Conversational affective social robots for ageing and dementia support

Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation and patient benefit remain immature. Affective human-robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and humanrobot engagement. In this paper, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centred approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarise the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement, 2) deployment in real-world settings, and 3) clinical translation

The Perceptions of People with Dementia and Key Stakeholders Regarding the Use and Impact of the Social Robot MARIO

People with dementia often experience loneliness and social isolation. This can result in increased cognitive decline which, in turn, has a negative impact on quality of life. This paper explores the use of the social robot, MARIO, with older people living with dementia as a way of addressing these issues. A descriptive qualitative study was conducted to explore the perceptions and experiences of the use and impact of MARIO. The research took place in the UK, Italy and Ireland. Semi-structured interviews were held in each location with people with dementia (n = 38), relatives/carers (n = 28), formal carers (n = 28) and managers (n = 13). The data was analyzed using qualitative content analysis. The findings revealed that despite challenges in relation to voice recognition and the practicalities of conducting research involving robots in real-life settings, most participants were positive about MARIO. Through the robot’s user-led design and personalized applications, MARIO provided a point of interest, social activities, and cognitive engagement increased. However, some formal carers and managers voiced concern that robots might replace care staff

Artificial Emotional Intelligence in Socially Assistive Robots

Artificial Emotional Intelligence (AEI) bridges the gap between humans and machines by demonstrating empathy and affection towards each other. This is achieved by evaluating the emotional state of human users, adapting the machine’s behavior to them, and hence giving an appropriate response to those emotions. AEI is part of a larger field of studies called Affective Computing. Affective computing is the integration of artificial intelligence, psychology, robotics, biometrics, and many more fields of study. The main component in AEI and affective computing is emotion, and how we can utilize emotion to create a more natural and productive relationship between humans and machines. An area in which AEI can be particularly beneficial is in building machines and robots for healthcare applications. Socially Assistive Robotics (SAR) is a subfield in robotics that aims at developing robots that can provide companionship to assist people with social interaction and companionship. For example, residents living in housing designed for older adults often feel lonely, isolated, and depressed; therefore, having social interaction and mental stimulation is critical to improve their well-being. Socially Assistive Robots are designed to address these needs by monitoring and improving the quality of life of patients with depression and dementia. Nevertheless, developing robots with AEI that understand users’ emotions and can reply to them naturally and effectively is in early infancy, and much more research needs to be carried out in this field. This dissertation presents the results of my work in developing a social robot, called Ryan, equipped with AEI for effective and engaging dialogue with older adults with depression and dementia. Over the course of this research there has been three versions of Ryan. Each new version of Ryan is created using the lessons learned after conducting the studies presented in this dissertation. First, two human-robot-interaction studies were conducted showing validity of using a rear-projected robot to convey emotion and intent. Then, the feasibility of using Ryan to interact with older adults is studied. This study investigated the possible improvement of the quality of life of older adults. Ryan the Companionbot used in this project is a rear-projected lifelike conversational robot. Ryan is equipped with many features such as games, music, video, reminders, and general conversation. Ryan engages users in cognitive games and reminiscence activities. A pilot study was conducted with six older adults with early-stage dementia and/or depression living in a senior living facility. Each individual had 24/7 access to a Ryan in his/her room for a period of 4-6 weeks. The observations of these individuals, interviews with them and their caregivers, and analysis of their interactions during this period revealed that they established rapport with the robot and greatly valued and enjoyed having a companionbot in their room. A multi-modal emotion recognition algorithm was developed as well as a multi-modal emotion expression system. These algorithms were then integrated into Ryan. To engage the subjects in a more empathic interaction with Ryan, a corpus of dialogues on different topics were created by English major students. An emotion recognition algorithm was designed and implemented and then integrated into the dialogue management system to empathize with users based on their perceived emotion. This study investigates the effects of this emotionally intelligent robot on older adults in the early stage of depression and dementia. The results of this study suggest that Ryan equipped with AEI is more engaging, likable, and attractive to users than Ryan without AEI. The long-term effect of the last version of Ryan (Ryan V3.0) was studied in a study involving 17 subjects from 5 different senior care facilities. The participants in this study experienced a general improvement in their cognitive and depression scores

