As someone who struggled for years to manage my emotions effectively, I can attest to the incredible impact that emotional intelligence can have on our lives. Growing up, I was quick to anger and struggled to control my impulses. I was in a lot of chaos with my friends, family and colleagues which lead to losing my job, that made me devastated and angry. I hated the way my emtions took hold of me until I began focusing on developing my emotional intelligence that I was able to turn my life around. Emotional intelligence, or EI, is the ability to identify, understand, and manage our own emotions, as well as those of others.

Emotional Intelligence Activities to Increase your EQ. Develop Emotional Intelligence with 15 Practical Exercises. Learn to manage your emotions and have better quality life. In this course, you will learn about emotional intelligence (EQ) and some of the activities that will help you develop your EQ. This course is suitable and beneficial for people of all age groups having an adequate literacy level and also the ones who want to develop a full range of human intelligence rather than limiting themselves to standard IQ scores.

Every cat owner knows that you don't have to observe the animals for long to know they are highly intelligent beings. Despite having relatively small brains, studies have shown felines have high emotional intelligence and a great willingness to adapt, making them some of the smartest creatures in the animal kingdom. But how to breeds stack up when it comes to intelligence? As a study this month revealed the most intelligent breeds of dogs, we delve into which breeds of cats can be crowned the cleverest. Does it respond to its own name? People tend to assume that cat's cannot learn their own names, unlike dogs. But research from Sophia University in Japan revealed that cats do recognise when their name is being called.

Abstract: Couples generally manage chronic diseases together and the management takes an emotional toll on both patients and their romantic partners. Consequently, recognizing the emotions of each partner in daily life could provide an insight into their emotional well-being in chronic disease management. The emotions of partners are currently inferred in the lab and daily life using self-reports which are not practical for continuous emotion assessment or observer reports which are manual, time-intensive, and costly. Currently, there exists no comprehensive overview of works on emotion recognition among couples. Furthermore, approaches for emotion recognition among couples have (1) focused on English-speaking couples in the U.S., (2) used data collected from the lab, and (3) performed recognition using observer ratings rather than partner's self-reported / subjective emotions.

Abstract: Recognizing human emotions from complex, multivariate, and non-stationary electroencephalography (EEG) time series is essential in affective brain-computer interface. However, because continuous labeling of ever-changing emotional states is not feasible in practice, existing methods can only assign a fixed label to all EEG timepoints in a continuous emotion-evoking trial, which overlooks the highly dynamic emotional states and highly non-stationary EEG signals. To solve the problems of high reliance on fixed labels and ignorance of time-changing information, in this paper we propose a time-aware sampling network (TAS-Net) using deep reinforcement learning (DRL) for unsupervised emotion recognition, which is able to detect key emotion fragments and disregard irrelevant and misleading parts. Extensive experiments are conducted on three public datasets (SEED, DEAP, and MAHNOB-HCI) for emotion recognition using leave-one-subject-out cross-validation, and the results demonstrate the superiority of the proposed method against previous unsupervised emotion recognition methods. Abstract: The study proposes and tests a technique for automated emotion recognition through mouth detection via Convolutional Neural Networks (CNN), meant to be applied for supporting people with health disorders with communication skills issues (e.g.

Abstract: Understanding the facial expressions of our interlocutor is important to enrich the communication and to give it a depth that goes beyond the explicitly expressed. In fact, studying one's facial expression gives insight into their hidden emotion state. However, even as humans, and despite our empathy and familiarity with the human emotional experience, we are only able to guess what the other might be feeling. In the fields of artificial intelligence and computer vision, Facial Emotion Recognition (FER) is a topic that is still in full growth mostly with the advancement of deep learning approaches and the improvement of data collection. The main purpose of this paper is to compare the performance of three state-of-the-art networks, each having their own approach to improve on FER tasks, on three FER datasets.

In 2023, emotional AI--technology that can sense and interact with human emotions--will become one of the dominant applications of machine learning. For instance, Hume AI, founded by Alan Cowen, a former Google researcher, is developing tools to measure emotions from verbal, facial, and vocal expressions. Swedish company Smart Eyes recently acquired Affectiva, the MIT Media Lab spinoff that developed the SoundNet neural network, an algorithm that classifies emotions such as anger from audio samples in less than 1.2 seconds. Even the video platform Zoom is introducing Zoom IQ, a feature that will soon provide users with real-time analysis of emotions and engagement during a virtual meeting. In 2023, tech companies will be releasing advanced chatbots that can closely mimic human emotions to create more empathetic connections with users across banking, education, and health care.

New algorithms allow for a greater level of control in operating rooms and medical centres around the globe. Similarly, self-driving vehicles and city infrastructure will benefit immensely from advanced AI algorithms and machine learning frameworks. AI is now able to understand human emotions to some extent and has the capability to predict human behaviour. For example, some forms of AI can now tell if someone is lying or not. AI can now also be used for social good and in the future maybe even save lives and prevent crimes. Second, they allow us to predict what will happen in the future by using AI to create forecasting models that can tell us about future events or changes in trends. And finally, they help us understand how people behave and react so that we can improve our own behaviour and reactions as well as develop better customer service based on what people want and need. As AI forays into every aspect of human life, it is time for intervention by responsible actions by policymakers as well as industry stakeholders to counter its possible misuse.

Technology serves as a way to bridge the gap between the physical and digital worlds. It connects us and opens up channels of communication in our personal and professional lives. Being able to infuse these conversations -- no matter where or when they occur -- with emotional intelligence and empathy has become a top priority for leaders eager to help employees become more effective and genuine communicators. However, the human emotion that goes into communication is often a hidden variable, changing at any moment. In customer-facing roles, for example, a representative might become sad after hearing why a customer is seeking an insurance claim, or become stressed when a caller raises their voice. The emotional volatility surrounding customer experiences requires additional layers of support to meet evolving demands and increasing expectations.

Check out the on-demand sessions from the Low-Code/No-Code Summit to learn how to successfully innovate and achieve efficiency by upskilling and scaling citizen developers. Technology serves as a way to bridge the gap between the physical and digital worlds. It connects us and opens up channels of communication in our personal and professional lives. Being able to infuse these conversations -- no matter where or when they occur -- with emotional intelligence and empathy has become a top priority for leaders eager to help employees become more effective and genuine communicators. However, the human emotion that goes into communication is often a hidden variable, changing at any moment.