Work

Deep-Learning-Based Models for Pain Recognition: A Systematic Review

Year: 2020

Type: review

Abstract: The traditional standards employed for pain assessment have many limitations. One such limitation is reliability because of inter-observer variability. Therefore, there have been many approaches to automate the task of pain recognition. Recently, deep-learning methods have appeared to solve many challenges, such as feature selection and cases with a small number of data sets. This study provides a systematic review of pain-recognition systems that are based on deep-learning models for the last two years only. Furthermore, it presents the major deep-learning methods that were used in review papers. Finally, it provides a discussion of the challenges and open issues.

Source: Applied Sciences

DOI: 10.3390/app10175984

Authors: Rasha M. Al-Eidan, Hend Al-Khalifa, AbdulMalik Alsalman

Institution: King Saud University

Language: English

Topic: Emotion and Mood Recognition

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,901