Impairment in the Recognition of Facial Expression: A Case Study

2009 ◽  
Vol 105 (1) ◽  
pp. 232-234
Author(s):  
Ayumu Goukon ◽  
Toru Suzuki ◽  
Kazuhito Noguchi
Keyword(s):  
Facial Expression ◽  
Everyday Life ◽  
Facial Expressions ◽  
Vegetative State ◽  
Persistent Vegetative State ◽  
Normal Controls

In this study, a case (HY) is described. This man, now 25 yr. old, lived in a persistent vegetative state for 6 yr. after encephalitis at the age of 10 yr. He was reportedly impaired at recognizing fear, and in everyday life, apparently had impaired recognition of anger as well. In testing with facial expressions, no obvious differences between HY and normal controls in anger perceptions were found. In this study, Japanese and Caucasian models of facial expression were used; on these tests, HY was impaired at recognizing facial expressions of anger only in the Japanese models.

Is Processing Emotional Signals Necessary for Performance on Tasks Requiring Understanding a “Theory of Mind”

2007 ◽  
Vol 101 (2) ◽  
pp. 469-474
Author(s):  
Ayumu Goukon ◽  
Kazuhito Noguchi ◽  
Toru Hosokawa
Keyword(s):  
Theory Of Mind ◽  
Facial Expressions ◽  
Vegetative State ◽  
Persistent Vegetative State ◽  
Neural Systems ◽  
Gambling Task ◽  
Meaningful Information

In this case study, HY had lived in a persistent vegetative state for 6 years after onset of encephalitis at age 10. His processing of emotionally and socially meaningful information was impaired by the age of 20, as it is in individuals with amygdala damage; however, his performance on tasks requiring understanding a “theory of mind” improved by age 22. A series of responses to photographs of facial expressions and to a gambling task were obtained to evaluate his functioning related to the amygdala. He was particularly impaired in recognizing fear. One may tentatively suggest that processing emotional signals, i.e., functioning related to the amygdala, may not play an important role in the neural systems supporting development of understanding a “theory of mind.”

scholarly journals 3D Facial Expression Recognition for Defining Users’ Inner Requirements—An Emotional Design Case Study

2019 ◽  
Vol 9 (11) ◽  
pp. 2218 ◽  
Author(s):  
Maria Grazia Violante ◽  
Federica Marcolin ◽  
Enrico Vezzetti ◽  
Luca Ulrich ◽  
Gianluca Billia ◽  
...  
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Quality Function Deployment ◽  
Three Dimensional ◽  
Support Vector ◽  
Expression Recognition ◽  
Emotional Design ◽  
3D Data

This study proposes a novel quality function deployment (QFD) design methodology based on customers’ emotions conveyed by facial expressions. The current advances in pattern recognition related to face recognition techniques have fostered the cross-fertilization and pollination between this context and other fields, such as product design and human-computer interaction. In particular, the current technologies for monitoring human emotions have supported the birth of advanced emotional design techniques, whose main focus is to convey users’ emotional feedback into the design of novel products. As quality functional deployment aims at transforming the voice of customers into engineering features of a product, it appears to be an appropriate and promising nest in which to embed users’ emotional feedback with new emotional design methodologies, such as facial expression recognition. This way, the present methodology consists in interviewing the user and acquiring his/her face with a depth camera (allowing three-dimensional (3D) data), clustering the face information into different emotions with a support vector machine classificator, and assigning customers’ needs weights relying on the detected facial expressions. The proposed method has been applied to a case study in the context of agriculture and validated by a consortium. The approach appears sound and capable of collecting the unconscious feedback of the interviewee.

