The DOI matches its Crossref record; 182 of the 182 references it cites were found in a registry or an index.
A Review, Current Challenges, and Future Possibilities on Emotion Recognition Using Machine Learning and Physiological Signals
Open accessAbstract
The seminal work on Affective Computing in 1995 by Picard set the base for computing that relates to, arises from, or influences emotions. Affective computing is a multidisciplinary field of research spanning the areas of computer science, psychology, and cognitive science. Potential applications include automated driver assistance, healthcare, human-computer interaction, entertainment, marketing, teaching and many others. Thus, quickly, the field acquired high interest, with an enormous growth of the number of papers published on the topic since its inception. This paper aims to (1) Present an introduction to the field of affective computing though the description of key theoretical concepts; (2) Describe the current state-of-the-art of emotion recognition, tracing the developments that helped foster the growth of the field; and lastly, (3) point the literature take-home messages and conclusions, evidencing the main challenges and future opportunities that lie ahead, in particular for the development of novel machine learning (ML) algorithms in the context of emotion recognition using physiological signals.
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Cites
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Cited by
Emotion recognition in EEG signals using deep learning methods: A review
Jafari, M., Shoeibi, A., Khodatars, M., Bagherzadeh, S., Shalbaf, A., García, D. L., Gorriz, J. M., & Acharya, U. R. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107450 · Cited by 240
Emotion assessment using Machine Learning and low-cost wearable devices
Laureanti, R., Bilucaglia, M., Zito, M., Circi, R., Fici, A., Rivetti, F., Valesi, R., Oldrini, C., Mainardi, L. T., & Russo, V. (2020) · 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175221 · Cited by 33
Moussaoui, K., & Farah, M. (2024) · 2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP) · doi:10.1109/atsip62566.2024.10638977 · Cited by 2
Metadata
- Authors
- Bota, P. J., Wang, C., Fred, A. L. N., & Placido Da Silva, H.
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 140990-141020
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2975003464
- Cited by
- 322
- References
- 182
- FWCI
- 24.06
- Type
- journal article
- Language
- en
- Open access
- gold
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- Bota, P. J., Wang, C., Fred, A. L. N., & Placido Da Silva, H. (2019). A Review, Current Challenges, and Future Possibilities on Emotion Recognition Using Machine Learning and Physiological Signals. IEEE Access. https://doi.org/10.1109/access.2019.2944001
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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