Physiological-signal-based emotion recognition: An odyssey from methodology to philosophy
暂无分享,去创建一个
[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 .