Emotional State Of Mind Research Articles

Perioperative Staff’s Experiences of Premedication for Children

PurposeProviding perioperative care for children who express anxiety or react with negative anxiety-associated consequences can be a challenge. The use of premedication is established as an important intervention for young children before surgery, yet research into care providers’ experiences of premedication is limited. The aim of this study was to explore perioperative staff’s experiences of premedication for preschool-age children. DesignA descriptive inductive qualitative study was performed based on focus group discussions. MethodsA purposive sample of a team from the operating department with experience in anesthetizing and caring for children in the perioperative period was interviewed in small focus groups: five preoperative and postoperative care nurses, five nurse anesthetists, and five anesthesiologists. The transcribed text was categorized using qualitative content analysis. FindingsThe content analysis revealed three themes: a matter of time, do not wake the sleeping bear, and on responsive tiptoes. ConclusionsCare providers must adapt their work to the child’s emotional state of mind and needs, allowing time for the child to trust and accept the premedication and for the premedication to reach its peak effect. Premedication provides light sleep preoperatively, which requires careful treatment of the child to avoid emotional reactions, and the postoperative path is most peaceful when the premedication supports a long duration of sedation. Our findings highlight the need for safety precautions and a permissive and flexible organization with the goal of achieving a smooth and safe journey for the child in the perioperative path.

Survey on A Smart Medical System on Drug Analysis using ML Algorithms

Online health communities continue to offer huge variety of medical information useful for medical practitioners, system administrators and patients alike. In this system we collect real time health posts from reputed websites, where patients express their views, including their experiences and side-effects on drugs used by them. We propose to perform Summarization of user posts per drug, and come out with useful conclusions for medical fraternity as well as patient community at a glance. Further, we propose to classify the users based on their ‘emotional state of mind’. Also, we shall perform knowledge discovery from user posts, whereby useful ‘patterns’ about the triad ‘drugs-symptoms-medicine’ is done by Association Rule Mining. Association rule mining is a popular and widely-known machine learning task. It is used to find out interesting relations between variables in large database. Rules generated by association have two disjoint set of items having form LHS (Left Hand Side) => RHS (Right Hand Side). The rule says that RHS is likely to occur whenever the LHS set occurs.

Does Nutritional Knowledge Translate into Healthier Dietary Practices: Perceptions and Barriers to Healthy Eating among Indian Adults

Adequate level of nutritional knowledge need not assure good dietary practices. Perceptions about the link between food and health as well as barriers in following healthy eating practices need to be examined to understand why people choose certain foods over others. The objective of the study was to assess the knowledge, perceptions and practices of adults regarding healthy eating. It is a cross-sectional, observational study where participants were selected purposively from a total of 23 housing colonies from four geographical zones (North, South, East, and West) of Delhi, India. A mixed methods approach was used to study the eating habits of 589 adults (20-40 years of age). A pretested questionnaire was used to gather information on knowledge, perceptions and practices regarding healthy eating. Twelve focus group discussions with 6-8 participants in each group were also conducted. The knowledge and practice scores had a weak positive relationship (p=0.181, p<0.01). Taste, emotional state of mind, social company and convenience influenced the food choices. Barriers such as lack of time to prepare meals, busy work schedules, not having skills to cook meals caused difficulty in following a healthy diet. Raising nutrition literacy levels cannot be the only focus of interventions to improve the quality of diet in a community. The barriers and enablers of a healthy diet need to be addressed in order to facilitate better food choices. A systematic ‘whole of society’ approach can be used to make a more conducive food environment.

Drug Analysis System Using Machine Learning Algorithms

Internet-based healthcare communities persist in providing an extensive array of valuable medical insights, serving medical professionals, system administrators, and patients alike. Our approach involves the real-time compilation of health-related posts from reputable online sources, where patients share their perspectives, encompassing their encounters and potential drug side-effects. We intend to execute user post summarization on a per-drug basis, facilitating succinct findings accessible to both the medical community and patient cohort instantaneously. Further, we propose to classify the users based on their `emotional state of mind'. Furthermore, our methodology encompasses knowledge exploration within user-generated content, facilitating the identification of valuable 'patterns' pertaining to the interconnected 'drugs-symptoms-medicine' triad through the application of Association Learning techniques. Index Terms: Online Health Communities, Drug Summarization, Emotional User Classification, Association Learning.

