Using non-invasive wearables for detecting emotions with intelligent agents

This paper proposes the use of intelligent wristbands for the automatic detection of emotional states in order to develop an application which allows to extract, analyze, represent and manage the social emotion of a group of entities. Nowadays, the detection of the joined emotion of an heterogeneous group of people is still an open issue. Most of the existing approaches are centered in the emotion detection and management of a single entity. Concretely, the application tries to detect how music can influence in a positive or negative way over individuals’ emotional states. The main goal of the proposed system is to play music that encourages the increase of happiness of the overall patrons.This work is partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon. This work is supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the projects UID/CEC/00319/2013 and Post-Doc scholarship SFRH/BPD/102696/2014 (A. Cost

Detecting emotions through non-invasive wearables

Current research on computational intelligence is being conducted in order to emulate and/or detect emotional states using specific devices such as wristbands or similar wearables. In this sense, this paper proposes the use of intelligent wristbands for the automatic detection of emotional states in order to develop an application which allows us to extract, analyse, represent and manage the social emotion of a group of entities. Nowadays, most of the existing approaches are centred in the emotion detection and management of a single entity. The designed system has been developed as a multi-agent system where each agent controls a wearable device and is in charge of detecting individual emotions based on bio-signals

New methods for stress assessment and monitoring at the workplace

The topic of stress is nowadays a very important one, not only in research but on social life in general. People are increasingly aware of this problem and its consequences at several levels: health, social life, work, quality of life, etc. This resulted in a significant increase in the search for devices and applications to measure and manage stress in real-time. Recent technological and scientific evolution fosters this interest with the development of new methods and approaches. In this paper we survey these new methods for stress assessment, focusing especially on those that are suited for the workplace: one of today’s major sources of stress. We contrast them with more traditional methods and compare them between themselves, evaluating nine characteristics. Given the diversity of methods that exist nowadays, this work facilitates the stakeholders’ decision towards which one to use, based on how much their organization values aspects such as privacy, accuracy, cost-effectiveness or intrusivenes

New methods for stress assessment and monitoring at the workplace

The topic of stress is nowadays a very important one, not only in research but on social life in general. People are increasingly aware of this problem and its consequences at several levels: health, social life, work, quality of life, etc. This resulted in a significant increase in the search for devices and applications to measure and manage stress in real-time. Recent technological and scientific evolution fosters this interest with the development of new methods and approaches. In this paper we survey these new methods for stress assessment, focusing especially on those that are suited for the workplace: one of today’s major sources of stress. We contrast them with more traditional methods and compare them between themselves, evaluating nine characteristics. Given the diversity of methods that exist nowadays, this work facilitates the stakeholders’ decision towards which one to use, based on how much their organization values aspects such as privacy, accuracy, cost-effectiveness or intrusivenes

Robotic-based well-being monitoring and coaching system for the elderly in their daily activities

The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In the COVID 19 pandemic, the elderly have been seriously affected in addition to suffering from isolation and its associated and psychological consequences. This paper provides an overview of the RobWell (Robotic-based Well-Being Monitoring and Coaching System for the Elderly in their Daily Activities) system. It is a system focused on the field of artificial intelligence for mood prediction and coaching. This paper presents a general overview of the initially proposed system as well as the preliminary results related to the home automation subsystem, autonomous robot navigation and mood estimation through machine learning prior to the final system integration, which will be discussed in future works. The main goal is to improve their mental well-being during their daily household activities. The system is composed of ambient intelligence with intelligent sensors, actuators and a robotic platform that interacts with the user. A test smart home system was set up in which the sensors, actuators and robotic platform were integrated and tested. For artificial intelligence applied to mood prediction, we used machine learning to classify several physiological signals into different moods. In robotics, it was concluded that the ROS autonomous navigation stack and its autodocking algorithm were not reliable enough for this task, while the robot’s autonomy was sufficient. Semantic navigation, artificial intelligence and computer vision alternatives are being sought.This research was funded by the Spanish Ministerio de Ciencia, Innovación y Univesidades, Agencia Estatal de Investigación (AEI) and the European Regional Development Fund (ERDF) under project ROBWELL (RTI2018-095599-A-C22) and by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation

Using emotions in intelligent virtual environments: the EJaCalIVE framework

Nowadays, there is a need to provide new applications which allow the definition and implementation of safe environments that attends to the user needs and increases their wellbeing. In this sense, this paper introduces the EJaCalIVE framework which allows the creation of emotional virtual environments that incorporate agents, eHealth related devices, human actors, and emotions projecting them virtually and managing the interaction between all the elements. In this way, the proposed framework allows the design and programming of intelligent virtual environments, as well as the simulation and detection of human emotions which can be used for the improvement of the decision-making processes of the developed entities. The paper also shows a case study that enforces the need of this framework in common environments like nursing homes or assisted living facilities. Concretely, the case study proposes the simulation of a residence for the elderly. The main goal is to have an emotion-based simulation to train an assistance robot avoiding the complexity involved in working with the real elders. The main advantage of the proposed framework is to provide a safe environment, that is, an environment where users are able to interact safely with the system.This work is partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R and the FPI Grant AP2013-01276 awarded to Jaime-Andres Rincon. This work is also supported by COMPETE: POCI-01-0145-FEDER-007043 and Fundacao para a Ciencia e Tecnologia (FCT) within the projects UID/CEC/00319/2013 and Post-Doc scholarship SFRH/BPD/102696/2014 (A. Costa).info:eu-repo/semantics/publishedVersio

Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour

Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial

Toward Emotional Internet of Things for Smart Industry

In this paper, an approach to design and implement non-invasive and wearable emotion recognition technologies in smart industries is proposed. The proposed approach benefits from the interconnectivity of Internet of Things (IoT) to recognize and adapt to complex negative emotional states of employees (e.g., stress, frustration, etc.). Two types of connected objects are proposed: emotional detectors and emotional actors. The steps to design and implement these connected objects are described. The proposed approach is expected to ensure and maintain a healthy work environment in smart industries