Zakia Hammal
Steffen Walter
ABSTRACT
Pain communication varies, with some patients being highly expressive regarding their pain and others exhibiting stoic forbearance and minimal verbal account of discomfort. Considerable progress has been made in defining behavioral indices of pain [1-3]. An abundant literature shows that a limited subset of facial movements, in several non-human species, encode pain intensity across the lifespan [2]. To advance reliable pain monitoring, automated assessment of pain is emerging as a powerful mean to realize that goal. Though progress has been made, this field remains in its infancy. The workshop aims to promote current research and support growth of interdisciplinary collaborations to advance this groundbreaking research.
- Zakia Hammal and Jeffrey F. Cohn. 2018. Automatic, Objective, and Efficient Measurement of Pain Using Automated Face Analysis. Handbook of Social and interpersonal processes in pain: We don't suffer alone, pp. 121–146, Springer.Google Scholar
- Ken Prkachin and Zakia Hammal. 2021. Computer mediated automatic detection of pain-related behavior: prospect, progress, perils. Frontiers in Pain Research. vol. 2, pp. 1-14.Google ScholarCross Ref
- Ken Prkachin and Zakia Hammal. 2021. Automated Assessment of Pain: Prospects, Progress, and a Path Forward. In Companion Publication of the 2021 ACM International Conference in Multimodal Interaction Workshops.Google ScholarDigital Library
- Werner Philipp, Daniel Lopez-Martinez, Steffen Walter, Ayoub Al-Hamadi, Sascha Gruss, and Rosalind Picard. 2019. Automatic Recognition Methods Supporting Pain Assessment: A Survey. IEEE Transactions on Affective Computing (2019).Google Scholar
- Benjamin Szczapa, Mohamed Daoudi, Stefano Berretti, Pietro Pala, Alberto Del Bimbo and Zakia Hammal. 2022. Automatic Estimation of Self-Reported Pain by Trajectory Analysis in the Manifold of Fixed Rank Positive Semi-Definite Matrices. IEEE Transactions on Affective Computing. vol. 13, no. 4, pp. 1813-1826Google ScholarCross Ref
- Diyala Erekat, Zakia Hammal, Maimoon Siddiqui and Hamdi Dibeklioğlu. 2020. Enforcing Multilabel Consistency for Spatio-Temporal Assessment of Shoulder Pain Intensity. In Companion Publication of the 2020 ACM International Conference in Multimodal Interaction Workshops.Google Scholar
- Tobias Beniamin Ricken, Peter Bellmann, Sasha Gruss, Steffen Walter and Friedhelm Schwenker. (2023). Pain Recognition Differences between Female and Male Subjects: An Analysis based on the Physiological Signals of the X-ITE Pain Database. In Companion Publication of the 2023 ACM International Conference in Multimodal Interaction Workshops.Google ScholarDigital Library
- Prasanth Murali, Mehdi Arjmand, Matias Volonte, James Griffith, Michael Paasche-Orlow and Timothy Bickmore.. 2023. Towards Automated Pain Assessment using Embodied Conversational Agents. In Companion Publication of the 2023 ACM International Conference in Multimodal Interaction Workshops.Google ScholarDigital Library
- Mustafa Atee, Kreshnik Hoti, Jeffery D. Hughes. 2018. Technical Note on the PainChek System: A Web Portal and Mobile Medical Device for Assessing Pain in People with Dementia. Front Aging Neurosci. (2018) 10:117.Google Scholar
Index Terms
- Automated Assessment of Pain (AAP)
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