Social Touch Gesture Recognition using Random Forest and Boosting on Distinct Feature Sets

Touch is a primary nonverbal communication channel used to communicate emotions or other social messages. Despite its importance, this channel is still very little explored in the affective computing field, as much more focus has been placed on visual and aural channels. In this paper, we investigate the possibility to automatically discriminate between different social touch types. We propose five distinct feature sets for describing touch behaviours captured by a grid of pressure sensors. These features are then combined together by using the Random Forest and Boosting methods for categorizing the touch gesture type. The proposed methods were evaluated on both the HAART (7 gesture types over different surfaces) and the CoST (14 gesture types over the same surface) datasets made available by the Social Touch Gesture Challenge 2015. Well above chance level performances were achieved with a 67% accuracy for the HAART and 59% for the CoST testing datasets respectively

Believing in BERT:Using expressive communication to enhance trust and counteract operational error in physical Human-robot interaction

Strategies are necessary to mitigate the impact of unexpected behavior in collaborative robotics, and research to develop solutions is lacking. Our aim here was to explore the benefits of an affective interaction, as opposed to a more efficient, less error prone but non-communicative one. The experiment took the form of an omelet-making task, with a wide range of participants interacting directly with BERT2, a humanoid robot assistant. Having significant implications for design, results suggest that efficiency is not the most important aspect of performance for users; a personable, expressive robot was found to be preferable over a more efficient one, despite a considerable trade off in time taken to perform the task. Our findings also suggest that a robot exhibiting human-like characteristics may make users reluctant to ‘hurt its feelings’; they may even lie in order to avoid this

Can robots tackle late-life loneliness? : Scanning of future opportunities and challenges in assisted living facilities

This future-oriented study examines the opportunities and challenges offered by social robots and communication technology when aiming to decrease emotional and social loneliness in older people residing in assisted living (AL). The paper draws on prior literature on loneliness, elder care and social robots. The aim is to scan the futures regarding technology support for the frail older people in future AL. The analytical frame was built on Robert Weiss’ division of relational functions: attachment, social integration, opportunity for nurturance, reassurance of worth, sense of reliable alliance, and guidance in stressful situations, and on a distinction between direct and indirect social robots. Our examinations show that social robots could tackle both emotional and social loneliness in assisted living by empowering people to engage in different forms of social interaction inside and outside the facility. However, ethical concerns of objectification, lack of human contact, and deception need to be thoroughly considered when implementing social robots in care for frail older people.Peer reviewe

Voisivatko robotit vahvistaa hoivakodeissa asuvien vanhojen ihmisten autonomiaa? - Tulevaisuusorientoitunut tutkimus

There is an urge to introduce high technology and robotics in care settings. Assisted living (AL) is the fastest growing form of older adults’ long-term care. Resident autonomy has become the watchword for good care. This article sheds light on the potential effects of care robotics on the sense of autonomy of older people in AL. Three aspects of the residents’ sense of autonomy are of particular interest: (a) interaction-based sense of autonomy, (b) coping-based sense of autonomy, and (c) potential-based sense of autonomy. Ethnographical data on resident autonomy in an AL facility and existing literature on care robots are utilized in studying what kind of assurances different types of robots would provide to maintain the sense of autonomy in AL. Robots could strengthen the different types of sense of autonomy in multiple ways. Different types of robots could widen the residents’ space of daily movements, sustain their capacities, and help them maintain and even create future expectations. Robots may strengthen the sense of autonomy of older persons in AL; however, they may simultaneously pose a threat. Multi-professional discussions are needed on whether robots are welcomed in care, and if they are, how, for whom, and in what areas.There is an urge to introduce high technology and robotics in care settings. Assisted living (AL) is the fastest growing form of older adults’ long-term care. Resident autonomy has become the watchword for good care. This article sheds light on the potential effects of care robotics on the sense of autonomy of older people in AL. Three aspects of the residents’ sense of autonomy are of particular interest: (a) interaction-based sense of autonomy, (b) coping-based sense of autonomy, and (c) potential-based sense of autonomy. Ethnographical data on resident autonomy in an AL facility and existing literature on care robots are utilized in studying what kind of assurances different types of robots would provide to maintain the sense of autonomy in AL. Robots could strengthen the different types of sense of autonomy in multiple ways. Different types of robots could widen the residents’ space of daily movements, sustain their capacities, and help them maintain and even create future expectations. Robots may strengthen the sense of autonomy of older persons in AL; however, they may simultaneously pose a threat. Multi-professional discussions are needed on whether robots are welcomed in care, and if they are, how, for whom, and in what areas.Peer reviewe

