scholarly journals Measurement of emotional states of zebrafish through integrated analysis of motion and respiration using bioelectric signals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zu Soh ◽  
Motoki Matsuno ◽  
Masayuki Yoshida ◽  
Akira Furui ◽  
Toshio Tsuji
Keyword(s):  
Alarm Pheromone ◽  
Emotional State ◽  
Electrode Array ◽  
Principal Component ◽  
Integrated Analysis ◽  
Anxiety State ◽  
Emotional States ◽  
Real Time Analysis ◽  
Bioelectric Signals ◽  
Analysis Of Motion

AbstractFear, anxiety, and preference in fish are generally evaluated by video-based behavioural analyses. We previously proposed a system that can measure bioelectrical signals, called ventilatory signals, using a 126-electrode array placed at the bottom of an aquarium and achieved cameraless real-time analysis of motion and ventilation. In this paper, we propose a method to evaluate the emotional state of fish by combining the motion and ventilatory indices obtained with the proposed system. In the experiments, fear/anxiety and appetitive behaviour were induced using alarm pheromone and ethanol, respectively. We also found that the emotional state of the zebrafish can be expressed on the principal component (PC) space extracted from the defined indices. The three emotional states were discriminated using a model-based machine learning method by feeding the PCs. Based on discrimination performed every 5 s, the F-score between the three emotional states were as follows: 0.84 for the normal state, 0.76 for the fear/anxiety state, and 0.59 for the appetitive behaviour. These results indicate the effectiveness of combining physiological and motional indices to discriminate the emotional states of zebrafish.

scholarly journals Investigation of a Standardized Qualitative Behaviour Assessment and Exploration of Potential Influencing Factors on the Emotional State of Dairy Calves

Animals ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 757 ◽  
Author(s):  
Marta Brscic ◽  
Nina Dam Otten ◽  
Barbara Contiero ◽  
Marlene Katharina Kirchner
Keyword(s):  
Linear Models ◽  
Emotional State ◽  
Standard Procedure ◽  
Behavioral Assessment ◽  
Principal Component ◽  
Observer Agreement ◽  
Dairy Calves ◽  
Emotional States ◽  
Mixed Linear Models ◽  
Explained Variation

Assessing emotional states of dairy calves is an essential part of welfare assessment, but standardized protocols are absent. The present study aims at assessing the emotional states of dairy calves and establishing a reliable standard procedure with Qualitative Behavioral Assessment (QBA) and 20 defined terms. Video material was used to compare multiple observer results. Further, live observations were performed on 49 dairy herds in Denmark and Italy. Principal Component Analysis (PCA) identified observer agreement and QBA dimensions (PC). For achieving overall welfare judgment, PC1-scores were turned into the Welfare Quality (WQ) criterion ‘Positive Emotional State’. Finally, farm factors’ influence on the WQ criterion was evaluated by mixed linear models. PCA summarized QBA descriptors as PC1 ‘Valence’ and PC2 ‘Arousal’ (explained variation 40.3% and 13.3%). The highest positive descriptor loadings on PC1 was Happy (0.92) and Nervous (0.72) on PC2. The WQ-criterion score (WQ-C12) was on average 51.1 ± 9.0 points (0: worst to 100: excellent state) and ‘Number of calves’, ‘Farming style’, and ‘Breed’ explained 18% of the variability of it. We conclude that the 20 terms achieved a high portion of explained variation providing a differentiated view on the emotional state of calves. The defined term list proved to need good training for observer agreement.

scholarly journals Therapists’ emotional state after sessions in which suicidality is addressed: need for improved management of suicidal tendencies in patients with borderline personality pathology

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Vera Bühlmann ◽  
Susanne Schlüter-Müller ◽  
Lukas Fürer ◽  
Martin Steppan ◽  
Marc Birkhölzer ◽  
...  
Keyword(s):  
Emotional State ◽  
Therapeutic Process ◽  
Principal Component ◽  
Borderline Personality ◽  
Personality Pathology ◽  
Emotional States ◽  
Difficult Situation ◽  
Session Evaluation ◽  
Therapist Response ◽  
Suicidal Patients

Abstract Introduction Patient suicidality is a frequently experienced topic for psychotherapists. Especially adolescents with borderline personality pathology (BPP) often exhibit suicidal tendencies. Previous research which examined therapists’ countertransference towards suicidal patients suggested that therapists are negatively affected and distressed by them. We hypothesize that this emotional response of the therapists is related to specific sessions in which suicidality came up as a topic. Accordingly, the objective of this study consists in examining therapists’ emotional state on a session level of analysis. Methods The sample consisted of N = 21 adolescents (age 13–19 years) with BPD or subthreshold BPD. Therapists’ emotional states were measured in n = 418 sessions using the Session Evaluation Questionnaire. Principal component analysis was used to reduce dimensionality of the therapist response. The emotional states were compared depending on whether suicidality has been addressed in the session (SS) or not (NSS). Results Two components could be identified. Firstly, therapists were more aroused, excited, afraid, angry and uncertain after SS than after NSS. Secondly, therapists were more aroused, excited, definite and pleased after SS than after NSS. Discussion: Suicidality does not always have to be a burden for therapists: Both a “distress” and an “eustress” component occur in this context from which the latter is supposed to help clinicians master a difficult situation. Since countertransference feelings are often not fully conscious, it is necessary to do research on therapists’ emotional states after sessions in which suicidality is addressed. This is crucial to both prevent the therapeutic process from being endangered and preserve clinicians’ mental health. Clinical implications and limitations are discussed.

