Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition

Fourati, Rahma; Ammar, Boudour; Sánchez-Medina, Javier J.; Alimi, Adel M.

doi:10.48550/arxiv.1811.07516

Cited by 2 publications

(2 citation statements)

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“…The simplest approach to this training is to use the Moore-Penrose pseudo-inverse: W out = ỹ(t)x(t) † which gives the solution explicitly and without the need for iterative backpropagation. A δ update rule can also be used that performs single-step gradient descent on the linear outputs [114], continually tuning weights in response to changes in input data conditions or even the reservoir itself. No matter the particular training methodology the reservoir may be used to solve multiple problems, since W out is not integral to the reservoir.…”

Section: Reservoir Computingmentioning

confidence: 99%

SuperMind: a survey of the potential of superconducting electronics for neuromorphic computing

Schneider

Toomey

Rowlands

et al. 2022

Supercond. Sci. Technol.

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Neuromorphic computing is a broad field that uses biological inspiration to address computing design. It is being pursued in many hardware technologies both novel and conventional. We discuss the use of superconductive electronics for neuromorphic computing and why they are a compelling technology for the design of neuromorphic computing systems. One example is, the natural spiking behavior of Josephson junctions and the ability to transmit short voltage spikes without the resistive capacitive time constants that typically hinder spike based computing. We review the work that has been done on biologically inspired superconductive devices, circuits, and architectures and discuss the scaling potential of these demonstrations.

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Section: Reservoir Computingmentioning

confidence: 99%

SuperMind: a survey of the potential of superconducting electronics for neuromorphic computing

Schneider

Toomey

Rowlands

et al. 2022

Supercond. Sci. Technol.

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“…Researches conducted for anxiety/stress detection based on EEG signals analysis are few compared to those done for emotion recognition surveyed in [17] [18]. Most of the proposed works for EEG-based emotion recognition as in [19] [3] were validated using DEAP datatset [20]. It was recorded using Biosemi Active 2 headset with 32 channels.…”

Section: Introductionmentioning

confidence: 99%

DASPS: A Database for Anxious States based on a Psychological Stimulation

Baghdadi,

Aribi,

Fourati

et al. 2019

Preprint

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Anxiety affects human capabilities and behavior as much as it affects productivity and quality of life. It can be considered as the main cause of depression and suicide. Anxious states are detectable by specialists due to their acquired cognition and skills, humans interpret the interlocutor's tone of speech, gesture, facial expressions and recognize their mental state. There is a need for non-invasive reliable techniques that performs the complex task of anxiety detection. In this paper, we present DASPS database containing recorded Electroencephalogram (EEG) signals of 23 participants during anxiety elicitation by means of face-to-face psychological stimuli. EEG signals were captured with Emotiv Epoc headset as it's a wireless wearable low-cost equipment. In our study, we investigate the impact of different parameters, notably: trial duration, feature type, feature combination and anxiety levels number. Our findings showed that anxiety is well elicited in 1 second. For instance, stacked sparse autoencoder with different type of features achieves 83.50% and 74.60% for 2 and 4 anxiety levels detection, respectively. The presented results prove the benefits of the use of a low-cost EEG headset instead of medical non-wireless devices and create a starting point for new researches in the field of anxiety detection.

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Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition

Cited by 2 publications

References 0 publications

SuperMind: a survey of the potential of superconducting electronics for neuromorphic computing

SuperMind: a survey of the potential of superconducting electronics for neuromorphic computing

DASPS: A Database for Anxious States based on a Psychological Stimulation

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