Machine Learning Models for Classification of Human Emotions Using Multivariate Brain Signals

Humans can portray different expressions contrary to their emotional state of mind. Therefore, it is difficult to judge humans’ real emotional state simply by judging their physical appearance. Although researchers are working on facial expressions analysis, voice recognition, and gesture recognition; the accuracy levels of such analysis are much less and the results are not reliable. Hence, it becomes vital to have realistic emotion detector. Electroencephalogram (EEG) signals remain neutral to the external appearance and behavior of the human and help in ensuring accurate analysis of the state of mind. The EEG signals from various electrodes in different scalp regions are studied for performance. Hence, EEG has gained attention over time to obtain accurate results for the classification of emotional states in human beings for human–machine interaction as well as to design a program where an individual could perform a self-analysis of his emotional state. In the proposed scheme, we extract power spectral densities of multivariate EEG signals from different sections of the brain. From the extracted power spectral density (PSD), the features which provide a better feature for classification are selected and classified using long short-term memory (LSTM) and bi-directional long short-term memory (Bi-LSTM). The 2-D emotion model considered for the classification of frontal, parietal, temporal, and occipital is studied. The region-based classification is performed by considering positive and negative emotions. The performance accuracy of our previous model’s results of artificial neural network (ANN), support vector machine (SVM), K-nearest neighbor (K-NN), and LSTM was compared and 94.95% accuracy was received using Bi-LSTM considering four prefrontal electrodes.

The Role of the Hypothalamus–Pituitary–Adrenal (HPA) Axis in Test-Induced Anxiety: Assessments, Physiological Responses, and Molecular Details

Test anxiety may be a contributing factor to low-performing examination scores among students. There can be numerous physiological responses in the body that lead to test anxiety. One is the body’s response to stress, which activates the brain to release hormones that stimulate central and peripheral nervous responses. The hypothalamus–pituitary–adrenal (HPA) axis is a known responder during stress, causing an elevation of cortisol in the blood, a glucocorticoid (GC) hormone that affects sympathetic nervous responses. Stressors during testing include the method of information delivered, prior knowledge of the subject material, emotional state, or how accurately the student can retain knowledge. A student’s emotional state of mind is essential and may cause hyperactivation of the HPA axis during stress encountered during testing, exacerbating cortisol levels and nervous responsiveness. This review discusses the potential involvement of the HPA stress axis on an individual’s performance during testing and assessment.

Recognition of arm and body postures as social cues for proactive HRI

AbstractArtificial agents can uplift the living standards of domestic population considerably. One hindrance for this is that the robot is less competent to perceive complex human behaviors. With such perceptive skills in the robot, nonexpert users will find it easier to cope with their robot companion with less and less instructions to follow. Perception of the internal state of a user or “user situation” before interaction is crucial in this regard. There are a variety of factors that affect this user situation. Out of these, posture becomes prominent in displaying the emotional state of a person. This article presents a novel approach to identify diverse human postures often encountered in domestic environments and how a robot could assess its user’s emotional state of mind before an interaction based on postures. Therefore, the robot evaluates posture and the overall postural behavior of its user throughout the period of observation before initiating an interaction with its user. Aforementioned user evaluation is nonverbal and decisions are made through observation as well. We introduced a variable called “valence” to measure how “relaxed” or “stressed” a user is, in a certain encounter. The robot decides upon an appropriate approach behavior accordingly. Furthermore, the proposed concept was capable of recognizing both arm and body postures and both postural behaviors over time. This leads to an interaction initiated by robot itself in a favorable situation so that the scenario looks more intelligent. Hence more humanlike. The system has been implemented, and experiments have been conducted on an assistive robot placed in an artificially created domestic environment. Results of the experiments have been used to validate the proposed concept and critical observations are discussed.