Relative preservation of the recognition of positive facial expression “happiness” in Alzheimer disease

2012 ◽  
Vol 25 (1) ◽  
pp. 105-110 ◽  
Author(s):  
Yohko Maki ◽  
Hiroshi Yoshida ◽  
Tomoharu Yamaguchi ◽  
Haruyasu Yamaguchi
Keyword(s):  
Alzheimer Disease ◽  
Facial Expression ◽  
Facial Expressions ◽  
The Other ◽  
Spatial Processing ◽  
Facial Features ◽  
Confounding Factors ◽  
Verbal Processing ◽  
Verbal Labels ◽  
Normal Controls

ABSTRACTBackground:Positivity recognition bias has been reported for facial expression as well as memory and visual stimuli in aged individuals, whereas emotional facial recognition in Alzheimer disease (AD) patients is controversial, with possible involvement of confounding factors such as deficits in spatial processing of non-emotional facial features and in verbal processing to express emotions. Thus, we examined whether recognition of positive facial expressions was preserved in AD patients, by adapting a new method that eliminated the influences of these confounding factors.Methods:Sensitivity of six basic facial expressions (happiness, sadness, surprise, anger, disgust, and fear) was evaluated in 12 outpatients with mild AD, 17 aged normal controls (ANC), and 25 young normal controls (YNC). To eliminate the factors related to non-emotional facial features, averaged faces were prepared as stimuli. To eliminate the factors related to verbal processing, the participants were required to match the images of stimulus and answer, avoiding the use of verbal labels.Results:In recognition of happiness, there was no difference in sensitivity between YNC and ANC, and between ANC and AD patients. AD patients were less sensitive than ANC in recognition of sadness, surprise, and anger. ANC were less sensitive than YNC in recognition of surprise, anger, and disgust. Within the AD patient group, sensitivity of happiness was significantly higher than those of the other five expressions.Conclusions:In AD patient, recognition of happiness was relatively preserved; recognition of happiness was most sensitive and was preserved against the influences of age and disease.

scholarly journals Severe Hypoglycemia Due To the Administration of Bromocriptine in a Non-diabetic Patient: A Case Study

2020 ◽  
Author(s):  
Saeed Choobkar ◽  
Samad Nazarpoor ◽  
Mojgan Kaviani
Keyword(s):  
Diabetic Patient ◽  
Vegetative State ◽  
Persistent Vegetative State ◽  
Severe Hypoglycemia ◽  
Clonic Seizure ◽  
Unusual Complication ◽  
Intravenous Antibiotic ◽  
Peg Tube ◽  
Car Accident

The patient was a 24-year-old man with persistent vegetative state following severe traumatic brain injury due to a car accident, who was referred to the emergency department with ageneralized tonic-clonic seizure due to severe hypoglycemia. The patient was treated with phenytoin, levetiracetam, bromocriptine and enoxaparine. The patient was transferred to theIntensive Care Unit (ICU) for accurate monitoring. The patient in the ICU was treated with 100 cc/h of Dextrose 10% plus Intravenous antibiotic to treat urinary tract infection induced sepsis. The previous prescribed medications were also prescribed. Despite proper feeding through PEG tube and receiving 100 cc/h of Dextrose 10%, the patient’s blood glucose was dropped frequently below 50 mg/dl and hypertonic glucose infusion was several times required for treatment of hypoglycemia. Administration of bromocriptine as antidiabetic agent waseliminated after consultation with a neurologist surgeon. After bromocriptine discontinuation, hypoglycemia was resolved. In this non-diabetic patient, severe hypoglycemia occurred afteradministration of bromocriptine, which was an unusual complication in the non-diabetic patient treated with bromocriptine.

scholarly journals Driver Facial Expression Analysis Using LFA-CRNN-Based Feature Extraction for Health-Risk Decisions

2020 ◽  
Vol 10 (8) ◽  
pp. 2956 ◽  
Author(s):  
Chang-Min Kim ◽  
Ellen J. Hong ◽  
Kyungyong Chung ◽  
Roy C. Park
Keyword(s):  
Feature Extraction ◽  
Facial Expression ◽  
Health Risk ◽  
Everyday Life ◽  
Facial Expressions ◽  
Health Risks ◽  
Line Segment ◽  
Emotional State ◽  
Feature Analysis ◽  
Facial Expression Analysis

