J. A. Rincon

Bio: J. A. Rincon is an academic researcher from Polytechnic University of Valencia. The author has contributed to research in topics: Computer science & Multi-agent system. The author has an hindex of 9, co-authored 47 publications receiving 243 citations.

A new emotional robot assistant that facilitates human interaction and persuasion

Abstract: 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).

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks

Abstract: Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation.

Emotions detection on an ambient intelligent system using wearable devices

Abstract: 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.

Using Non-invasive Wearables for Detecting Emotions with Intelligent Agents

Abstract: 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.

Wearable-Based Affect Recognition-A Review.

Abstract: Affect recognition is an interdisciplinary research field bringing together researchers from natural and social sciences. Affect recognition research aims to detect the affective state of a person based on observables, with the goal to, for example, provide reasoning for the person's decision making or to support mental wellbeing (e.g., stress monitoring). Recently, beside of approaches based on audio, visual or text information, solutions relying on wearable sensors as observables, recording mainly physiological and inertial parameters, have received increasing attention. Wearable systems enable an ideal platform for long-term affect recognition applications due to their rich functionality and form factor, while providing valuable insights during everyday life through integrated sensors. However, existing literature surveys lack a comprehensive overview of state-of-the-art research in wearable-based affect recognition. Therefore, the aim of this paper is to provide a broad overview and in-depth understanding of the theoretical background, methods and best practices of wearable affect and stress recognition. Following a summary of different psychological models, we detail the influence of affective states on the human physiology and the sensors commonly employed to measure physiological changes. Then, we outline lab protocols eliciting affective states and provide guidelines for ground truth generation in field studies. We also describe the standard data processing chain and review common approaches related to the preprocessing, feature extraction and classification steps. By providing a comprehensive summary of the state-of-the-art and guidelines to various aspects, we would like to enable other researchers in the field to conduct and evaluate user studies and develop wearable systems.

Frontline robots in tourism and hospitality: service enhancement or cost reduction?

Abstract: Robots are being implemented in many frontline services, from waiter robots in restaurants to robotic concierges in hotels. A growing number of firms in hospitality and tourism industries introduce service robots to reduce their operational costs and to provide customers with enhanced services (e.g. greater convenience). In turn, customers may consider that such a disruptive innovation is altering the established conditions of the service-provider relationship. Based on attribution theory, this research explores how customers’ attributions about the firm motivations to implement service robots (i.e. cost reduction and service enhancement) are affecting customers’ intentions to use and recommend this innovation. Following previous research on robot’s acceptance, our research framework analyzes how these attributions may be shaped by customers’ perceptions of robot’s human-likeness and their affinity with the robot. Structural equation modelling is used to analyze data collected from 517 customers evaluating service robots in the hospitality industry; results show that attributions mediate the relationships between affinity toward the robot and customer behavioral intentions to use and recommend service robots. Specifically, customer’s affinity toward the service robot positively affects service improvement attribution, which in turn has a positive influence on customer behavioral intentions. In contrast, affinity negatively affects cost reduction attribution, which in turn has a negative effect on behavioral intentions. Finally, human-likeness has a positive influence on affinity. This research provides practitioners with empirical evidence and guidance about the introduction of service robots and its relational implications in hospitality and tourism industries. Theoretical advances and future research avenues are also discussed.

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

Abstract: The internet of things (IoT) aims to extend the internet to real-world objects, connecting smart and sensing devices into a global network infrastructure by connecting physical and virtual objects. The IoT has the potential to increase the quality of life of inhabitants and users of intelligent ambient assisted living (AAL) environments. The paper overviews and discusses the IoT technologies and their foreseen impacts and challenges for the AAL domain. The results of this review are summarized as the IoT based gerontechnology acceptance model for the assisted living domain. The model focuses on the acceptance of new technologies by older people and underscores the need for the adoption of the IoT for the AAL domain.

OpenEI: An Open Framework for Edge Intelligence

Abstract: In the last five years, edge computing has attracted tremendous attention from industry and academia due to its promise to reduce latency, save bandwidth, improve availability, and protect data privacy to keep data secure. At the same time, we have witnessed the proliferation of AI algorithms and models which accelerate the successful deployment of intelligence mainly in cloud services. These two trends, combined together, have created a new horizon: Edge Intelligence (EI). The development of EI requires much attention from both the computer systems research community and the AI community to meet these demands. However, existing computing techniques used in the cloud are not applicable to edge computing directly due to the diversity of computing sources and the distribution of data sources. We envision that there missing a framework that can be rapidly deployed on edge and enable edge AI capabilities. To address this challenge, in this paper we first present the definition and a systematic review of EI. Then, we introduce an Open Framework for Edge Intelligence (OpenEI), which is a lightweight software platform to equip edges with intelligent processing and data sharing capability. We analyze four fundamental EI techniques which are used to build OpenEI and identify several open problems based on potential research directions. Finally, four typical application scenarios enabled by OpenEI are presented.