Social touch in human–computer interaction

Touch is our primary non-verbal communication channel for conveying intimate emotions and as such essential for our physical and emotional wellbeing. In our digital age, human social interaction is often mediated. However, even though there is increasing evidence that mediated touch affords affective communication, current communication systems (such as videoconferencing) still do not support communication through the sense of touch. As a result, mediated communication does not provide the intense affective experience of co-located communication. The need for ICT mediated or generated touch as an intuitive way of social communication is even further emphasized by the growing interest in the use of touch-enabled agents and robots for healthcare, teaching, and telepresence applications. Here, we review the important role of social touch in our daily life and the available evidence that affective touch can be mediated reliably between humans and between humans and digital agents. We base our observations on evidence from psychology, computer science, sociology, and neuroscience with focus on the first two. Our review shows that mediated affective touch can modulate physiological responses, increase trust and affection, help to establish bonds between humans and avatars or robots, and initiate pro-social behavior. We argue that ICT mediated or generated social touch can (a) intensify the perceived social presence of remote communication partners and (b) enable computer systems to more effectively convey affective information. However, this research field on the crossroads of ICT and psychology is still embryonic and we identify several topics that can help to mature the field in the following areas: establishing an overarching theoretical framework, employing better research methodologies, developing basic social touch building blocks, and solving specific ICT challenges

Humanamente só ou roboticamente acompanhado?: uma revisão da literatura sobre o impacto de Paro na população idosa

Por meio da interação com os humanos, os robôs sociais começam a desempenhar um papel importante no que diz respeito à saúde e bem-estar dos indivíduos. Esta revisão da literatura de caráter exploratório, destaca os efeitos positivos da interação do robô social de companhia Paro com a população idosa, cujos resultados se verificam a nível psicológico (redução da solidão e dos sintomas depressivos e humor mais positivo), social (aumento das interações sociais e do envolvimento em atividades) e fisiológico (redução da ansiedade, stress, pressão arterial, frequência cardíaca e aumento da qualidade do sono). Contudo, as conclusões são limitadas devido à falta de estudos sobre a matéria, sendo que todos os resultados devem ser interpretados como meramente preliminares e iniciais

Autonomous decision-making for socially interactive robots

Mención Internacional en el título de doctorThe aim of this thesis is to present a novel decision-making system based on bio-inspired concepts to decide the actions to make during the interaction between humans and robots. We use concepts from nature to make the robot may behave analogously to a living being for a better acceptance by people. The system is applied to autonomous Socially Interactive Robots that works in environments with users. These objectives are motivated by the need of having robots collaborating, entertaining or helping in educational tasks for real situations with children or elder people where the robot has to behave socially. Moreover, the decision-making system can be integrated into this kind of robots in order to learn how to act depending on the user profile the robot is interacting with. The decision-making system proposed in this thesis is a solution to all these issues in addition to a complement for interactive learning in HRI. We also show real applications of the system proposed applying it in an educational scenario, a situation where the robot can learn and interact with different kinds of people. The last goal of this thesis is to develop a robotic architecture that is able to learn how to behave in different contexts where humans and robots coexist. For that purpose, we design a modular and portable robotic architecture that is included in several robots. Including well-known software engineering techniques together with innovative agile software development procedures that produces an easily extensible architecture.El objetivo de esta tesis es presentar un novedoso sistema de toma de decisiones basado en conceptos bioinspirados para decidir las acciones a realizar durante la interacción entre personas y robots. Usamos conceptos de la naturaleza para hacer que el robot pueda comportarse análogamente a un ser vivo para una mejor aceptación por las personas. El sistema está desarrollado para que se pueda aplicar a los llamados Robots Socialmente Interactivos que están destinados a entornos con usuarios. Estos objetivos están motivados por la necesidad de tener robots en tareas de colaboración, entretenimiento o en educación en situaciones reales con niños o personas mayores en las cuales el robot debe comportarse siguiendo las normas sociales. Además, el sistema de toma de decisiones es integrado en estos tipos de robots con el fin de que pueda aprender a actuar dependiendo del perfil de usuario con el que el robot está interactuando. El sistema de toma de decisiones que proponemos en esta tesis es una solución a todos estos desafíos además de un complemento para el aprendizaje interactivo en la interacción humano-robot. También mostramos aplicaciones reales del sistema propuesto aplicándolo en un escenario educativo, una situación en la que el robot puede aprender e interaccionar con diferentes tipos de personas. El último objetivo de esta tesis es desarrollar un arquitectura robótica que sea capaz de aprender a comportarse en diferentes contextos donde las personas y los robots coexistan. Con ese propósito, diseñamos una arquitectura robótica modular y portable que está incluida en varios robots. Incluyendo técnicas bien conocidas de ingeniería del software junto con procedimientos innovadores de desarrollo de sofware ágil que producen una arquitectura fácilmente extensible.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Fabio Bonsignorio.- Secretario: María Dolores Blanco Rojas.- Vocal: Martin Stoele