Nothing to Be Happy about: Consumer Emotions and AI

Advancements in artificial intelligence and Big Data allow for a range of goods and services to determine and respond to a consumer’s emotional state of mind. Considerable potential surrounds the technological ability to detect and respond to an individual’s emotions, yet such technology is also controversial and raises questions surrounding the legal protection of emotions. Despite their highly sensitive and private nature, this article highlights the inadequate protection of emotions in aspects of data protection and consumer protection law, arguing that the contribution by recent proposal for an Artificial Intelligence Act is not only unsuitable to overcome such deficits but does little to support the assertion that emotions are highly sensitive.

DEVOURED IDENTITIES: THE POLITICS OF FOOD AND GENDER IN ANITA DESAI’S FASTING AND FEASTING

The research paper is an attempt to examine the subjugation of identity and hence the perturbed experience of the protagonist and various other characters due to power politics in Anita Desai’s Fasting and Feasting. In the novel, the character’s involvement with food becomes a means of expression of their emotional state of mind. Thus, by studying the food behavioral patterns of a character we can infer the deeply embedded associations and internal anguish that the character has gone through. The novel explores the dichotomic theme of hunger and plenty which is reflected in characters like Uma, Arun and, Melanie. The researcher has identified and analyzed the food behavioral patterns of these characters to anatomize the politics of food and gender. From Uma’s imposed fasting to Arun’s obtrude feasting, the novel is a testimony of how consumption patterns mirror the socio-cultural struggles of an individual. The author in the novel indicates how food consumption is gendered and logicized culturally. In the research paper, food and food consumption will act as a lens to the character's social, cultural, and psychological needs.

Facial Expression Recognition Using Local Gravitational Force Descriptor-Based Deep Convolution Neural Networks

An image is worth a thousand words; hence, a face image illustrates extensive details about the specification, gender, age, and emotional states of mind. Facial expressions play an important role in community-based interactions and are often used in the behavioral analysis of emotions. Recognition of automatic facial expressions from a facial image is a challenging task in the computer vision community and admits a large set of applications, such as driver safety, human-computer interactions, health care, behavioral science, video conferencing, cognitive science, and others. In this work, a deep-learning-based scheme is proposed for identifying the facial expression of a person. The proposed method consists of two parts. The former one finds out local features from face images using a local gravitational force descriptor, while, in the latter part, the descriptor is fed into a novel deep convolution neural network (DCNN) model. The proposed DCNN has two branches. The first branch explores geometric features, such as edges, curves, and lines, whereas holistic features are extracted by the second branch. Finally, the score-level fusion technique is adopted to compute the final classification score. The proposed method along with 25 state-of-the-art methods is implemented on five benchmark available databases, namely, Facial Expression Recognition 2013, Japanese Female Facial Expressions, Extended CohnKanade, Karolinska Directed Emotional Faces, and Real-world Affective Faces. The databases consist of seven basic emotions: neutral, happiness, anger, sadness, fear, disgust, and surprise. The proposed method is compared with existing approaches using four evaluation metrics, namely, accuracy, precision, recall, and f1-score. The obtained results demonstrate that the proposed method outperforms all state-of-the-art methods on all the databases.

Stress Management in Libraries

Stress has become a major problem of every human being in society. Stress is the mental, physical, situational and emotional state of mind. In this paper stress management in libraries discusses some aspects of stress in the library professionals. It describes about the stress in libraries and its reasons. It also elaborate types of stress, causes and symptom of stress and strategies to counter stress. It also analyzed the best way to manage stress in LIS professionals. However there are many motivational factors as well as bottlenecks which effects professionals to participate in continuous professional development (CPD) activities. So this topic brings focus, he need to ensure library professionals well prepared and up dated with current trends in their jobs and duties.

