EmotionEmotions are mental states brought on by neurophysiological changes, variously associated with thoughts, feelings, behavioral responses, and a degree of pleasure or displeasure. There is no scientific consensus on a definition. Emotions are often intertwined with mood, temperament, personality, disposition, or creativity. Research on emotion has increased over the past two decades, with many fields contributing, including psychology, medicine, history, sociology of emotions, and computer science.
Emotion in animalsEmotion is defined as any mental experience with high intensity and high hedonic content. The existence and nature of emotions in non-human animals are believed to be correlated with those of humans and to have evolved from the same mechanisms. Charles Darwin was one of the first scientists to write about the subject, and his observational (and sometimes anecdotal) approach has since developed into a more robust, hypothesis-driven, scientific approach.
Affective computingAffective computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is an interdisciplinary field spanning computer science, psychology, and cognitive science. While some core ideas in the field may be traced as far back as to early philosophical inquiries into emotion, the more modern branch of computer science originated with Rosalind Picard's 1995 paper on affective computing and her book Affective Computing published by MIT Press.
Emotion classificationEmotion classification, the means by which one may distinguish or contrast one emotion from another, is a contested issue in emotion research and in affective science. Researchers have approached the classification of emotions from one of two fundamental viewpoints: that emotions are discrete and fundamentally different constructs that emotions can be characterized on a dimensional basis in groupings In discrete emotion theory, all humans are thought to have an innate set of basic emotions that are cross-culturally recognizable.
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
Discrete emotion theoryDiscrete emotion theory is the claim that there is a small number of core emotions. For example, Silvan Tomkins (1962, 1963) concluded that there are nine basic affects which correspond with what we come to know as emotions: interest, enjoyment, surprise, distress, fear, anger, shame, dissmell (reaction to bad smell) and disgust. More recently, Carroll Izard at the University of Delaware factor analytically delineated 12 discrete emotions labeled: Interest, Joy, Surprise, Sadness, Anger, Disgust, Contempt, Self-Hostility, Fear, Shame, Shyness, and Guilt (as measured via his Differential Emotions Scale or DES-IV).
Emotions and cultureAccording to some theories, emotions are universal phenomena, albeit affected by culture. Emotions are "internal phenomena that can, but do not always, make themselves observable through expression and behavior". While some emotions are universal and are experienced in similar ways as a reaction to similar events across all cultures, other emotions show considerable cultural differences in their antecedent events, the way they are experienced, the reactions they provoke and the way they are perceived by the surrounding society.
Theory of constructed emotionThe theory of constructed emotion (formerly the conceptual act model of emotion) is a theory in affective science proposed by Lisa Feldman Barrett to explain the experience and perception of emotion. The theory posits that instances of emotion are constructed predictively by the brain in the moment as needed. It draws from social construction, psychological construction, and neuroconstruction.
Residual neural networkA Residual Neural Network (a.k.a. Residual Network, ResNet) is a deep learning model in which the weight layers learn residual functions with reference to the layer inputs. A Residual Network is a network with skip connections that perform identity mappings, merged with the layer outputs by addition. It behaves like a Highway Network whose gates are opened through strongly positive bias weights. This enables deep learning models with tens or hundreds of layers to train easily and approach better accuracy when going deeper.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
AutoencoderAn autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning). An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation. The autoencoder learns an efficient representation (encoding) for a set of data, typically for dimensionality reduction. Variants exist, aiming to force the learned representations to assume useful properties.
Emotion recognitionEmotion recognition is the process of identifying human emotion. People vary widely in their accuracy at recognizing the emotions of others. Use of technology to help people with emotion recognition is a relatively nascent research area. Generally, the technology works best if it uses multiple modalities in context. To date, the most work has been conducted on automating the recognition of facial expressions from video, spoken expressions from audio, written expressions from text, and physiology as measured by wearables.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Affect (psychology)Affect, in psychology, refers to the underlying experience of feeling, emotion, attachment, or mood. The modern conception of affect developed in the 19th century with Wilhelm Wundt. The word comes from the German Gefühl, meaning "feeling". A number of experiments have been conducted in the study of social and psychological affective preferences (i.e., what people like or dislike). Specific research has been done on preferences, attitudes, impression formation, and decision-making.
Facial expressionA facial expression is one or more motions or positions of the muscles beneath the skin of the face. According to one set of controversial theories, these movements convey the emotional state of an individual to observers. Facial expressions are a form of nonverbal communication. They are a primary means of conveying social information between humans, but they also occur in most other mammals and some other animal species. (For a discussion of the controversies on these claims, see Fridlund and Russell & Fernandez Dols.
EducationEducation is the transmission of knowledge, skills, and character traits. There are many debates about its precise definition, for example, about which aims it tries to achieve. A further issue is whether part of the meaning of education is that the change in the student is an improvement. Some researchers stress the role of critical thinking to distinguish education from indoctrination. These disagreements affect how to identify, measure, and improve forms of education.
Types of artificial neural networksThere are many types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate functions that are generally unknown. Particularly, they are inspired by the behaviour of neurons and the electrical signals they convey between input (such as from the eyes or nerve endings in the hand), processing, and output from the brain (such as reacting to light, touch, or heat). The way neurons semantically communicate is an area of ongoing research.
Cardiac arrestCardiac arrest occurs when the heart stops beating. It is defined as cessation of normal circulation of blood due to failure of the heart to pump effectively. It is a medical emergency that, without immediate medical intervention, will result in cardiac death within minutes. When it happens suddenly, it is called sudden cardiac arrest. Cardiopulmonary resuscitation (CPR) and possibly defibrillation are needed until further treatment can be provided. Cardiac arrest results in a rapid loss of consciousness, and breathing may be abnormal or absent.
Affective scienceAffective science is the scientific study of emotion or affect. This includes the study of emotion elicitation, emotional experience and the recognition of emotions in others. Of particular relevance are the nature of feeling, mood, emotionally-driven behaviour, decision-making, attention and self-regulation, as well as the underlying physiology and neuroscience of the emotions. An increasing interest in emotion can be seen in the behavioral, biological and social sciences.
Cardiac outputIn cardiac physiology, cardiac output (CO), also known as heart output and often denoted by the symbols , , or , is the volumetric flow rate of the heart's pumping output: that is, the volume of blood being pumped by a single ventricle of the heart, per unit time (usually measured per minute). Cardiac output (CO) is the product of the heart rate (HR), i.e. the number of heartbeats per minute (bpm), and the stroke volume (SV), which is the volume of blood pumped from the left ventricle per beat; thus giving the formula: Values for cardiac output are usually denoted as L/min.
