A multimodal conversational coach for active ageing based on sentient computing and m-health

As Life Expectancy Increases, It Has Become More Necessary To Find Ways To Support Healthy Ageing. A Number Of Active Ageing Initiatives Are Being Developed Nowadays To Foster Healthy Habits In The Population. This Paper Presents Our Contribution To These Initiatives In The Form Of A Multimodal Conversational Coach That Acts As A Coach For Physical Activities. The Agent Can Be Developed As An Android App Running On Smartphones And Coupled With Cheap Widely Available Sport Sensors In Order To Provide Meaningful Coaching. It Can Be Employed To Prepare Exercise Sessions, Provide Feedback During The Sessions, And Discuss The Results After The Exercise. It Incorporates An Affective Component That Informs Dynamic User Models To Produce Adaptive Interaction Strategies.Spanish project, Grant/Award Number:TEC2017-88048-C2-2-R and TRA2016-78886-C3-1-

Incorporating android conversational agents in m-learning apps

Smart Mobile Devices Have Fostered New Learning Scenarios That Demand Sophisticated Interfaces. Multimodal Conversational Agents Have Became A Strong Alternative To Develop Human-Machine Interfaces That Provide A More Engaging And Human-Like Relationship Between Students And The System. The Main Developers Of Operating Systems For Such Devices Have Provided Application Programming Interfaces For Developers To Implement Their Own Applications, Including Different Solutions For Developing Graphical Interfaces, Sensor Control And Voice Interaction. Despite The Usefulness Of Such Resources, There Are No Strategies Defined For Coupling The Multimodal Interface With The Possibilities That These Devices Offer To Enhance Mobile Educative Apps With Intelligent Communicative Capabilities And Adaptation To The User Needs. In This Paper, We Present A Practical M-Learning Application That Integrates Features Of Android Application Programming Interfaces On A Modular Architecture That Emphasizes Interaction Management And Context-Awareness To Foster User-Adaptively, Robustness And Maintainability.This work was supported in part by Projects MINECO TEC2012-37832-C02-01, CICYT TEC2011-28626-C02-02, CAM CONTEXTS (S2009/TIC-1485

Social robots as communication partners to support emotional well-being

Interpersonal communication behaviors play a significant role in maintaining emotional well being. Self-disclosure is one such behavior that can have a meaningful impact on our emotional state. When we engage in self-disclosure, we can receive and provide support, improve our mood, and regulate our emotions. It also creates a comfortable space to share our feelings and emotions, which can have a positive impact on our overall mental and physical health. Social robots are gradually being introduced in a range of social and health settings. These autonomous machines can take on various forms and shapes and interact with humans using social behaviors and rules. They are being studied and introduced in psychosocial health interventions, including mental health and rehabilitation settings, to provide much- needed physical and social support to individuals. In my doctoral thesis, I aimed to explore how humans self-disclose and express their emotions to social robots and how this behavior can affect our perception of these agents. By studying speech-based communication interactions between humans and social robots, I wanted to investigate how social robots can support human emotional well-being. While social robots show great promise in offering social support, there are still many questions to consider before deploying them in actual care contexts. It is important to carefully evaluate their utility and scope in interpersonal communication settings, especially since social robots do not yet offer the same opportunities as humans for social interactions. My dissertation consists of three empirical chapters that investigate the underlying psychological mechanisms of perception and behaviour within human–robot communication and their potential deployment as interventions for emotional wellbeing. Chapter 1 offers a comprehensive introduction to the topic of emotional well-being and self-disclosure from a psychological perspective. I begin by providing an overview of the existing literature and theory in this field. Next, I delve into the social perception of social robots, presenting a theoretical framework to help readers understand how people view these machines. To illustrate this, I review some of the latest studies on social robots in care settings, as well as those exploring how robots can encourage people to self-disclose more about themselves. Finally, I explore the key concepts of self disclosure, including how it is defined, operationalized, and measured in experimental psychology and human–robot interaction research. In my first empirical chapter, Chapter 2, I explore how a social robot’s embodiment influences people’s disclosures in measurable terms, and how these disclosures differ from disclosures made to humans and disembodied agents. Chapter 3 studies how prolonged and intensive long-term interactions with a social robot affect people’s self-disclosure behavior towards the robot, perceptions of the robot, and how it affected factors related to well-being. Additionally, I examine the role of the interaction’s discussion theme. In Chapter 4, the final empirical chapter, I test a long-term and intensive social robot intervention with informal caregivers, people living with considerably difficult life situations. I investigate the potential of employing a social robot for eliciting self-disclosure among informal caregivers over time, supporting their emotional well-being, and implicitly encouraging them to adapt emotion regulation skills. In the final discussion chapter, Chapter 5, I summarise the current findings and discuss the contributions, implications and limitations of my work. I reflect on the contribution and challenges of this research approach and provide some future directions for researchers in the relevant fields. The results of these studies provide meaningful evidence for user experience, acceptance, and trust of social robots in different settings, including care, and demonstrate the unique psychological nature of these dynamic social interactions with social robots. Overall, this thesis contributes to the development of social robots that can support emotional well-being through self-disclosure interactions and provide insights into how social robots can be used as mental health interventions for individuals coping with emotional distress