A Review of Emotion Recognition Using Physiological Signals

Figures

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  Figure 1. Plutchik’s Wheel of Emotions.

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  Figure 2. 2D emotion space model.

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  Figure 3. 3D emotion space model.

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  Figure 4. (a) MAUI—Multimodal Affective User Interface; (b) Framework of AVRS; (c) VR scenes cut show.

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  Figure 5. Position of the bio-sensors.

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  Figure 6. (a) Mean accuracy of different channels; (b) The performance of different windows sizes; (c) The average accuracies of GELM; (d) Spectrogram shows different patterns with different emotions.

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  Figure 7. (a) Logical scheme of the overall short-time emotion recognition concept; (b) Instantaneous tracking of the HR V indices computed from a representative subject using the proposed NARI model during the passive emotional elicitation (two neutral sessions alternated to a L-M and a M-H arousal session); (c) Diagram of the proposed method; (d) Experimental results.

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  Figure 8. (a) The Emotion Check device; (b) Diagram describing the components of the Emotion Check device; (c) Prototype of glove with sensor unit; (d) Body Media Sense Wear Armband; (e) Left: The physiological measures of EMG and EDA. Middle: The physiological measures of EEG, BVP and TMP. Right: The physiological measures of physiological sensors in the experiments; (g) Illustration of R-TIPS. This platform allows wireless monitoring of cardiac signals. It consists of a transmitter system and three sensors; (f) The transmitter system is placed on the participant’s hip, and the sensors are placed below right breast, on the right side, and on the back.

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  Figure 9. (a) Monitoring of epileptic seizures using EDA; (b,c) Wearable GSR sensor.

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  Figure 10. Emotion recognition process using physiological signals under target emotion stimulation.

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  Figure 11. (a) The decomposition of R-R interval signal (emotion of sadness); (b) The structure of Autoencoder; (c) The structure of Bimodal Deep AutoEncoder.

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  Figure 12. (a) Typical framework of multimodal information fusion; (b) SVM results for different emotions with EEG frequency band; (c) Demo of the proposed feature level fusion. A feature vector created at any time step is valid for the next two steps.