Emotion Recognition Based on Galvanic Skin Response and Photoplethysmography Signals Using Artificial Intelligence Algorithms
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-61960-1_3
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3. Schmidt, P., Reiss, A., Dürichen, R., Laerhoven, K.V.: Wearable-based affect recognition—a review. Sensors 19, 4079 (2019). https://doi.org/10.3390/s19194079
4. Shu, L., et al.: A review of emotion recognition using physiological signals. Sensors 18, 2074 (2018). https://doi.org/10.3390/s18072074
5. Bota, P.J., Wang, C., Fred, A.L.N., Da Silva, H.P.: A review, current challenges, and future possibilities on emotion recognition using machine learning and physiological signals. IEEE Access 7, 140990–141020 (2019). https://doi.org/10.1109/ACCESS.2019.2944001
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