2017 .

[112]  Wanhui Wen,et al.  The Recognition and Classification of Stress Base on Pulse Transit Time Series , 2017, ICCDA '17.

[113]  Gokhan Ince,et al.  Emotion recognition from EEG signals through one electrode device , 2017, 2017 25th Signal Processing and Communications Applications Conference (SIU).

[114]  M. Dolphens,et al.  Brain changes associated with cognitive and emotional factors in chronic pain: A systematic review , 2017, European journal of pain.

[115]  Dongkyoo Shin,et al.  Development of emotion recognition interface using complex EEG/ECG bio-signal for interactive contents , 2017, Multimedia Tools and Applications.

[116]  Mary Helen Immordino‐Yang,et al.  The Brainstem in Emotion: A Review , 2017, Front. Neuroanat..

[117]  Miki Haseyama,et al.  Emotion estimation via tensor-based supervised decision-level fusion from multiple Brodmann areas , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[118]  Mauricio A. Álvarez,et al.  SVM-based feature selection methods for emotion recognition from multimodal data , 2016, Journal on Multimodal User Interfaces.

[119]  Tapio Seppänen,et al.  Emotion Recognition Using Neighborhood Components Analysis and ECG/HRV-Based Features , 2017, ICPRAM.

[120]  Ioannis Patras,et al.  AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups , 2017, IEEE Transactions on Affective Computing.

[121]  Ayoub Al-Hamadi,et al.  “BioVid Emo DB”: A multimodal database for emotion analyses validated by subjective ratings , 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

[122]  Mingyang Liu,et al.  Human Emotion Recognition Based on Galvanic Skin Response Signal Feature Selection and SVM , 2016, 2016 International Conference on Smart City and Systems Engineering (ICSCSE).

[123]  Miki Haseyama,et al.  Estimating human emotion evoked by visual stimuli using fMRI data , 2016, 2016 IEEE 5th Global Conference on Consumer Electronics.

[124]  Chien-Hung Lin,et al.  Heart Rate Variability Signal Features for Emotion Recognition by Using Principal Component Analysis and Support Vectors Machine , 2016, 2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE).

[125]  A. Hani,et al.  Mental stress assessment using simultaneous measurement of EEG and fNIRS. , 2016, Biomedical optics express.

[126]  Tapio Seppänen,et al.  Comparing features from ECG pattern and HRV analysis for emotion recognition system , 2016, 2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

[127]  Priyanka S. Ghare,et al.  Human emotion recognition using non linear and non stationary EEG signal , 2016, 2016 International Conference on Automatic Control and Dynamic Optimization Techniques (ICACDOT).

[128]  Senem Velipasalar,et al.  A More Complete Picture of Emotion Using Electrocardiogram and Electrodermal Activity to Complement Cognitive Data , 2016, HCI.

[129]  Kiran George,et al.  Bio-signal based emotion detection device , 2016, 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

[130]  A. Khasnobish,et al.  Emotion recognition employing ECG and GSR signals as markers of ANS , 2016, 2016 Conference on Advances in Signal Processing (CASP).

[131]  Heather T. Ma,et al.  Emotion recognition based on the multiple physiological signals , 2016, 2016 IEEE International Conference on Real-time Computing and Robotics (RCAR).

[132]  Shinichi Yoshida,et al.  Decoding of emotional visual stimuli using fMRI brain signal , 2016, 2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS).

[133]  S. Sowmiya,et al.  Emotion recognition from EEG signal using ISO-FLANN with firefly algorithm , 2016, 2016 International Conference on Communication and Signal Processing (ICCSP).

[134]  Alain Pruski,et al.  Multiresolution framework for emotion sensing in physiological signals , 2016, 2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP).

[135]  Zhen Gao,et al.  Emotion recognition from peripheral physiological signals enhanced by EEG , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[136]  Lipo Wang,et al.  Real-time EEG-based emotion monitoring using stable features , 2016, The Visual Computer.

[137]  Pei-Ying S. Chan,et al.  Being Anxious, Thinking Positively: The Effect of Emotional Context on Respiratory Sensory Gating , 2016, Front. Physiol..

[138]  Rosalind W. Picard,et al.  Multiple Arousal Theory and Daily-Life Electrodermal Activity Asymmetry , 2016 .

[139]  P. Unschuld,et al.  Huang Di Nei Jing Ling Shu Der Innere Klassiker des Gelben Thearchen , 2015, Deutsche Zeitschrift für Akupunktur.

