Emotions States Recognition Based on Physiological Parameters by Employing of Fuzzy-Adaptive Resonance Theory

Monajati, Mahdis; Abbasi, Seyed Hamidreza; Shabaninia, Faridoon; Shamekhi, Sina

doi:10.4236/ijis.2012.224022

Cited by 23 publications

(16 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In this research, the Statistical probability ratio test and Autoassociative neural networks residual values were used to detect changes from a neutral to a nonneutral state and, once a change was detected, determine whether it was negative or positive results from applying proposed methodology on real-time data demonstrated a recognition level of 71.4% which is comparable to the best results achieved by others through offline analysis (Leon et al 2007). The other investigation on negative emotions states recognition was made by Monajati et al (2012). In this research, the three physiological applied signals are galvanic skin response, heart rate and respiration rate.…”

Section: Dependence Of Blood Pressures and Heart Rate On A Person's Ementioning

confidence: 82%

See 1 more Smart Citation

Human Resource Management in Emergency Situations

Peciure¹

2016

View full text Add to dashboard Cite

Vadovas prof. habil. dr. Artūras KAKLAUSKAS (Vilniaus Gedimino technikos universitetas, vadyba-03S). Vilniaus Gedimino technikos universiteto Vadybos mokslo krypties disertacijos gynimo taryba: Pirmininkas prof. habil. dr. Borisas MELNIKAS (Vilniaus Gedimino technikos universitetas, vadyba-03S). Nariai: prof. dr. Eugenijus CHLIVICKAS (Vilniaus Gedimino technikos universitetas, vadyba-03S), dr. Richard HAIGH (Hadersfildo universitetas, vadyba-03S), prof. dr. Bronius NEVERAUSKAS (Kauno technologijos universitetas, vadyba-03S), doc. dr. Jelena STANKEVIČIENĖ (Vilniaus Gedimino technikos universitetas, ekonomika-04S). Disertacija bus ginama viešame Vadybos mokslo krypties disertacijos gynimo tarybos posėdyje 2015 m. lapkričio 13 d. 9 val. Vilniaus Gedimino technikos universiteto senato posėdžių salėje.

show abstract

Section: Dependence Of Blood Pressures and Heart Rate On A Person's Ementioning

confidence: 82%

“…Physiological responses were analysed by Fuzzy Adaptive Resonance Theory to recognize the negative emotions. Detecting negative emotions from neutral is obtained with total accuracy of 94% (Monajati et al 2012).…”

Section: Dependence Of Blood Pressures and Heart Rate On A Person's Ementioning

confidence: 99%

Human Resource Management in Emergency Situations

Peciure¹

2016

View full text Add to dashboard Cite

show abstract

“…Cada indivíduo apresenta um sistema de zonas de aprendizado único, que por sua vez se altera de acordo com as experiências pessoais ao longo da vida. De forma mais elaborada, Monajati et al (2012) aborda o tema, estudando humanos, sob o enfoque dos estímulos serem positivos ou negativos e em qual intensidade (Figura 2). Neste enfoque, o estímulo é definido pela intensidade da emoção, variando de calmo (estímulo baixo) a excitado (estímulo elevado).…”

Section: Distintos Níveis De Estresseunclassified

“…Discretização da interação entre estímulo e emoção, adaptado deMonajati et al (2012). Discretização das interações e intensidades de estímulos e emoções…”

unclassified

Otimizando o desempenho e o bem-estar de equinos usados em atividades esportivas

Schmidek¹

2018

Revista Brasileira De Zoociências

View full text Add to dashboard Cite

Optimizing the performance and welfare of horses in sports activities. Horses are born athletes. Throughout their evolution, they have been trained in a really arduous way, as the less skilled individuals in running and jumping over natural fences -which were on their escape routes from predators -certainly left fewer offspring, if any. Although the domestication of the equines occurred since a long time ago, to this day they continue to present the main characteristics of their ancestral ones: they are group animals, scared and afraid of predators, that feel insecure when alone and that spend much of their day walking and grazing. In nature, it is difficult to identify environments or days in the life of living beings, with the absence of some type or degree of stress. Many of the knowledge and learning of the equines that occur in nature or from human training involve some degree of stress, which indicates to be a trait whose optimal values are intermediate. Regarding skills learned trought some stress degree, it seems that the learning of the horse does not occur when the stress (or pressure) occurs, but at the moment of its relief. Thus, the more immediate the pressure relief, the more efficient the learning will be. There seems to be a consensus that relaxed and motivated horses have improved learning outcomes and more fearful horses are more influenced by the training system. We could sum up in minimal pressure, immediate, long and frequent relief of pressure, repetition of exercises, consistency in asking the exercises, and finish the training section in a positive way, with correctness, even if an easy task as the main strategies or tools for equine training. In practical terms, the best training for each horse involves improving the communication between human and equine, both in terms of understanding the urges and fears of each horse, drawing up an individualized training plan, and adopting rational training techniques.Resumo. Cavalos são atletas natos. Ao longo de sua evolução, foram treinados de forma realmente árdua, pois os indivíduos menos habilidosos em correr e saltar por cima de obstáculos naturais -que haviam em suas rotas de fuga de predadores -certamente deixaram menor número de descendentes, se é que deixaram alguns. Ainda que a domesticação dos equinos tenha ocorrido há muito tempo, até hoje esses animais continuam a apresentar as principais características dos equídeos ancestrais: são sociais, por natureza assustados e com medo de predadores, que se sentem inseguros quando sozinhos e que passam grande parte do dia andando e pastejando. Na natureza, dificilmente se identificam ambientes, ou dias, na vida dos seres vivos em que não tenha havido algum tipo ou grau de estresse. Muitos dos aprendizados dos equinos, quer ocorram na natureza, ou no convívio com humanos, envolvem algum grau de estresse, que indica ser um fenômeno biológico cujo ótimo são valores intermediários. Em aprendizados que envolvam algum grau de estresse, o aprendizado do equino parece não se dar no momento em que ocorre ...

show abstract

“…Furthermore, most subjects become uncomfortable wearing the electrodes all day long when interacting with systems for any given application. Indeed, most physiological signal-based emotion recognition systems have been developed within a controlled laboratory environment, and very few have been developed in real-time scenarios [ 16 , 17 ]. Therefore, recent developments in novel image processing algorithms will likely make facial expression detection more reliable and effective for real-time system development over other modalities.…”

Section: Introductionmentioning

confidence: 99%

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions

Maruthapillai

Murugappan

2016

PLoS ONE

View full text Add to dashboard Cite

In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject’s face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject’s face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.

show abstract

Emotions States Recognition Based on Physiological Parameters by Employing of Fuzzy-Adaptive Resonance Theory

Cited by 23 publications

References 10 publications

Human Resource Management in Emergency Situations

Human Resource Management in Emergency Situations

Otimizando o desempenho e o bem-estar de equinos usados em atividades esportivas

Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions

Contact Info

Product

Resources

About