ArticleScientific data2024
An Experimental and Clinical Physiological Signal Dataset for Automated Pain Recognition.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Predictors of Procedural Pain in Office Hysteroscopy.Medical science monitor : international medical journal of experimental and clinical research · 2026Observational
- Pain assessment using physiological responses/markers in different types of pain: a scoping review.NPJ digital medicine · 2026Article
- Machine Learning and ECG-Derived Biomarkers for Objective Pain Assessment: An Explainable AI Approach Toward Precision Pain Management.Pain research & management · 2026Article
- Classifying social and physical pain from multimodal physiological signals using machine learning.Scientific reports · 2025Article
- A comprehensive survey and comparative analysis of time series data augmentation in medical wearable computing.PloS one · 2025Article
- Pseudo-labeling based adaptations of pain domain classifiers.Frontiers in pain research (Lausanne, Switzerland) · 2025Article
- An Experimental and Clinical Physiological Signal Dataset for Automated Pain Recognition.Scientific data · 2024Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Access to large amounts of data is essential for successful machine learning research. However, there is insufficient data for many applications, as data collection is often challenging and time-consuming. The same applies to automated pain recognition, where algorithms aim to learn associations between a level of pain and behavioural or physiological responses. Although machine learning models have shown promise in improving the current gold standard of pain monitoring (self-reports) only a handful of datasets are freely accessible to researchers. This paper presents the PainMonit Dataset for automated pain detection using physiological data. The dataset consists of two parts, as pain can be perceived differently depending on its underlying cause. (1) Pain was triggered by heat stimuli in an experimental study during which nine physiological sensor modalities (BVP, 2×EDA, skin temperature, ECG, EMG, IBI, HR, respiration) were recorded from 55 healthy subjects. (2) Eight modalities (2×BVP, 2×EDA, EMG, skin temperature, respiration, grip) were recorded from 49 participants to assess their pain during a physiotherapy session.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.