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

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

A new emotional robot assistant that facilitates human interaction and persuasion

The development of robots that are truly sociable requires understanding how human interactions can be applied to the interaction between humans and robots. A sociable robot must be able to interact with people taking into account aspects like verbal and non-verbal communications (emotions, postures, gestures). This work presents a social robot which main goal is to provide assistance to older people in carrying out their daily activities (through suggestions or reminders). In addition, the robot presents non-verbal communications like perceiving emotions and displaying human identifiable emotions in order to express empathy. A prototype of the robot is being tested in a daycare center in the northern area of Portugal.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 - Fundacao para a Ciencia e Tecnologia within the projects UID/CEC/00319/2013 and Post-Doc scholarship SFRH/BPD/102696/2014 (Angelo Costa)

Emotions detection on an ambient intelligent system using wearable devices

This paper presents the Emotional Smart Wristband and its integration with the iGenda. The aim is to detect emotional states of a group of entities through the wristband and send the social emotion value to the iGenda so it may change the home environment and notify the caregivers. This project is advantageous to communities of elderly people, like retirement homes, where a harmonious environment is imperative and where the number of inhabitants keeps increasing. The iGenda provides the visual interface and the information center, receiving the information from the Emotional Smart Wristband and tries achieve a specific emotion (such as calm or excitement). Thus, the goal is to provide an affective system that directly interacts with humans by discreetly improving their lifestyle. In this paper, it is described the wristband in depth and the data models, and is provided an evaluation of them performed by real individuals and the validation of this evaluation.- This work is supported by COMPETE, Portugal: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologi, Portugal a within the projects UID/CEC/00319/2013 and Post-Doc scholarship SFRH/BPD/102696/2014 (Angelo Costa) This work is partially supported by the MINECO/FEDER, Spain TIN2015-65515-C4-1-R and AP2013-01276 awarded to Jaime-Andres Rincon

A low-cost cognitive assistant

In this paper, we present in depth the hardware components of a low-cost cognitive assistant. The aim is to detect the performance and the emotional state that elderly people present when performing exercises. Physical and cognitive exercises are a proven way of keeping elderly people active, healthy, and happy. Our goal is to bring to people that are at their homes (or in unsupervised places) an assistant that motivates them to perform exercises and, concurrently, monitor them, observing their physical and emotional responses. We focus on the hardware parts and the deep learning models so that they can be reproduced by others. The platform is being tested at an elderly people care facility, and validation is in process.This work was partly supported by the FCT (Fundação para a Ciência e Tecnología) through the Post-Doc scholarship SFRH/BPD/102696/2014 (A. Costa), by the Generalitat Valenciana (PROMETEO/2018/002), and by the Spanish Government (RTI2018-095390-B-C31)

EMERALD—Exercise Monitoring Emotional Assistant

The increase in the elderly population in today’s society entails the need for new policies to maintain an adequate level of care without excessively increasing social spending. One of the possible options is to promote home care for the elderly. In this sense, this paper introduces a personal assistant designed to help elderly people in their activities of daily living. This system, called EMERALD, is comprised of a sensing platform and different mechanisms for emotion detection and decision-making that combined produces a cognitive assistant that engages users in Active Aging. The contribution of the paper is twofold—on the one hand, the integration of low-cost sensors that among other characteristics allows for detecting the emotional state of the user at an affordable cost; on the other hand, an automatic activity suggestion module that engages the users, mainly oriented to the elderly, in a healthy lifestyle. Moreover, by continuously correcting the system using the on-line monitoring carried out through the sensors integrated in the system, the system is personalized, and, in broad terms, emotionally intelligent. A functional prototype is being currently tested in a daycare centre in the northern area of Portugal where preliminary tests show positive results.This research was partially funded by the Fundacao para a Ciencia e Tecnologia (FCT) within the projects UID/CEC/00319/2019 and Post-Doc Grant SFRH/BPD/102696/2014 (Angelo Costa). This work is also partially funded by the MINECO/FEDER TIN2015-65515-C4-1-R and RISEWISE (RISEWomen with disabilities In Social Engagement) EU project under Agreement No. 690874.info:eu-repo/semantics/publishedVersio