Muslims in the U.S. Military: Moral Injury and Eroding Rights

How does moral injury affect Muslim military personnel (MMP) serving in the United States longest war, Operations Enduring Freedom and Iraqi Freedom? Moral injury in MMP has often been triggered by stressors such as harassment, embarrassment, marginalization, prejudice, and being associated with a co-religionist enemy. MMP are perceived as a threat to the safety and security of the United States, which exacerbates their emotional state of mind because they do not feel included as valuable assets within their units. Little is known about this population’s mental state of mind and how they cope when their religion is ridiculed and distorted, causing it to become a stressor and exacerbating the effects of moral stress and injury experienced by individual MMP—including the author—as they serve their country today and in the recent past. Recommendations include (1) more in-depth studies on the experience of moral injury and how it manifests with this population, (2) studies on the incidence and prevalence of moral injury among MMP, and (3) more Muslim chaplains in the U.S. military.

The Role of Pattern Extrapolation in the Perception of Dynamic Facial Expressions in Autism Spectrum Disorder.

Changes in the intensity and type of facial expressions reflect alterations in the emotional state of the agent. Such “direct” access to the other’s affective state might, top-down, influence the perception of the facial expressions that gave rise to the affective state inference. Previously, we described a perceptual bias occurring when the last, neutral, expression of offsets of facial expressions (joy-to-neutral and anger-to-neutral), was evaluated. Individuals with high-functioning autism (HFA) and matched typically developed (TD) individuals rated the neutral expression at the end of the joy-offset videos as slightly angry and the identical neutral expression at the end of the anger-offset videos as slightly happy (“overshoot” bias). That study suggested that the perceptual overshoot response bias in the TD group could be best explained by top-down “emotional anticipation,” i.e., the involuntary/automatic anticipation of the agent’s next emotional state of mind, generated by the immediately preceding perceptual history (low-level mind reading). The experimental manipulations further indicated that in the HFA group the “overshoot” was better explained by contrast effects between the first and last facial expressions, both presented for a relatively long period of 400 ms. However, in principle, there is another, more parsimonious, explanation, which is pattern extrapolation or representational momentum (RM): the extrapolation of a pattern present in the dynamic sequence. This hypothesis is tested in the current study, in which 18 individuals with HFA and a matched control group took part. In a base-line condition, joy-offset and anger-offset video-clips were presented. In the new experimental condition, the clips were modified so as to create an offset-onset-offset pattern within each sequence (joy-to-anger-to-neutral and anger-to-joy-to-neutral). The final neutral expressions had to be evaluated. The overshoot bias was confirmed in the base-line condition for both TD and HFA groups, while the experimental manipulation removed the bias in both groups. This outcome ruled out pattern extrapolation or RM as explanation for the perceptual “overshoot” bias in the HFA group and suggested a role for facial contrast effects in HFA. This is compatible with the view that ASD individuals tend to lack the spontaneous “tracking” of changes in the others’ affective state and hence show no or reduced emotional anticipation.

Solving the prefrontal conundrum of high-order anxiety: conciliating HOTEC and hypofrontality. A theoretical review

ABSTRACTIntroduction: According to the High-order Theory of Emotional Consciousness (HOTEC), every emotional process is a conscious and high-order state of mind carried out by the General Networks of Cognition (GNC), which consists mainly of prefrontal mechanisms. This means that anxiety is also an emotional state of mind carried out by the GNC (positive correlation). However, numerous studies have suggested what is commonly called “hypofrontality” during states of anxiety (negative correlation), which seems to give rise to a theoretical and empirical contraction.Methods: I present a theoretical review to address the following issue: how to advocate a HOTEC view of anxiety in the face of a growing paradigm of hypofrontality during states of anxiety?Results: Here I propose that dmPFC, the dACC, and the anterior insula are GNC areas positively correlated with anxiety, which, along with the prefrontal areas responsible for regulating the activation of survival circuits and driving the attention to adaptive ways to overcome potential threats, form an interconnective model of anticipatory and regulatory mechanisms related to learned threats based on autobiographical memories.Conclusions: Through this model, I propose that HOTEC is still a valid way to approach and understand both healthy and unhealthy anxious states of mind.

