scholarly journals Rules Extraction of Relevance Vector Machine for Predicting Negative Emotions from EEG Signals

2008 ◽  
Author(s):  
Sandro Chagas ◽  
Marcio Eisencraft ◽  
Clodoaldo Aparecido Moraes Lima

2021 ◽  
Vol 15 ◽  
Author(s):  
Fangfang Long ◽  
Shanguang Zhao ◽  
Xin Wei ◽  
Siew-Cheok Ng ◽  
Xiaoli Ni ◽  
...  

The EEG features of different emotions were extracted based on multi-channel and forehead channels in this study. The EEG signals of 26 subjects were collected by the emotional video evoked method. The results show that the energy ratio and differential entropy of the frequency band can be used to classify positive and negative emotions effectively, and the best effect can be achieved by using an SVM classifier. When only the forehead and forehead signals are used, the highest classification accuracy can reach 66%. When the data of all channels are used, the highest accuracy of the model can reach 82%. After channel selection, the best model of this study can be obtained. The accuracy is more than 86%.


2019 ◽  
Author(s):  
Victoria Leong ◽  
Valdas Noreika ◽  
Kaili Clackson ◽  
Stanimira Georgieva ◽  
Laura Brightman ◽  
...  

Social learning allows infants to learn vicariously by observing adult behaviour, but how the infant brain accomplishes this feat remains unknown. Here, electroencephalography (EEG) signals were simultaneously measured from forty-seven mothers and infants (10.7 months) during a live social learning task. First, infants observed mothers demonstrate positive or negative emotions toward novel toys. Next, infants’ own toy interaction (learning) was measured. Infants’ social learning likelihood was robustly predicted by mother-infant interpersonal neural connectivity in the Alpha (6-9 Hz) band. Stronger dyadic neural connectedness predicted increased learning, and was associated with extended ostensive eye contact and maternal utterances. Intra-infant neural connectivity predicted learning valence (positive/negative) but was unrelated to learning likelihood. Therefore, interpersonal connectivity is a neural mechanism by which infants learn from their social partners.


2022 ◽  
Vol 12 ◽  
Author(s):  
Lei Jiang ◽  
Panote Siriaraya ◽  
Dongeun Choi ◽  
Noriaki Kuwahara

Objective: Numerous communication support systems based on reminiscence therapy have been developed. However, when using communication support systems, the emotional assessment of older people is generally conducted using verbal feedback or questionnaires. The purpose of this study is to investigate the feasibility of using Electroencephalography (EEG) signals for automatic emotion recognition during RT for older people.Participants: Eleven older people (mean 71.25, SD 4.66) and seven young people (mean 22.4, SD 1.51) participated in the experiment.Methods: Old public photographs were used as material for reminiscence therapy. The EEG signals of the older people were collected while the older people and young people were talking about the contents of the photos. Since emotions change slowly and responses are characterized by delayed effects in EEG, the depth models LSTM and Bi-LSTM were selected to extract complex emotional features from EEG signals for automatic recognition of emotions.Results: The EEG data of 8 channels were inputted into the LSTM and Bi-LSTM models to classify positive and negative emotions. The recognition highest accuracy rate of the two models were 90.8% and 95.8% respectively. The four-channel EEG data based Bi-LSTM also reached 94.4%.Conclusion: Since the Bi-LSTM model could tap into the influence of “past” and “future” emotional states on the current emotional state in the EEG signal, we found that it can help improve the ability to recognize positive and negative emotions in older people. In particular, it is feasible to use EEG signals without the necessity of multimodal physiological signals for emotion recognition in the communication support systems for reminiscence therapy when using this model.


2010 ◽  
Vol 24 (2) ◽  
pp. 131-135 ◽  
Author(s):  
Włodzimierz Klonowski ◽  
Pawel Stepien ◽  
Robert Stepien

Over 20 years ago, Watt and Hameroff (1987 ) suggested that consciousness may be described as a manifestation of deterministic chaos in the brain/mind. To analyze EEG-signal complexity, we used Higuchi’s fractal dimension in time domain and symbolic analysis methods. Our results of analysis of EEG-signals under anesthesia, during physiological sleep, and during epileptic seizures lead to a conclusion similar to that of Watt and Hameroff: Brain activity, measured by complexity of the EEG-signal, diminishes (becomes less chaotic) when consciousness is being “switched off”. So, consciousness may be described as a manifestation of deterministic chaos in the brain/mind.


2001 ◽  
Vol 6 (1) ◽  
pp. 26-35 ◽  
Author(s):  
Marja Kokkonen ◽  
Lea Pulkkinen ◽  
Taru Kinnunen

The study was part of the Jyväskylä Longitudinal Study of Personality and Social Development, underway since 1968, in which children's low self-control of emotions was studied using teacher ratings at age 8 in terms of inattentiveness, shifting moods, aggression, and anxiety. The study was based on data from 112 women and 112 men who participated in the previous data collections at ages 8, 27, and 36. At age 27, the participants had been assessed in Neuroticism (N) using the Eysenck Personality Questionnaire , and at age 36 they filled in several inventories measuring, among others, conscious and active attempts to repair negative emotions in a more positive direction as well as physical symptoms. The present study used structural equation modeling to test the hypothesis that personality characteristics indicating low self-control of emotions at ages 8 and 27 are antecedents of self-reported physical symptoms at age 36; and that this relationship is indirect, mediated by attempts to repair negative emotions in a more positive direction. The findings showed, albeit for men only, that inattentiveness at age 8 was positively related to self-reported physical symptoms at age 36 via high N at age 27 and low attempts to repair negative emotions at age 36. Additionally, N at age 27 was directly linked to self-reported physical symptoms at age 36. The mediation of an active attempt to repair negative emotions was not found for women. Correlations revealed, however, that shifting moods and aggression in girls were antecedents of self-reported physical symptoms in adulthood, particularly, pain and fatigue.


1998 ◽  
Vol 14 (3) ◽  
pp. 202-210 ◽  
Author(s):  
Suzanne Skiffington ◽  
Ephrem Fernandez ◽  
Ken McFarland

This study extends previous attempts to assess emotion with single adjective descriptors, by examining semantic as well as cognitive, motivational, and intensity features of emotions. The focus was on seven negative emotions common to several emotion typologies: anger, fear, sadness, shame, pity, jealousy, and contempt. For each of these emotions, seven items were generated corresponding to cognitive appraisal about the self, cognitive appraisal about the environment, action tendency, action fantasy, synonym, antonym, and intensity range of the emotion, respectively. A pilot study established that 48 of the 49 items were linked predominantly to the specific emotions as predicted. The main data set comprising 700 subjects' ratings of relatedness between items and emotions was subjected to a series of factor analyses, which revealed that 44 of the 49 items loaded on the emotion constructs as predicted. A final factor analysis of these items uncovered seven factors accounting for 39% of the variance. These emergent factors corresponded to the hypothesized emotion constructs, with the exception of anger and fear, which were somewhat confounded. These findings lay the groundwork for the construction of an instrument to assess emotions multicomponentially.


Sign in / Sign up

Export Citation Format

Share Document