Activities suggestion based on emotions in AAL environments

The elderly population is increasing and the response of the society was to provide them with services directed to them to cope with their needs. One of the oldest solutions is the retirement home, providing housing and permanent assistance for the elderly. Furthermore, most of the retirement homes are inhabited by multiple elderly people, thus creating a community of people who are somewhat related in age and medical issues. The ambient assisted living (AAL) area tries to solve some of the elderly issues by producing technological products, some of them dedicated to elderly homes. One of the identified problem is that elderly people are sometimes discontent about the activities that consume most of their day promoted by the retirement home social workers. The work presented in this paper attempts to improve how these activities are scheduled taking into account the elderlies' emotional response to these activities. The aim is to maximize the group happiness by promoting the activities the group likes, minding if they are bored due to activities repetition. In this sense, this paper presents an extension of the Cognitive Life Assistant platform incorporating a social emotional model. The proposed system has been modelled as a free time activity manager which is in charge of suggesting activities to the social workers. (C) 2018 Elsevier B.V. All rights reserved.Angelo Costa thanks the Fundacao para a Ciencia e a Tecnologia (FCT) the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work is also supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e Tecnologia within the Project Scope: UID/CEC/00319/2013 and partially supported by the MINECO/FEDER TIN2015-65515-C4-1-R and the FPI grant AP2013-01276 awarded to Jaime-Andres Rincon

Discordance between old and new criteria for stratifying patients with COPD

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A Cross-Sectional Population-Based Study

Funding Information: We thank the EpiDoc Unit and EpiReumaPt team for conceptualising, planning, and implementing the main research project. We would like to acknowledge that the present publication was supported by Fundação Ciência e Tecnologia, IP national support through CHRC (UIDP/04923/2020). Funding Information: This work was supported by an independent research grant from Pfizer. DC received national funding through FCT—Fundação para a Ciência e Tecnologia, I. P. under the Ph.D. grant SFRH/BD/148420/2019Background: Hip/knee osteoarthritis (HKOA) is a leading cause of disability and imposes a major socioeconomic burden. The aim of this study is to estimate the prevalence of HKOA in Portugal, characterised the clinical severity of HKOA in the population, and identified sociodemographic, lifestyle, and clinical factors associated with higher clinical and radiographic severity. Methods: Participants with a diagnosis of HKOA from the EpiReumaPt study (2011–2013) were included (n = 1,087). Hip/knee osteoarthritis diagnosis was made through a structured evaluation by rheumatologists according to American College of Rheumatology criteria. Clinical severity was classified based on Hip Disability and Osteoarthritis Outcome Scale (HOOS) and Knee Injury and Osteoarthritis Outcome Scale (KOOS) score tertiles. Radiographic severity was classified based on the Kellgren-Lawrence grades as mild, moderate, or severe. Sociodemographic lifestyle and clinical variables, including the presence of anxiety and depression symptoms, were analysed. Factors associated with higher clinical and radiographic severity were identified using ordinal logistic regression models. Results: Hip/knee osteoarthritis diagnosis was present in 14.1% of the Portuguese population [12.4% with knee osteoarthritis (OA) and 2.9% with hip OA]. Clinical severity was similar between people with hip (HOOS = 55.79 ± 20.88) and knee (KOOS = 55.33 ± 20.641) OA. People in the high HOOS/KOOS tertile tended to be older (64.39 ± 0.70 years), female (75.2%), overweight (39.0%) or obese (45.9%), and had multimorbidity (86.1%). Factors significantly associated with higher clinical severity tertile were age [55–64 years: odds ratio (OR) = 3.18; 65–74 years: OR = 3.25; ≥75 years: OR = 4.24], female sex (OR = 1.60), multimorbidity (OR = 1.75), being overweight (OR = 2.01) or obese (OR = 2.82), and having anxiety symptoms (OR = 1.83). Years of education was inversely associated with higher clinical severity. Factors significantly associated with higher radiographic severity were age (65–74 years: OR = 3.59; ≥75 years: OR = 3.05) and being in the high HOOS/KOOS tertile (OR = 4.91). Being a female and live in Lisbon or in the Centre region were inversely associated with the higher radiographic severity. Conclusion: Hip/knee osteoarthritis is present in ~1.1 million of Portuguese people. Age, educational level, and obesity are independently associated with HKOA clinical severity, whereas age, sex, geographic location, and clinical severity are independently associated with radiographic severity.publishersversionpublishe

EmIR: An emotional intelligent robot assistant

The development of robots that are truly sociable requires understanding how human interactions can be applied to the interaction between humans and robots. A sociable robot must be able to interact with people taking into account aspects like verbal and non-verbal communications (emotions, postures, gestures). This work presents a social robot which main goal is to provide assistance to older people in carrying out their daily activities (through suggestions or reminders). In addition, the robot presents non-verbal communications like perceiving emotions and displaying human identifiable emotions in order to express empathy. A prototype of the robot is being tested in a daycare centre in the northern area of Portugal.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. Angelo Costa thanks the FCT - Fundacao para a Ciencia e Tecnologia for the PostDoc grant SFRH/BPD/102696/2014. This work is supported by FCT within the projects UID/CEC/00319/2013 and COMPETE: POCI-01-0145-FEDER007043