WEB MINING IN CLASSIFYING YOUTH EMOTIONS

Social media sites are websites used as mediums to create and share various types of contents over the internet. These sites can also be accessed through applications on mobile gadgets. Different social media sites are available for free, and most teenagers or youths have at least one active account. They use social media sites to connect and share their online profiles, daily activities, stories, and emotions. Depending on their social settings, their activities may or may not be seen by others. One of the latest trends that is spreading over the social media is the Korean Pop entertainment or popularly known as KPop. Over the social media, youths share and express how they feel about their Korean celebrities, music, and drama. However, the issue of excessive sharing of emotion-sharing over social media may increase the risk of mental illness and affect their mental health. Their obsession to keep up-to-date with their idols might lead or cause adverse consequences on their emotional states of mind. Thus, the aim of this research is to study the changes of youths’ emotions in two different countries which are Malaysia and Korea that are related to the KPop trend. We extract texts from tweets from Twitter social media sites using the Twitter API as the basis of our study. Then, the keyword 'KPop' is used to filter the tweets. Web mining model classifies the 12,000 tweets into six emotion categories, which are joy, sadness, fear, anger, disgust, and surprise. The system then records the emotion changes and the triggering events respectively.

Emotional responsiveness in convicted fraudsters: a study on baseline activation of the anterior insula and its influence on moral decision-making

Low emotional responsiveness promotes utilitarian decision-making on moral dilemmas. Based on the assumption that fraudsters use their emotional competence to deceive their victims, their emotional responsiveness is not expected to be protective against utilitarian decision-making. The present study investigates the key role of emotional responsiveness in relation to moral decision-making in 11 imprisoned fraudsters, 10 imprisoned violent offenders, and 11 non-offenders. Participants’ neural baseline activation of bilateral anterior insula (AI) was used as an indicator for emotional responsiveness. Results indicate that fraudsters and non-offenders have a higher right AI baseline activation than violent offenders. Yet, fraudsters and violent offenders show a stronger tendency towards utilitarian decisions than non-offenders. The predictive power of AI baseline activation on moral decision-making reaches significance only for fraudsters. Results give evidence that fraudsters are highly sensitive to their emotional state of mind, which, contrary to our expectation, exerts a strong influence on their moral decisions.

Representational momentum in dynamic facial expressions is modulated by the level of expressed pain: Amplitude and direction effects.

Humans have developed a specific capacity to rapidly perceive and anticipate other people's facial expressions so as to get an immediate impression of their emotional state of mind. We carried out two experiments to examine the perceptual and memory dynamics of facial expressions of pain. In the first experiment, we investigated how people estimate other people's levels of pain based on the perception of various dynamic facial expressions; these differ both in terms of the amount and intensity of activated action units. A second experiment used a representational momentum (RM) paradigm to study the emotional anticipation (memory bias) elicited by the same facial expressions of pain studied in Experiment 1. Our results highlighted the relationship between the level of perceived pain (in Experiment 1) and the direction and magnitude of memory bias (in Experiment 2): When perceived pain increases, the memory bias tends to be reduced (if positive) and ultimately becomes negative. Dynamic facial expressions of pain may reenact an "immediate perceptual history" in the perceiver before leading to an emotional anticipation of the agent's upcoming state. Thus, a subtle facial expression of pain (i.e., a low contraction around the eyes) that leads to a significant positive anticipation can be considered an adaptive process-one through which we can swiftly and involuntarily detect other people's pain.