scholarly journals Emotion recognition using Kinect motion capture data of human gaits

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2364 ◽  
Author(s):  
Shun Li ◽  
Liqing Cui ◽  
Changye Zhu ◽  
Baobin Li ◽  
Nan Zhao ◽  
...  
Keyword(s):  
Emotion Recognition ◽  
Emotional State ◽  
Low Cost ◽  
Information Source ◽  
Principal Component ◽  
Microsoft Kinect ◽  
Main Body ◽  
Emotional States ◽  
System Transformation ◽  
Neutral State

Automatic emotion recognition is of great value in many applications, however, to fully display the application value of emotion recognition, more portable, non-intrusive, inexpensive technologies need to be developed. Human gaits could reflect the walker’s emotional state, and could be an information source for emotion recognition. This paper proposed a novel method to recognize emotional state through human gaits by using Microsoft Kinect, a low-cost, portable, camera-based sensor. Fifty-nine participants’ gaits under neutral state, induced anger and induced happiness were recorded by two Kinect cameras, and the original data were processed through joint selection, coordinate system transformation, sliding window gauss filtering, differential operation, and data segmentation. Features of gait patterns were extracted from 3-dimentional coordinates of 14 main body joints by Fourier transformation and Principal Component Analysis (PCA). The classifiers NaiveBayes, RandomForests, LibSVM and SMO (Sequential Minimal Optimization) were trained and evaluated, and the accuracy of recognizing anger and happiness from neutral state achieved 80.5% and 75.4%. Although the results of distinguishing angry and happiness states were not ideal in current study, it showed the feasibility of automatically recognizing emotional states from gaits, with the characteristics meeting the application requirements.

Effect of Emotions in a Lexical Decision Task

2017 ◽  
Vol 76 (2) ◽  
pp. 71-79 ◽  
Author(s):  
Hélène Maire ◽  
Renaud Brochard ◽  
Jean-Luc Kop ◽  
Vivien Dioux ◽  
Daniel Zagar
Keyword(s):  
Lexical Decision ◽  
Lexical Decision Task ◽  
Emotional State ◽  
Control Group ◽  
Decision Task ◽  
Attentional Orienting ◽  
Emotional States ◽  
Sequence Effect ◽  
Emotion Induction ◽  
Before And After

Abstract. This study measured the effect of emotional states on lexical decision task performance and investigated which underlying components (physiological, attentional orienting, executive, lexical, and/or strategic) are affected. We did this by assessing participants’ performance on a lexical decision task, which they completed before and after an emotional state induction task. The sequence effect, usually produced when participants repeat a task, was significantly smaller in participants who had received one of the three emotion inductions (happiness, sadness, embarrassment) than in control group participants (neutral induction). Using the diffusion model ( Ratcliff, 1978 ) to resolve the data into meaningful parameters that correspond to specific psychological components, we found that emotion induction only modulated the parameter reflecting the physiological and/or attentional orienting components, whereas the executive, lexical, and strategic components were not altered. These results suggest that emotional states have an impact on the low-level mechanisms underlying mental chronometric tasks.

scholarly journals Dogs can infer implicit information from human emotional expressions

2021 ◽  
Author(s):  
Natalia Albuquerque ◽  
Daniel S. Mills ◽  
Kun Guo ◽  
Anna Wilkinson ◽  
Briseida Resende
Keyword(s):  
Emotional State ◽  
Food Resource ◽  
Emotional Expressions ◽  
Emotional States ◽  
Emotional Information ◽  
Implicit Information ◽  
Emotional Display ◽  
Affective Information ◽  
Social Decision Making ◽  
Current Behaviour

AbstractThe ability to infer emotional states and their wider consequences requires the establishment of relationships between the emotional display and subsequent actions. These abilities, together with the use of emotional information from others in social decision making, are cognitively demanding and require inferential skills that extend beyond the immediate perception of the current behaviour of another individual. They may include predictions of the significance of the emotional states being expressed. These abilities were previously believed to be exclusive to primates. In this study, we presented adult domestic dogs with a social interaction between two unfamiliar people, which could be positive, negative or neutral. After passively witnessing the actors engaging silently with each other and with the environment, dogs were given the opportunity to approach a food resource that varied in accessibility. We found that the available emotional information was more relevant than the motivation of the actors (i.e. giving something or receiving something) in predicting the dogs’ responses. Thus, dogs were able to access implicit information from the actors’ emotional states and appropriately use the affective information to make context-dependent decisions. The findings demonstrate that a non-human animal can actively acquire information from emotional expressions, infer some form of emotional state and use this functionally to make decisions.