Neuroscience, Artificial Intelligence, and the Case Against Solitary Confinement

Prolonged solitary confinement remains in widespread use in the United States despite many legal challenges. A difficulty when making the legal case against solitary confinement is proffering sufficiently systematic and precise evidence of the detrimental effects of the practice on inmates\u27 mental health. Given this need for further evidence, this Article explores how neuroscience and artificial intelligence (AI) might provide new evidence of the effects of solitary confinement on the human brain. This Article argues that both neuroscience and AI are promising in their potential ability to present courts with new types of evidence on the effects of solitary confinement on inmates\u27 brain circuitry. But at present, neither field has collected the type of evidence that is likely to tip the scales against solitary confinement and end the practice. This Article concludes that ending the entrenched practice of solitary confinement will likely require both traditional and novel forms of evidence. In exploring the potential effects of neuroscientific evidence on support for solitary confinement, the Article reports results from an Associate Professor of Law and McKnight Presidential Fellow, University original online experiment with a group of 250 ideologically conservative participants. The analysis finds that the introduction of brain injury reduced conservatives\u27 support for solitary confinement but not to the extent that is likely to make a policy impact. The Article argues that future, more individualized brain evidence may be of greater use, but at present neuroscience is limited in its ability to systematically measure the brain changes that inmates experience in solitary confinement. This Article then turns to AI and argues that it could be developed to provide litigators and inmates with the ability to more effectively document the detrimental effects of solitary confinement. Looking to the future, the Article lays out a vision for an AI system called Helios, named after the Homeric sun god believed to see and hear everything. The Article envisions Helios as a self-learning AI system with a mission to help inmates and their attorneys gather more systematic evidence of the effects of solitary confinement on inmate health. Helios is also a platform on which additional inmate services might one day be provided. The Article describes how Helios must be carefully designed, with particular attention given to privacy concerns. This Article is organized in seven parts. Part I describes the historical and contemporary use of solitary confinement in the United States, highlighting the known effects of solitary confinement on inmates. Part II summarizes recent constitutional challenges to the practice of solitary confinement. Part III explores the potential for integrating neuroscientific evidence into these legal challenges to solitary confinement. Part IV discusses a new online experiment to explore whether neuroscience might change public opinion on solitary confinement. In Part V, the Article transitions to a consideration of AI. The Article proposes a self-learning system, Helios, and describes how the system would operate. Part VI turns to a series of challenging ethical and legal questions about the design and implementation of Helios. Part VII briefly concludes

Automated vision-based generation of event statistics for decision support

Many tasks require surveillance and analysis in order to make decisions regarding the next course of action. The people responsible for these tasks are usually concerned with any event that affects their bottom-line. Traditionally, human operators have had to either actively man a set of video displays to determine if specific events were occurring or manually review hours of collected video data to see if a specific event occurred. Actively monitoring video stream or manually reviewing and analyzing the data collected, however, is a tedious and long process which is prone to errors due to biases and inattention. Automatically processing and analyzing the video provides an alternate way of getting more accurate results because it can reduce the likelihood of missing important events and the human factors that lead to decreased efficiency. The thesis aims to contribute to the area of using computer vision as a decision support tool by integrating detector, tracker, re-identification, activity status estimation, and event processor modules to generate the necessary event statistics needed by a human operator. The contribution of this thesis is a system that uses feedback from each of the modules to provide better target detection, and tracking results for event statistics generation over an extended period of time. To demonstrate the efficacy of the proposed system, it is first used to generate event statistics that measure productivity on multiple construction work sites. The versatility of the proposed system is also demonstrated in an indoor assisted living environment by using it to determine how much of an influence a technology intervention had on promoting interactions amongst older adults in a shared space.Ph.D

The Potential use of Social Robots in Acute Paediatric Settings: A mixed-methods exploration of feasibility, acceptance, and utility.

The hospital can be an anxious place for paediatric patients. Reducing and managing anxiety in children is important; finding tools and interventions to support this is essential to the healthcare of paediatric patients. Social robots offer a new way of interacting with children and have the potential to reduce negative emotions. Even though research has found that social robots could potentially be an anxiety-preventing tool, there is no research exploring how children play in hospital settings and which features are required for social robots to impact paediatric patients positively. There are also gaps regarding parents of paediatric patients' and healthcare professionals' views on social robots and how they feel about using them as a tool within a hospital setting. This thesis examined the feasibility of using social robots in four hospital settings to address this gap. Observations of paediatric patients revealed the importance of tactile play and games with rules as popular forms of interaction with social robots. Questionnaires and interviews gathered feedback from paediatric patients, parents, and healthcare professionals. Overall, the response to social robots was positive, with parents and healthcare professionals acknowledging their potential benefits in reducing anxiety. However, some paediatric patients did not find the social robot relaxing, and there were mixed opinions on its anxiety-reducing capabilities. While parents noticed a change in their children's negative moods and enjoyed the interaction, a few were uncertain about anxiety reduction. Healthcare professionals expressed excitement about social robots but sought further clarity on their practical implementation in a hospital setting. Despite the promising aspects, this thesis highlights the need for further research and development. Large-scale comparisons of social robots in diverse hospital settings and longitudinal studies with paediatric patients are warranted to gain deeper insights and enhance the practicality of using social robots as anxiety-reducing tools in paediatric care