SigRep: Towards Robust Wearable Emotion Recognition with Contrastive Representation Learning

Dissanayake, Vipula and Seneviratne, Sachith and Rana, Rajib ORCID: https://orcid.org/0000-0002-0506-2409 and Wen, Elliot and Kaluarachchi, Tharindu and Nanayakkara, Suranga (2022) SigRep: Towards Robust Wearable Emotion Recognition with Contrastive Representation Learning. IEEE Access.

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Abstract

Extracting emotions from physiological signals has become popular over the past decade. Recent advancements in wearable smart devices have enabled capturing physiological signals continuously and unobtrusively. However, signal readings from different smart wearables are lossy due to user activities, making it difficult to develop robust models for emotion recognition. Also, the limited availability of data labels is an inherent challenge for developing machine learning techniques for emotion classification. This paper presents a novel self-supervised approach inspired by contrastive learning to address the above challenges. In particular, our proposed approach develops a method to learn representations of individual physiological signals, which can be used for downstream classification tasks. Our evaluation with four publicly available datasets shows that the proposed method surpasses the emotion recognition performance of state-of-the-art techniques for emotion classification. In addition, we show that our method is more robust to losses in the input signal.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Mathematics, Physics and Computing (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Mathematics, Physics and Computing (1 Jan 2022 -)
Date Deposited: 09 Feb 2022 03:22
Last Modified: 09 Feb 2022 23:52
Uncontrolled Keywords: emotion recognition, representation learning, self-supervised learning, wearable signals
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080199 Artificial Intelligence and Image Processing not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460212 Speech recognition
46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461199 Machine learning not elsewhere classified
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: https://doi.org/10.1109/ACCESS.2022.3149509
URI: http://eprints.usq.edu.au/id/eprint/47017

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