An experimental study on the effect of emotion lines in comics

Semiotica ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Amitash Ojha ◽  
Charles Forceville ◽  
Bipin Indurkhya
Keyword(s):  
Experimental Study ◽  
Emotional State ◽  
Negative Emotions ◽  
Emotional States ◽  
One To One

Abstract Both mainstream and art comics often use various flourishes surrounding characters’ heads. These so-called “pictorial runes” (also called “emanata”) help convey the emotional states of the characters. In this paper, using (manipulated) panels from Western and Indian comic albums as well as neutral emoticons and basic shapes in different colors, we focus on the following two issues: (a) whether runes increase the awareness in comics readers about the emotional state of the character; and (b) whether a correspondence can be found between the types of runes (twirls, spirals, droplets, and spikes) and specific emotions. Our results show that runes help communicate emotion. Although no one-to-one correspondence was found between the tested runes and specific emotions, it was found that droplets and spikes indicate generic emotions, spirals indicate negative emotions, and twirls indicate confusion and dizziness.

scholarly journals The role of emotional service in the restaurant business

2022 ◽  
pp. 164-167
Author(s):  
N. A. Ofitserova
Keyword(s):  
Emotional Intelligence ◽  
Customer Satisfaction ◽  
Emotional Labor ◽  
Work Performance ◽  
Positive Emotions ◽  
Emotional State ◽  
Communicative Competence ◽  
Point Of View ◽  
Emotional States

The article considers the restaurant business from the point of view of not only the entrepreneurial aspect, but also the service aspect, which is fundamental. The reasons why people visit restaurants have been revealed. In addition to physical need, restaurants are an element of cognition and a way of experiencing positive emotions. The importance of the restaurant business in shaping people’s positive emotional state has been formulated. Two forms of emotional labor of an employee and the influence of emotional states on work performance have been highlighted. The role of emotional intelligence and communicative competence in customer satisfaction with a restaurant visit has been determined. The importance of developing emotional intelligence has been concluded. Recommendations for its development has been formulated. 

scholarly journals Speech-based human emotion recognition

2021 ◽  
Author(s):  
Talieh Seyed Tabtabae
Keyword(s):  
Emotion Recognition ◽  
Emotional State ◽  
Speaker Identification ◽  
Recognition System ◽  
Research Area ◽  
Speech Signals ◽  
Spectral Features ◽  
Emotional States ◽  
Human Communication ◽  
Set Up

Automatic Emotion Recognition (AER) is an emerging research area in the Human-Computer Interaction (HCI) field. As Computers are becoming more and more popular every day, the study of interaction between humans (users) and computers is catching more attention. In order to have a more natural and friendly interface between humans and computers, it would be beneficial to give computers the ability to recognize situations the same way a human does. Equipped with an emotion recognition system, computers will be able to recognize their users' emotional state and show the appropriate reaction to that. In today's HCI systems, machines can recognize the speaker and also content of the speech, using speech recognition and speaker identification techniques. If machines are equipped with emotion recognition techniques, they can also know "how it is said" to react more appropriately, and make the interaction more natural. One of the most important human communication channels is the auditory channel which carries speech and vocal intonation. In fact people can perceive each other's emotional state by the way they talk. Therefore in this work the speech signals are analyzed in order to set up an automatic system which recognizes the human emotional state. Six discrete emotional states have been considered and categorized in this research: anger, happiness, fear, surprise, sadness, and disgust. A set of novel spectral features are proposed in this contribution. Two approaches are applied and the results are compared. In the first approach, all the acoustic features are extracted from consequent frames along the speech signals. The statistical values of features are considered to constitute the features vectors. Suport Vector Machine (SVM), which is a relatively new approach in the field of machine learning is used to classify the emotional states. In the second approach, spectral features are extracted from non-overlapping logarithmically-spaced frequency sub-bands. In order to make use of all the extracted information, sequence discriminant SVMs are adopted. The empirical results show that the employed techniques are very promising.

scholarly journals Engineering Emotionally Intelligent Agents

2011 ◽  
pp. 99-117
Author(s):  
Penny Baillie ◽  
Mark Toleman ◽  
Dickson Lukose
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Emotional State ◽  
Psychological Theory ◽  
Emotional States ◽  
Changing Environment ◽  
Emotionally Intelligent ◽  
Over Time ◽  
The Way

Interacting with intelligence in an ever-changing environment calls for exceptional performances from artificial beings. One mechanism explored to produce intuitive-like behavior in artificial intelligence applications is emotion. This chapter examines the engineering of a mechanism that synthesizes and processes an artificial agent’s internal emotional states: the Affective Space. Through use of the affective space, an agent can predict the effect certain behaviors will have on its emotional state and, in turn, decide how to behave. Furthermore, an agent can use the emotions produced from its behavior to update its beliefs about particular entities and events. This chapter explores the psychological theory used to structure the affective space, the way in which the strength of emotional states can be diminished over time, how emotions influence an agent’s perception, and the way in which an agent can migrate from one emotional state to another.

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