Awesome Pain Intensity Classification Papers

(to be updated)

A comprehensive list of pain intensity classification papers and the dataset used.

Any contribution is welcome!

Latest Review/Survey papers

Year	Topic
2023	Review and Analysis of Pain Research Literature through Keyword Co-occurrence Networks Plos Digital Health
2023	Artificial Intelligence for Automatic Pain Assessment: Research Methods and Perspectives Pain Research and Management
2021	Pain and Stress Detection Using Wearable Sensors and Devices—A Review sensors
2021	Machine Learning in Pain Medicine: An Up-To-Date Systematic Review Pain and Therapy
2020	Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review sensors
2020	Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review sensors
2019	Automatic Recognition Methods Supporting Pain Assessment: A Survey IEEE Transactions on Affective Computing
2018	A Review of Automated Pain Assessment in Infants: Features, Classification Tasks, and Databases IEEE Reviews in Biomedical Engineering

Pain Classification Papers

Year	Topic	Model	Signal	Dataset
2023	Transformer Encoder with Multiscale Deep Learning for Pain Classification Using Physiological Signals Frontiers in Physiology	Transformer Encoder+Temporal Conv+SEResNet; Code: github	EDA	BioVid
2022	Personalized Deep Bi-LSTM RNN Based Model for Pain Intensity Classification Using EDA Signal sensors	BiLSTM + XGBoost	EDA	Proprietary Dataset: Cold Pain Data
2022	Tree-Based Models for Pain Detection from Biomedical Signals ICOST 2022	AdaBoost, XGBoost, TabNet, Random Forest (RF)	EDA,ECG	BioVid
2021	Multi-Modal Pain Intensity Assessment Based on Physiological Signals: A Deep Learning Perspective Frontiers in Physiology	Self-supervised Learning, Auto-Encoder	EMG + ECG + EDA	BioVid; SenseEmotion
2021	Automated Nociceptive Pain Assessment Using Physiological Signals and a Hybrid Deep Learning Network IEEE Sensors Journal	CNN + LSTM	EDA, ECG	BioVid; Proprietary Dataset: Real-time Data
2021	Comparison of Feature Extraction Methods for Physiological Signals for Heat-Based Pain Recognition sensors	MLP	EDA	BioVid
2021	Pain Recognition With Electrocardiographic Features in Postoperative Patients: Method Validation Study JMIR	ADABoost, XGBoost, random forest, SVM, KNN	ECG	BioVid as baseline; UCI_iHurtDB
2021	Exploration of physiological sensors, features, and machine learning models for pain intensity estimation PLOS ONE	SVM	EDA	BioVid
2021	Objective Pain Assessment Using Wrist-based PPG Signals: A Respiratory Rate Based Method EMBC	ADABoost, XGBoost, random forest, SVM, KNN	PPG	UCI_iHurtDB
2021	Machine learning suggests sleep as a core factor in chronic pain Pain	CART, PART, RF	Mul-Sources Parametes	Proprietary Dataset: chronic pain, Finland
2021	Assessment of thoracic pain using machine learning: a case study from Baja California, Mexico Environmental Research and Public Health	Tree classification, RF, SVM, Logistic regression, kNN	AMI and FRCV Six Factors	Proprietary Dataset: Thoracic Pain
2021	Prediction of breakthrough pain during labour neuraxial analgesia: comparison of machine learning and multivariable regression approaches Obstetric Anesthesia	RF, XGBoost, Logistic Regression	Medical Record	Proprietary Dataset: breakthrough pain during labour, Singapore
2020	Hybrid RNN-ANN Based Deep Physiological Network for Pain Recognition EMBC 2020	BiLSTM	EDA, ECG, EMG	BioVid
2020	Pain phenotypes classified by machine learning using electroencephalography features NeuroImage	SVM	EEG, VAS	Proprietary Dataset: Chronic lumbar pain
2020	Machine-learning-based knowledge discovery in rheumatoid arthritis-related registry data to identify predictors of persistent pain Pain	CART, kNN, MLP, SVM, Naive Bayes	Multi-sources Parameters	Proprietary Dataset: Rheumatoid arthritis
2020	Diverse frequency band-based convolutional neural networks for tonic cold pain assessment using EEG Neurocomputing	CNN	EEG	Proprietary Dataset: Cold Pain Data
2020	Using a motion sensor to categorize nonspecific low back pain patients: a machine learning approach sensors	SVM, MLP	Trunk kinematic data	Propritary Dataset: Nonspecific low back pain
2020	Identifying predictive factors for neuropathic pain after breast cancer surgery using machine learning International Journal of Medical Informatics	RF, Linear Regression, Elastic Net, Ridge Regression, Gradient Boosting, Neural Net	Questionnaires before and after surgery	Prospective Cohort Study, Neuropathic pain