[140]  Ali N. Akansu,et al.  Neural correlates of affective context in facial expression analysis: A simultaneous EEG-fNIRS study , 2015, 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[141]  Alain Pruski,et al.  Emotion recognition from physiological signals using fusion of wavelet based features , 2015, 2015 7th International Conference on Modelling, Identification and Control (ICMIC).

[142]  Abdul Wahab,et al.  Statistical Approach for a Complex Emotion Recognition Based on EEG Features , 2015, 2015 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT).

[143]  Hsiu-Sen Chiang,et al.  ECG-based Mental Stress Assessment Using Fuzzy Computing and Associative Petri Net , 2015 .

[144]  Ahmad R. Sharafat,et al.  Reliable emotion recognition system based on dynamic adaptive fusion of forehead biopotentials and physiological signals , 2015, Comput. Methods Programs Biomed..

[145]  Takashi Yamauchi,et al.  Dynamic time warping: A single dry electrode EEG study in a self-paced learning task , 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).

[146]  Emre Ertin,et al.  cStress: towards a gold standard for continuous stress assessment in the mobile environment , 2015, UbiComp.

[147]  Hyo Jong Lee,et al.  Deep learninig of EEG signals for emotion recognition , 2015, 2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW).

[148]  E. Salazar-López,et al.  The mental and subjective skin: Emotion, empathy, feelings and thermography , 2015, Consciousness and Cognition.

[149]  Subramanian Ramanathan,et al.  DECAF: MEG-Based Multimodal Database for Decoding Affective Physiological Responses , 2015, IEEE Transactions on Affective Computing.

[150]  Bao-Liang Lu,et al.  Investigating Critical Frequency Bands and Channels for EEG-Based Emotion Recognition with Deep Neural Networks , 2015, IEEE Transactions on Autonomous Mental Development.

[151]  Aravind E. Vijayan,et al.  EEG-Based Emotion Recognition Using Statistical Measures and Auto-Regressive Modeling , 2015, 2015 IEEE International Conference on Computational Intelligence & Communication Technology.

[152]  Fethi Bereksi-Reguig,et al.  Negative emotion detection using EMG signal , 2014, 2014 International Conference on Control, Decision and Information Technologies (CoDIT).

[153]  Abdelhak Moussaoui,et al.  Objective model assessment for short-term anxiety recognition from blood volume pulse signal , 2014, Biomed. Signal Process. Control..

[154]  Z. Yao,et al.  Discriminative analysis with a limited number of MEG trials in depression. , 2014, Journal of affective disorders.

[155]  Yong Peng,et al.  EEG-based emotion classification using deep belief networks , 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).

[156]  Wanhui Wen,et al.  Emotion Recognition Based on Multi-Variant Correlation of Physiological Signals , 2014, IEEE Transactions on Affective Computing.

[157]  Luca Citi,et al.  Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics , 2014, Scientific Reports.

[158]  W. Sommer,et al.  Facial EMG Responses to Emotional Expressions Are Related to Emotion Perception Ability , 2014, PloS one.

[159]  Chuan-Yu Chang,et al.  Physiological emotion analysis using support vector regression , 2013, Neurocomputing.

[160]  Sharifa Alghowinem,et al.  An exploratory study of detecting emotion states using eye-tracking technology , 2013, 2013 Science and Information Conference.

[161]  Hironobu Takano,et al.  Pupil Diameter Variation in Positive and Negative Emotions with Visual Stimulus , 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

[162]  Tanja Schultz,et al.  Continuous Recognition of Affective States by Functional Near Infrared Spectroscopy Signals , 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.

[163]  S.-H. Kim,et al.  The design of Fuzzy C-Means Clustering based neural networks for emotion classification , 2013, 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS).

[164]  Jianlin Mo,et al.  Emotion feature selection from physiological signals using tabu search , 2013, 2013 25th Chinese Control and Decision Conference (CCDC).

[165]  M. Murugappan,et al.  Classification of emotional states from electrocardiogram signals: a non-linear approach based on hurst , 2013, Biomedical engineering online.

[166]  Yoshua Bengio,et al.  Learning deep physiological models of affect , 2013, IEEE Computational Intelligence Magazine.

[167]  T. Kochiyama,et al.  Relationships among Facial Mimicry, Emotional Experience, and Emotion Recognition , 2013, PloS one.