As people communicate with each other, they use gestures and facial expressions as a means to convey and understand emotional state. Non-verbal means of communication are essential to understanding, based on external clues to a person’s emotional state. Recently, active studies have been conducted on the lifecare service of analyzing users’ facial expressions. Yet, rather than a service necessary for everyday life, the service is currently provided only for health care centers or certain medical institutions. It is necessary to conduct studies to prevent accidents that suddenly occur in everyday life and to cope with emergencies. Thus, we propose facial expression analysis using line-segment feature analysis-convolutional recurrent neural network (LFA-CRNN) feature extraction for health-risk assessments of drivers. The purpose of such an analysis is to manage and monitor patients with chronic diseases who are rapidly increasing in number. To prevent automobile accidents and to respond to emergency situations due to acute diseases, we propose a service that monitors a driver’s facial expressions to assess health risks and alert the driver to risk-related matters while driving. To identify health risks, deep learning technology is used to recognize expressions of pain and to determine if a person is in pain while driving. Since the amount of input-image data is large, analyzing facial expressions accurately is difficult for a process with limited resources while providing the service on a real-time basis. Accordingly, a line-segment feature analysis algorithm is proposed to reduce the amount of data, and the LFA-CRNN model was designed for this purpose. Through this model, the severity of a driver’s pain is classified into one of nine types. The LFA-CRNN model consists of one convolution layer that is reshaped and delivered into two bidirectional gated recurrent unit layers. Finally, biometric data are classified through softmax. In addition, to evaluate the performance of LFA-CRNN, the performance was compared through the CRNN and AlexNet Models based on the University of Northern British Columbia and McMaster University (UNBC-McMaster) database.

scholarly journals Nasal thermal activity during voluntary facial expression in a patient with chronic pain and alexithymia

2018 ◽  
Vol 4 ◽  
pp. 25
Author(s):  
David Alberto Rodriguez Medina ◽  
Benjamín Domínguez Trejo ◽  
Irving Armando Cruz Albarrán ◽  
Luis Morales Hernández ◽  
Gerardo Leija Alva ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Facial Expression ◽  
Facial Expressions ◽  
Thermal Activity ◽  
Thermal Variation ◽  
Clinical Context ◽  
Facial Movements ◽  
Priority Needs ◽  
Thermal Variability

The presence of alexithymia (difficulty in recognizing and expressing emotions and feelings) is one of the psychological factors that has been studied in patients with chronic pain. Different psychological strategies have been used for its management; however, none of them regulates the autonomic activity. We present the case of a 74-year-old female patient diagnosed with rheumatoid arthritis with alexithymia. For twelve years he has been taking pregabalin for pain. The main objective of this case study was to perform a biopsychosocial evaluation of pain (level of interleukin 6 concentration, to evaluate the inflammatory appearance, psychophysiological nasal thermal evaluation and psychosocial measures associated with pain). He was presented videos with affective scenes of various emotions (joy, sadness, fear, pain, anger). The results show that, when the patient observes the videos, there is little nasal thermal variability. However, when facial movements are induced for 10 seconds of a facial expression, a thermal variation is reached around 1 ° C. The induced facial expressions that decrease the temperature are those of anger and pain, which coincide with the priority needs of the patient according to the biopsychosocial profile. The results are discussed in the clinical context of the use of facial expressions to promote autonomic regulation in this population.

The twins: a case study in ethical deliberation

2009 ◽  
Vol 16 (1) ◽  
pp. 127-130 ◽  
Author(s):  
Wyona Freysteinson
Keyword(s):  
Ethical Dilemma ◽  
Vegetative State ◽  
Persistent Vegetative State ◽  
Ethical Framework ◽  
Nursing Theory ◽  
Human Becoming

A case study of an ethical dilemma concerning twin nine-year-old sisters in a persistent vegetative state is presented. This is illustrated by the use of a systematic ethical framework to examine the case and the resolution, which was ultimately obtained with nurse—parent interrelations, using the human becoming nursing theory.

Persistent vegetative state in head injury

2005 ◽  
Vol 2 (2) ◽  
pp. 81-85
Author(s):  
Deepak Kumar Gupta ◽  
AK Mahapatra
Keyword(s):  
Head Injury ◽  
Vegetative State ◽  
Persistent Vegetative State
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