2020	Interpretable machine learning models for classifying low back pain status using functional physiological variables European Spine Journal	Functional Data Boosting (FDboost)	EMG	Proprietary Dataset: Low Back Pain
2020	Diverse frequency band-based convolutional neural networks for tonic cold pain assessment using EEG Neurocomputing	CNN	EEG	Proprietary Dataset: Cold Pain Data
2020	Medical expert system for low back pain management: design issues and conflict resolution with Bayesian network Medical & Biological Engineering & Computing	Bayes	Clinical Records	Proprietary Dataset: Low back pain
2019	Feature extraction and selection for pain recognition using peripheral physiological signals Frontiers in Neuroscience	SVM	EMG, SCL, ECG	BioVid
2019	Predicting inadequate postoperative pain management in depressed patients: a machine learning approach Plos ONE	Elastic Net, NLP (NegEx)	65 predictive features from EHR	Proprietary Dataset: EHR
2019	Exploring Deep Physiological Models for Nociceptive Pain Recognition sensors	CNN	EDA, ECG	BioVid
2019	A Deep Neural Network-Based Pain Classifier Using a Photoplethysmography Signal sensors	Deep Belief Network, MLP, SVM	PPG	Proprietary Dataset: Pre-/Post-operation of Surgery
2019	Acute pain intensity monitoring with the classification of multiple physiological parameters Journal of Clinical Monitoring and Computing	MLP	HR, BR, GSR, EMG	Proprietary Dataset: Heat and Electrical Stimuli
2019	Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics Pain	SVM	Neuroimages	Proprietary Dataset: Chronic Low Back Pain
2019	Exploring Deep Physiological Models for Nociceptive Pain Recognition sensors	CNN	EDA, ECG	BioVid
2019	Acute pain intensity monitoring with the classification of multiple physiological parameters Journal of Clinical Monitoring and Computing	MLP	HR, Breath Rate, GSR, EMG	Proprietary Dataset, HR, BR, GSR, Facial
2019	A joint deep neural network model for pain recognition from face ICCCS 2019	RNN+VGGFace CNN	Facial Images	UNBC-McMaster Shoulder Pain
2018	Deep Multimodal Pain Recognition: A Database and Comparison of Spatio-Temporal Visual Modalities FG 2018	CNN+LSTM	RGBDT (RGB, Depth, Thermal)	Multimodal Intensity Pain (MIntPAIN)
2018	Continuous Pain Intensity Estimation from Autonomic Signals with Recurrent Neural Networks EMBCC 2018	LSTM-NN	EDA, HR	BioVid
2018	Deep learning model for detection of pain intensity from facial expression ICOST 2018	BiLSTM-CNN-VSL-CRF	Facial Expressions	-
2018	Improving pain management in patients with sickle cell disease from physiological measures using machine learning techniques Smart Health	RF, kNN, SVM, Multinomial logistic regression	Peripheral capillary oxygen saturation, systolic blood pressure, diastolic blood pressure, heart rate, respiratory rate, temperature	Proprietary Dataset: SCD patients, Duke Hospital
2017	Prediction effects of personal, psychosocial, and occupational risk factors on low back pain severity using artificial neural networks approach in industrial workers Manipulative and Physiological Therapeutics	MLP, kNN, Logistic Regression	BVP, ECG, SCL	Proprietary Dataset: Low back pain
2017	Multi-task neural networks for personalized pain recognition from physiological signals ACIIW 2017	MLP	EDA, ECG	BioVid
2017	Physiological Signal-Based Method for Measurement of Pain Intensity Front Neurosci.	KNN, SVM, LDA	BVP, ECG, SCL	Proprietary Dataset: Electrical stimulation
2017	Multi-task neural networks for personalized pain recognition from physiological signals ACIIW 2017	MLP	EDA, ECG	BioVid
2015	Multimodal Data Fusion for Person-Independent, Continuous Estimation of Pain Intensity EANN 2015	Random Forest	EDA, ECG, EMG, Videos	BioVid
2014	Automatic Pain Recognition from Video and Biomedical Signals International Conference on Pattern Recognition	Random Forest	EDA, ECG, EMG, Videos	BioVid

Datasets Mentioned Above

Year	Name	Dataset
2005	Infant database: COPE/iCOPE	http://www.brahnam.info/papers/EN2031.pdf
2011	UNBC-McMaster Shoulder Pain	http://www.jeffcohn.net/Resources/
2013	BioVid Heat Pain Database	https://www.nit.ovgu.de/BioVid.html
2016	PPG Signals	http://cris.nih.go.kr Registration Number: KCT0002080 https://cris.nih.go.kr/cris/search/detailSearch.do/6638
2017	SenseEmotion	-
2018	Multimodal Intensity Pain (MIntPAIN)	https://vap.aau.dk/mintpain-database/

Other Public Pain Databases Collection

List of Publicly Available Pain Recognition Databases Collected by Philipp Werner.

License

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