[168]  Miyoung Kim,et al.  A Review on the Computational Methods for Emotional State Estimation from the Human EEG , 2013, Comput. Math. Methods Medicine.

[169]  M. Murugappan,et al.  Analysis of Electrocardiogram (ECG) Signals for Human Emotional Stress Classification , 2012, ICRA 2012.

[170]  Chuan-Yu Chang,et al.  Application of Support Vector Machine for Emotion Classification , 2012, 2012 Sixth International Conference on Genetic and Evolutionary Computing.

[171]  Paul Richard,et al.  Emotion assessment for affective computing based on physiological responses , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[172]  Byoung-Jun Park,et al.  Emotion classification based on physiological signals induced by negative emotions: Discriminantion of negative emotions by machine learning algorithm , 2012, Proceedings of 2012 9th IEEE International Conference on Networking, Sensing and Control.

[173]  Enzo Pasquale Scilingo,et al.  The Role of Nonlinear Dynamics in Affective Valence and Arousal Recognition , 2012, IEEE Transactions on Affective Computing.

[174]  H. Kessler,et al.  Repeatability of facial electromyography (EMG) activity over corrugator supercilii and zygomaticus major on differentiating various emotions , 2012, J. Ambient Intell. Humaniz. Comput..

[175]  Haruki Kawanaka,et al.  Classification of positive and negative emotion evoked by traffic jam based on electrocardiogram (ECG) and Pulse wave , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[176]  Javier Hernandez,et al.  Call Center Stress Recognition with Person-Specific Models , 2011, ACII.

[177]  Ludmila I. Kuncheva,et al.  Multi-modal biometric emotion recognition using classifier ensembles , 2011, IEA/AIE'11.

[178]  M. Murugappan Electromyogram signal based human emotion classification using KNN and LDA , 2011, 2011 IEEE International Conference on System Engineering and Technology.

[179]  Kil-sang Yoo,et al.  Mental stress assessment based on pulse photoplethysmography , 2011, 2011 IEEE 15th International Symposium on Consumer Electronics (ISCE).

[180]  F. B. Reguig,et al.  Analysis physiological signals for emotion recognition , 2011, International Workshop on Systems, Signal Processing and their Applications, WOSSPA.

[181]  M Murugappan,et al.  Physiological signals based human emotion Recognition: a review , 2011, 2011 IEEE 7th International Colloquium on Signal Processing and its Applications.

[182]  Sylvia D. Kreibig,et al.  Autonomic nervous system activity in emotion: A review , 2010, Biological Psychology.

[183]  Wanhui Wen,et al.  Construction and cross-correlation analysis of the affective physiological response database , 2010, Science China Information Sciences.

[184]  Wanhui Wen,et al.  Analysis of affective ECG signals toward emotion recognition , 2010 .

[185]  Guangyuan Liu,et al.  Extracting Emotional Features from ECG by Using Wavelet Transform , 2010, 2010 International Conference on Biomedical Engineering and Computer Science.

[186]  Rafael A. Calvo,et al.  Effect of Experimental Factors on the Recognition of Affective Mental States through Physiological Measures , 2009, Australasian Conference on Artificial Intelligence.

[187]  G. Colombetti From affect programs to dynamical discrete emotions , 2009 .

[188]  Mohammad Soleymani,et al.  Short-term emotion assessment in a recall paradigm , 2009, Int. J. Hum. Comput. Stud..

[189]  Jing Cai,et al.  The Research on Emotion Recognition from ECG Signal , 2009, 2009 International Conference on Information Technology and Computer Science.

[190]  Zahra Khalili,et al.  Emotion recognition system using brain and peripheral signals: Using correlation dimension to improve the results of EEG , 2009, 2009 International Joint Conference on Neural Networks.

[191]  Guang-yuan Liu,et al.  Feature Extraction, Feature Selection and Classification from Electrocardiography to Emotions , 2009, 2009 International Conference on Computational Intelligence and Natural Computing.

[192]  Cai Jing,et al.  Toward Recognizing Two Emotion States from ECG Signals , 2009, 2009 International Conference on Computational Intelligence and Natural Computing.

[193]  Yuan-Pin Lin,et al.  EEG-based emotion recognition in music listening: A comparison of schemes for multiclass support vector machine , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[194]  Wen Wan-Hui,et al.  Electrocardiography Recording, Feature Extraction and Classification for Emotion Recognition , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[195]  P. Jones,et al.  The I Ching: Points of Balance and Cycles of Change , 2008 .