Change is an emotional state of mind: Behavioral responses to online petitions

Scholars are increasingly concerned about the rising level of negativity in social media sites. This negativity has found its way into sites that are supposedly intended for prosocial civic engagement. To examine how hostility impacts behavior in a user-generated, prosocial context, an experimental study was conducted using an online petition modeled after those posted to the website Change.org . This study examines whether negativity causes a contagion effect leading to more negativity and the different types of negativity that may occur. Results suggest that when users read negative-toned petitions, a contagion effect increases both anger and anxiety. However, our findings are not consistent with previous literature that argues anger leads to increased proactive behavior. Instead, we find that while anxiety leads to an increase in petition-related action, anger does not. These findings have important theoretical and practical implications for scholars and those looking to participate in social justice via online platforms.

Neurotransmitter alteration in a testosterone propionate-induced polycystic ovarian syndrome rat model.

Polycystic ovarian syndrome (PCOS), one of the leading causes of infertility seen in women, is characterized by anovulation and hyperandrogenism, resulting in ovarian dysfunction. In addition, associations of several metabolic complications like insulin resistance, obesity, dyslipidemia and psychological co-morbidities are well known in PCOS. One of the major factors influencing mood and the emotional state of mind is neurotransmitters. Also, these neurotransmitters are very crucial for GnRH release. Hence, the current study investigates the status of neurotransmitters in PCOS. A PCOS rat model was developed using testosterone. Twenty-one-day-old rats were subcutaneously injected with 10 mg/kg body weight of testosterone propionate (TP) for 35 days. The animals were validated for PCOS characteristics by monitoring estrus cyclicity, serum testosterone and estradiol levels and by histological examination of ovarian sections. Neurotransmitter estimation was carried out using fluorometric and spectrophotometric methods. TP-treated animals demonstrated increased serum testosterone levels with unaltered estradiol content, disturbed estrus cyclicity and many peripheral cysts in the ovary compared to control rats mimicking human PCOS. Norepinephrine (NE), dopamine, serotonin, γ-amino butyric acid (GABA) and epinephrine levels were significantly low in TP-induced PCOS rats compared to control ones, whereas the activity of acetylcholinesterase in the PCOS brain was markedly elevated. Neurotransmitter alteration could be one of the reasons for disturbed gonadotropin-releasing hormone (GnRH) release, consequently directing the ovarian dysfunction in PCOS. Also, decrease in neurotransmitters, mainly NE, serotonin and dopamine (DA) attributes to mood disorders like depression and anxiety in PCOS.

Prevalence and Determinants of Repeat Mammography Among Women from a Developing Country.

Failures in repeat mammography decrease the potential benefits of screening; however, it is notable that the recent use of mammography is more frequently studied than repeat use. We estimated the prevalence and analyzed determinants for repeat mammography among women from Mexico, a developing country of Latin America. It was a two-stage study with an initial cross-sectional design (n = 1045) and a final case-control design that involved women of at least 45years of age with no history of breast, ovarian, or uterine cancer. Case subjects were those with three or more mammograms in the last 5years, with the last one carried out within the last two years (n = 444); control subjects included those who underwent ≥3 mammograms throughout their life with the most recent carried out >2years ago (n = 444). Through interviews, we evaluated context-dependency, fulfillment of expected outcomes, self-efficacy, and risk perception, among other factors. We estimated the prevalence with 95 % confidence intervals (CI), and odds ratios (OR) using multivariate binary logistic regression. The prevalence of repeat mammography was 40.4 % (95 % CI 37.4-43.4). Self-efficacy demonstrated the highest effect on repeat use (OR 7.7, 95 % CI 4.7-12.6), followed by awareness context-dependency (OR 4.9, 95 % CI 3.3-7.2), the use of Papanicolaou testing (OR 3.5, 95 % CI 2.3-5.2), the fulfillment of expected waiting time outcome (OR 2.4, 95 % CI 1.2-4.7), and context-dependency related to self-referral/health provider referral (OR 2.4, 95 % CI 1.7-3.4), independent of risk perception, age, education, and positive emotional state of mind. The study showed a need for increasing the prevalence of promoting awareness of the determining factors of repeat mammography, which is a necessary component in the early detection of breast cancer.