ABSTRACT
In psychiatry, observation of the patients is often an important basis for making a diagnosis during clinical practice. However, changes in emotional facial expressions are often subtle and difficult to detect. For this reason, automated facial expression recognition can be used to assist in identifying mental disorders. Facial expression is one of the important ways of emotional expression, and strong similarities of basic human facial expression are not affected by cultural background or congenital blindness. With the development of computer science, facial expression recognition methods are also constantly improving. Among them, deep-learning-based facial expression recognition approaches, with their powerful information processing capabilities, highly reduce the dependence on face-physics-based models and other pre-processing techniques by using trainable feature extraction models to automatically learn representations from images and videos. This article focuses on the progress of facial expression recognition system in the diagnosis and treatment of schizophrenia, depression, borderline personality disorder, autism spectrum disorder and other diseases. This article also explores the application of facial expression recognition technology in the field of psychiatry and remote psychology intervention.
ABSTRACT
BACKGROUND@#The facial expression of medical staff has been known to greatly affect the psychological state of patients, making them feel uneasy or conversely, cheering them up. By clarifying the characteristics of facial expression recognition ability in patients with Lewy body disease, the aim of this study is to examine points to facilitate smooth communication between caregivers and patients with the disease whose cognitive function has deteriorated.@*METHODS@#During the period from March 2016 to July 2017, we examined the characteristics of recognition of the six facial expressions of "happiness," "sadness," "fear," "anger," "surprise," and "disgust" for 107 people aged 60 years or more, both outpatient and inpatient, who hospital specialists had diagnosed with Lewy body diseases of Parkinson's disease, Parkinson's disease with dementia, and dementia with Lewy bodies. Based on facial expression recognition test results, we classified them by cluster analysis and clarified features of each type.@*RESULTS@#In patients with Lewy body disease, happiness was kept unaffected by aging, age of onset, duration of the disease, cognitive function, and apathy; however, recognizing the facial expression of fear was difficult. In addition, due to aging, cognitive decline, and apathy, the facial expression recognition ability for sadness and anger decreased. In particular, cognitive decline reduced recognition of all of the facial expressions except for happiness. The test accuracy rates were classified into three types using the cluster analysis: "stable type," "mixed type," and "reduced type". In the "reduced type", the overall facial recognition ability declined except happiness, and in the mixed type, recognition ability of anger particularly declined.@*CONCLUSION@#There were several facial expressions that the Lewy body disease patients were unable to accurately identify. Caregivers are recommended to make an effort to compensate for such situations with language or body contact, etc., as a way to convey correct feeling to the patients of each type.
Subject(s)
Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Cluster Analysis , Cognition , Physiology , Emotions , Facial Expression , Facial Recognition , Physiology , Lewy Body Disease , PsychologyABSTRACT
Facial recognition is one of the most important aspects of social cognition. In this study, we investigate the patterns of change and the factors involved in the ability to recognize emotion in mild Alzheimer’s disease (AD). Through a longitudinal design, we assessed 30 people with AD. We used an experimental task that includes matching expressions with picture stimuli, labelling emotions and emotionally recognizing a stimulus situation. We observed a significant difference in the situational recognition task (p ≤ 0.05) between baseline and the second evaluation. The linear regression showed that cognition is a predictor of emotion recognition impairment (p ≤ 0.05). The ability to perceive emotions from facial expressions was impaired, particularly when the emotions presented were relatively subtle. Cognition is recruited to comprehend emotional situations in cases of mild dementia.
O reconhecimento da expressão facial é um dos aspectos mais importantes relacionados à cognição social. Foram investigados os padrões de mudança e os fatores envolvidos na habilidade de reconhecer emoções na doença de Alzheimer (DA) leve. Em um estudo longitudinal foram avaliadas 30 pessoas com DA. Para a avaliação da capacidade de reconhecimento facial na DA foi utilizada uma tarefa experimental que inclui a combinação de expressões com uma figura estímulo, rotulação da emoção e reconhecimento emocional de uma situação estímulo. Foi encontrada diferença significativa entre os momentos 1 e 2 na tarefa de reconhecimento situacional (p ≤ 0.05). A regressão linear mostrou que a cognição (p ≤ 0.05) é o fator preditor para o prejuízo do reconhecimento emocional, o que sugere um recrutamento da cognição para a compreensão de situações emocionais mais complexas. Houve comprometimento na percepção de emoções em expressões faciais, particularmente, quando as emoções eram sutis.
Subject(s)
Aged , Aged, 80 and over , Female , Humans , Male , Alzheimer Disease/psychology , Cognition/physiology , Emotions/physiology , Facial Expression , Recognition, Psychology , Alzheimer Disease/physiopathology , Epidemiologic Methods , Neuropsychological Tests , Quality of Life , Task Performance and Analysis , Time FactorsABSTRACT
El intercambio emocional humano implica expresión/reconocimiento de emociones. La cara es el lugar privilegiado para expresar o leer la emoción. Algunas emociones se asocian con llanto emocional, diferenciable del basal y del reflejo. Murube, Murube y Murube (1999) clasificaron el llanto emocional en de demanda y de ofrecimiento de ayuda. Se evaluó la validez de dicha tipología empleando rostros humanos de ambos sexos que lloraban por dolor propio y ajeno. Un grupo de jueces clasificó el llanto expresado en esos rostros. Se calcularon tasas de acierto de discriminación de llanto y se realizaron pruebas chi-cuadro por sexo. Los resultados no apoyan la idea de una habilidad para distinguir dos tipos de llanto y son explicados desde un punto de vista cultural.
Human emotional interchange implicates expression/recognition of emotions. The human face is a conspicuous place to express/read emotion. Certain emotions associate with emotional tearing, differentiable from basal and reflex tearing. Murube, Murube and Murube (1999) classified emotional tearing in requesting- and offering -help. The validity of that typology was evaluated using faces of people of both sexes crying because of their own suffering and because of others suffering. A group of judges classified the crying shown by those faces. Discrimination hit rates andqui-square tests were estimated by sex. Results do not support a human ability to distinguish two types of crying andare interpreted from a cultural point of view.