Multimodal Pain Level Recognition using Majority Voting Technique
| Autor: | Mahmoud I. Khalil, Hazem M. Abbas, Amir Ibrahim Mohamed Salah |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Majority rule
Facial expression Computer science Speech recognition Feature extraction 020206 networking & telecommunications Cognition 02 engineering and technology 030204 cardiovascular system & hematology Ensemble learning Data modeling Support vector machine 03 medical and health sciences Facial muscles 0302 clinical medicine medicine.anatomical_structure 0202 electrical engineering electronic engineering information engineering medicine |
| Zdroj: | 2018 13th International Conference on Computer Engineering and Systems (ICCES). |
| DOI: | 10.1109/icces.2018.8639215 |
| Popis: | The measurement of subjective pain is still a problem especially with people who have verbal or cognitive impairments. In this work, we analyze the problem of some patients who did not express their pain through their facial muscles, but they were expressing it involuntarily through the autonomic neural system that can be observed in the physiological signals. An ensemble learning algorithm consisting of multimodal models trained on the geometric facial expressions and the physiological signals is proposed. Each model provides a certainty measure and the pain level is assigned by the most certain model. The proposed system is compared with the previous models. |
| Databáze: | OpenAIRE |
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