Psychological stimulation for anxious states detection based on EEG-related features
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ORIGINAL RESEARCH
Psychological stimulation for anxious states detection based on EEG‑related features Asma Baghdadi1,2 · Yassine Aribi1,5 · Rahma Fourati1 · Najla Halouani3 · Patrick Siarry2,4 · Adel Alimi1 Received: 4 June 2020 / Accepted: 28 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Anxiety affects human capabilities and behavior as much as it affects productivity and quality of life. It is considered to be the main cause of depression and suicide. Anxious states are detectable by specialists by virtue of their acquired cognition and skills. There is a need for non-invasive reliable techniques that performs the complex task of anxiety detection. In our study, we investigate the impact of different parameters, notably: trial duration, feature type, feature combination and anxiety levels number. The system is evaluated using our own database containing recorded Electroencephalogram (EEG) signals from 23 participants during anxiety elicitation by means of face-to-face psychological stimuli. EEG signals were captured with an Emotiv Epoc headset as a cost-efficient wireless wearable equipment. Two labeling methods are used and results are presented accordingly. Our findings showed that anxiety is well elicited in 1 s. For Self Assessment Manikan SAM-based detection, Stacked Sparse Autoencoder (SSAE) with different type of features achieves 83.50% and 74.60% for 2 and 4 anxiety levels detection, respectively. Results are improved using the Hamilton-based method. We obtained a rate of 86.7% for 4 levels detection using SSAE. 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. Keywords Electroencephalogram · Stress and anxiety detection · Psychological stimulation · Feature extraction · Feature selection * Asma Baghdadi [email protected] * Yassine Aribi [email protected] * Rahma Fourati [email protected] Najla Halouani [email protected] Patrick Siarry siarry@univ‑paris12.fr Adel Alimi [email protected] 1
Research Groups in Intelligent Machines, National Engineering School of Sfax (ENIS), University of Sfax, BP 1173, 3038 Sfax, Tunisia
2
Laboratoire Images, Signaux et Systmes Intelligents, Université Paris Est Créteil, 120 Rue Paul Armangot, 94400 Vitry sur Seine, France
3
Hedi Chaker hospital, Sfax, Tunisia
4
LERISS, Université de Paris 12, 94010 Créteil, France
5
Taif University, College of Ranyah, Taif, Saudi Arabia
1 Introduction Anxiety is a mental health issue that has physical consequences on our bodies. However, it can affect the immune system, and unfortunately, there is evidence that too much anxiety can actually weaken the immune system dramatically (Felman 2018). Anxiety is essentially a long term stress, in such a way the stress hormone is liberated by our bodies in huge quantities which correlates with body performance degradation. This invisible disability can greatly affe
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