ArticleFrontiers in neuroscience2022
Experimental Exploration of Objective Human Pain Assessment Using Multimodal Sensing Signals.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Personalized Prediction of Acute and Chronic Postsurgical Pain - the role of Multidomain Biosignatures, Machine Learning-Based Integration, and Standardized Outcome Definitions.Current pain and headache reports · 2026Review
- Cross-spectral fusion of thermal and RGB imaging for objective pain estimation.PLOS digital health · 2026Article
- Pain assessment using physiological responses/markers in different types of pain: a scoping review.NPJ digital medicine · 2026Article
- Continuous, Contactless, and Multimodal Pain Assessment During Surgical Interventions.IEEE open journal of engineering in medicine and biology · 2026Article
- Influence of Pre-Existing Pain on the Body's Response to External Pain Stimuli: Experimental Study.JMIR biomedical engineering · 2025Article
- Utilizing Artificial Intelligence for the Diagnosis, Assessment, and Management of Chronic Pain.Journal of biomedical physics & engineering · 2025Review
- Physiological Sensor Modality Sensitivity Test for Pain Intensity Classification in Quantitative Sensory Testing.Sensors (Basel, Switzerland) · 2025Article
- The Investigation of the Relationship Between Individual Pain Perception, Brain Electrical Activity, and Facial Expression Based on Combined EEG and Facial EMG Analysis.Journal of pain research · 2025Article
- Non-Invasive Biosensing for Healthcare Using Artificial Intelligence: A Semi-Systematic Review.Biosensors · 2024Review
- Article
- A robust approach for multi-type classification of brain tumor using deep feature fusion.Frontiers in neuroscience · 2024Article
- Rethinking pain communication of patients with Alzheimer's disease through E-textile interaction design.Frontiers in physiology · 2023Article
- Personalized Deep Bi-LSTM RNN Based Model for Pain Intensity Classification Using EDA Signal.Sensors (Basel, Switzerland) · 2022Article
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10 authors.
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Abstract
Optimization of pain assessment and treatment is an active area of research in healthcare. The purpose of this research is to create an objective pain intensity estimation system based on multimodal sensing signals through experimental studies. Twenty eight healthy subjects were recruited at Northeastern University. Nine physiological modalities were utilized in this research, namely facial expressions (FE), electroencephalography (EEG), eye movement (EM), skin conductance (SC), and blood volume pulse (BVP), electromyography (EMG), respiration rate (RR), skin temperature (ST), blood pressure (BP). Statistical analysis and machine learning algorithms were deployed to analyze the physiological data. FE, EEG, SC, BVP, and BP proved to be able to detect different pain states from healthy subjects. Multi-modalities proved to be promising in detecting different levels of painful states. A decision-level multi-modal fusion also proved to be efficient and accurate in classifying painful states.
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