Real-time pain detection in facial expressions for health robotics

Laduona Dai*, Joost Broekens, Khiet Phuong Truong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Automatic pain detection is an important challenge in health computing. In this paper we report on our efforts to develop a real-time, real-world pain detection system from human facial expressions. Although many studies addressed this challenge, most of them use the same dataset for training and testing. There is no cross-check with other datasets or implementation in real-time to check performance on new data. This is problematic, as evidenced in this paper, because the classifiers overtrain on dataset-specific features. This limits realtime, real-world usage. In this paper, we investigate different methods of real-time pain detection. The training data uses a combination of pain and emotion datasets, unlike other papers. The best model shows an accuracy of 88.4% on a dataset including pain and 7 non-pain emotional expressions. Results suggest that convolutional neural networks (CNN) are not the best methods in some cases as they easily overtrain if the dataset is biased. Finally we implemented our pain detection method on a humanoid robot for physiotherapy. Our work highlights the importance of cross-corpus evaluation & real-time testing, as well as the need for a well balanced and ecologically valid pain dataset.
Original languageEnglish
Title of host publication2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW)
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages277-283
ISBN (Electronic)978-1-7281-3891-6
ISBN (Print)978-1-7281-3892-3
DOIs
Publication statusPublished - 2019
Event8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2019
- Cambridge, United Kingdom
Duration: 3 Sep 20196 Sep 2019
Conference number: 8

Conference

Conference8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos, ACIIW 2019
Abbreviated titleACIIW
CountryUnited Kingdom
CityCambridge
Period3/09/196/09/19

Keywords

  • Pain detection
  • Classification
  • Generalization
  • Cross validation
  • Health

Fingerprint Dive into the research topics of 'Real-time pain detection in facial expressions for health robotics'. Together they form a unique fingerprint.

  • Cite this

    Dai, L., Broekens, J., & Truong, K. P. (2019). Real-time pain detection in facial expressions for health robotics. In 2019 8th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) (pp. 277-283). Piscataway, NJ: IEEE. https://doi.org/10.1109/ACIIW.2019.8925192