Data from: Pain intensity recognition rates via biopotential feature patterns with support vector machines

Gruss S, Walter S

Date Published: October 19, 2015

DOI: http://dx.doi.org/10.5061/dryad.2b09s

 

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Title List of extracted biopotential pain features
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Description Reference: Steffen Walter, Philipp Werner, Sascha Gruss, Harald C. Traue, Ayoub Al-Hamadi, et al.: The BioVid Heat Pain Database: Data for the Advancement and Systematic Validation of an Automated Pain Recognition System. In Proceedings of IEEE International Conference on Cybernetics, 2013. Pain stimulation data: Extracted features of biomedical signals (SCL, ECG, EMG at trapezius, corrugator and zygomaticus muscle); 85 subjects; features extracted of time windows of 5.5 seconds; used to classify pain intensities; 5 classes (pain intensity 0 to pain intensity 4), 20 samples per class per subject.
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When using this data, please cite the original publication:

Gruss S, Treister R, Werner P, Traue HC, Crawcour S, Andrade A, Walter S (2015) Pain intensity recognition rates via biopotential feature patterns with support vector machines. PLoS ONE 10(10): e0140330. http://dx.doi.org/10.1371/journal.pone.0140330

Additionally, please cite the Dryad data package:

Gruss S, Walter S (2015) Data from: Pain intensity recognition rates via biopotential feature patterns with support vector machines. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.2b09s
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