Transformer with Leveraged Masked Autoencoder for video-based Pain Assessment

• URL: http://arxiv.org/abs/2409.05088v3
• Date: Mon, 30 Sep 2024 04:35:19 GMT
• Title: Transformer with Leveraged Masked Autoencoder for video-based Pain Assessment
• Authors: Minh-Duc Nguyen, Hyung-Jeong Yang, Soo-Hyung Kim, Ji-Eun Shin, Seung-Won Kim,
• Abstract summary: We enhance pain recognition by employing facial video analysis within a Transformer-based deep learning model. By combining a powerful Masked Autoencoder with a Transformers-based classifier, our model effectively captures pain level indicators through both expressions and micro-expressions.
• Score: 11.016004057765185
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Accurate pain assessment is crucial in healthcare for effective diagnosis and treatment; however, traditional methods relying on self-reporting are inadequate for populations unable to communicate their pain. Cutting-edge AI is promising for supporting clinicians in pain recognition using facial video data. In this paper, we enhance pain recognition by employing facial video analysis within a Transformer-based deep learning model. By combining a powerful Masked Autoencoder with a Transformers-based classifier, our model effectively captures pain level indicators through both expressions and micro-expressions. We conducted our experiment on the AI4Pain dataset, which produced promising results that pave the way for innovative healthcare solutions that are both comprehensive and objective.

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