[196]  J. Russell,et al.  The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology , 2005, Development and Psychopathology.

[197]  Johannes Wagner,et al.  From Physiological Signals to Emotions: Implementing and Comparing Selected Methods for Feature Extraction and Classification , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[198]  C. Chan,et al.  A Body-Mind-Spirit Model in Health , 2002, Social work in health care.

[199]  D. Ehling Oriental medicine: an introduction. , 2001, Alternative therapies in health and medicine.

[200]  H. Becher,et al.  Absolute Risk and Loss-of-Lifetime Estimates for Quantitative Risk Assessment , 1998 .

[201]  C. W. Hughes Emotion: Theory, Research and Experience , 1982 .

[202]  Sonia H. Contreras Ortiz,et al.  A machine learning model for emotion recognition from physiological signals , 2020, Biomed. Signal Process. Control..

[203]  Mingjiang Wang,et al.  Dynamic entropy-based pattern learning to identify emotions from EEG signals across individuals , 2020 .

[204]  Yongli Liu,et al.  Emotion Recognition From Multi-Channel EEG Signals by Exploiting the Deep Belief-Conditional Random Field Framework , 2020, IEEE Access.

[205]  Wenming Wang,et al.  Multimodal Emotion Recognition Based on Ensemble Convolutional Neural Network , 2020, IEEE Access.

[206]  S. T. Veena,et al.  Human Emotion Classification Using EEG Signals by Multivariate SynchroSqueezing Transform , 2019 .

[207]  J. X. Chen,et al.  A Hierarchical Bidirectional GRU Model With Attention for EEG-Based Emotion Classification , 2019, IEEE Access.

[208]  Neelam Rup Prakash,et al.  Audio-video emotional response mapping based upon Electrodermal Activity , 2019, Biomed. Signal Process. Control..

[209]  Dharmapal Dronacharya Doye,et al.  An Adaptive Approach of Fused Feature Extraction for Emotion Recognition Using EEG Signals , 2019, Application of Biomedical Engineering in Neuroscience.

[210]  Wei Li,et al.  Wavelets for Electrocardiogram: Overview and Taxonomy , 2019, IEEE Access.

[211]  Naeem Ramzan,et al.  DREAMER: A Database for Emotion Recognition Through EEG and ECG Signals From Wireless Low-cost Off-the-Shelf Devices , 2018, IEEE Journal of Biomedical and Health Informatics.

[212]  Cheng He,et al.  An Emotion Recognition System Based on Physiological Signals Obtained by Wearable Sensors , 2017 .

[213]  Khairun Nisa' Minhad,et al.  Human emotion classifications for automotive driver using skin conductance response signal , 2016, 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES).

[214]  Qingjie Zhao,et al.  Automatic Depression Discrimination on FNIRS by Using FastICA/WPD and SVM , 2015 .

[215]  I. Siegert,et al.  Emotion and Disposition Detection in Medical Machines: Chances and Challenges , 2015 .

[216]  F. Lozano Basic Theories of Traditional Chinese Medicine , 2014 .

[217]  Mohammad Soleymani,et al.  A Multimodal Database for Affect Recognition and Implicit Tagging , 2012, IEEE Transactions on Affective Computing.

[218]  Abhishek Vaish,et al.  A Comparative Study on Machine Learning Algorithms in Emotion State Recognition Using ECG , 2012, SocProS.

[219]  Dimitrios Hatzinakos,et al.  ECG Pattern Analysis for Emotion Detection , 2012, IEEE Transactions on Affective Computing.

[220]  Olga Sourina,et al.  Real-Time EEG-Based Emotion Recognition and Its Applications , 2011, Trans. Comput. Sci..

[221]  Guo Xian-Hai,et al.  Study of Emotion Recognition Based on Electrocardiogram and RBF neural network , 2011 .

[222]  K. Wong,et al.  A GMM based 2-stage architecture for multi-subject emotion recognition using physiological responses , 2010, AH.

[223]  S. Delplanque,et al.  Electrical autonomic correlates of emotion. , 2009, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[224]  P. Unschuld Huang Di Nei Jing Su Wen , 2003 .

[225]  A. Umezawa Facilitation and Inhibition of Breathing During Changes in Emotion , 2001 .

[226]  R. Bales Social Interaction Systems: Theory and Measurement , 1999 .