The Use of AI for Thermal Emotion Recognition: A Review of Problems and Limitations in Standard Design and Data

Ordun, Catherine; Raff, Edward; Purushotham, Sanjay

doi:10.48550/arxiv.2009.10589

Cited by 1 publication

(1 citation statement)

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“…Next, since patients were unable to conduct in-clinic visits, we were unable to gather thermal imagery captured from a thermal camera stationed at the clinic. Thermal imagery offers insights into physiological states that is unseen on visible images alone [61]. Our intent is to generate paired visible-thermal datasets as collected by the Iris, Eurecom, and Equinox datasets [62][63][64].…”

Section: Future Workmentioning

confidence: 99%

Intelligent Sight and Sound: A Chronic Cancer Pain Dataset

Ordun¹,

Cha²,

Raff³

et al. 2022

Preprint

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Cancer patients experience high rates of chronic pain throughout the treatment process. Assessing pain for this patient population is a vital component of psychological and functional well-being, as it can cause a rapid deterioration of quality of life. Existing work in facial pain detection often have deficiencies in labeling or methodology that prevent them from being clinically relevant. This paper introduces the first chronic cancer pain dataset, collected as part of the Intelligent Sight and Sound (ISS) clinical trial, guided by clinicians to help ensure that model findings yield clinically relevant results. The data collected to date consists of 29 patients, 509 smartphone videos, 189,999 frames, and self-reported affective and activity pain scores adopted from the Brief Pain Inventory (BPI). Using static images and multi-modal data to predict self-reported pain levels, early models show significant gaps between current methods available to predict pain today, with room for improvement. Due to the especially sensitive nature of the inherent Personally Identifiable Information (PII) of facial images, the dataset will be released under the guidance and control of the National Institutes of Health (NIH).35th Conference on Neural Information Processing Systems (NeurIPS 2021) Track on Datasets and Benchmarks.

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Section: Future Workmentioning

confidence: 99%