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

In the advancement of human-robot interaction technology, assistive social robots have been recognized as one of potential technologies that can provide physical and cognitive supports in older persons care. However, a major challenge faced by the designers is to develop an assistive social robot with prodigious usability and user experience for older persons who were known to have physical and cognitive limitations. A considerable number of published literatures was reporting on the technological design process of assistive social robots. However, only a small amount of attention has been paid to review the usability and user experience of the robots. The objective of this paper is to provide an overview of established researches in the literatures concerning usability and user experience issues faced by the older persons when interacting with assistive social robots. The authors searched relevant articles from the academic databases such as Google Scholar, Scopus and Web of Science as well as Google search for the publication period 2000 to 2021. Several search keywords were typed such as ‘older persons’ ‘elderly’, ‘senior citizens’, ‘assistive social robots’, ‘companion robots’, ‘personal robots’, ‘usability’ and ‘user experience’. This online search found a total of 215 articles which are related to assistive social robots in elderly care. Out of which, 54 articles identified as significant references, and they were examined thoroughly to prepare the main content of this paper. This paper reveals usability issues of 28 assistive social robots, and feedbacks of user experience based on 41 units of assistive social robots. Based on the research articles scrutinized, the authors concluded that the key elements in the design and development of assistive social robots to improve acceptance of older persons were determined by three factors: functionality, usability and users’ experience. Functionality refers to ability of robots to serve the older persons. Usability is ease of use of the robots. It is an indicator on how successful of interaction between the robots and the users. To improve usability, robot designers should consider the limitations of older persons such as vision, hearing, and cognition capabilities when interacting with the robots. User experience reflects to perceptions, preferences and behaviors of users that occur before, during and after use the robots. Combination of superior functionality and usability lead to a good user experience in using the robots which in the end achieves satisfaction of older persons

A Review on Usability and User Experience of Assistive Social Robots for Older Persons

In the advancement of human-robot interaction technology, assistive social robots have been recognized as one of potential technologies that can provide physical and cognitive supports in older persons care. However, a major challenge faced by the designers is to develop an assistive social robot with prodigious usability and user experience for older persons who were known to have physical and cognitive limitations. A considerable number of published literatures was reporting on the technological design process of assistive social robots. However, only a small amount of attention has been paid to review the usability and user experience of the robots. The objective of this paper is to provide an overview of established researches in the literatures concerning usability and user experience issues faced by the older persons when interacting with assistive social robots. The authors searched relevant articles from the academic databases such as Google Scholar, Scopus and Web of Science as well as Google search for the publication period 2000 to 2021. Several search keywords were typed such as ‘older persons’ ‘elderly’, ‘senior citizens’, ‘assistive social robots’, ‘companion robots’, ‘personal robots’, ‘usability’ and ‘user experience’. This online search found a total of 215 articles which are related to assistive social robots in elderly care. Out of which, 54 articles identified as significant references, and they were examined thoroughly to prepare the main content of this paper. This paper reveals usability issues of 28 assistive social robots, and feedbacks of user experience based on 41 units of assistive social robots. Based on the research articles scrutinized, the authors concluded that the key elements in the design and development of assistive social robots to improve acceptance of older persons were determined by three factors: functionality, usability and users’ experience. Functionality refers to ability of robots to serve the older persons. Usability is ease of use of the robots. It is an indicator on how successful of interaction between the robots and the users. To improve usability, robot designers should consider the limitations of older persons such as vision, hearing, and cognition capabilities when interacting with the robots. User experience reflects to perceptions, preferences and behaviors of users that occur before, during and after use the robots. Combination of superior functionality and usability lead to a good user experience in using the robots which in the end achieves satisfaction of older persons

Immersive Technologies in Virtual Companions: A Systematic Literature Review

The emergence of virtual companions is transforming the evolution of intelligent systems that effortlessly cater to the unique requirements of users. These advanced systems not only take into account the user present capabilities, preferences, and needs but also possess the capability to adapt dynamically to changes in the environment, as well as fluctuations in the users emotional state or behavior. A virtual companion is an intelligent software or application that offers support, assistance, and companionship across various aspects of users lives. Various enabling technologies are involved in building virtual companion, among these, Augmented Reality (AR), and Virtual Reality (VR) are emerging as transformative tools. While their potential for use in virtual companions or digital assistants is promising, their applications in these domains remain relatively unexplored. To address this gap, a systematic review was conducted to investigate the applications of VR, AR, and MR immersive technologies in the development of virtual companions. A comprehensive search across PubMed, Scopus, and Google Scholar yielded 28 relevant articles out of a pool of 644. The review revealed that immersive technologies, particularly VR and AR, play a significant role in creating digital assistants, offering a wide range of applications that brings various facilities in the individuals life in areas such as addressing social isolation, enhancing cognitive abilities and dementia care, facilitating education, and more. Additionally, AR and MR hold potential for enhancing Quality of life (QoL) within the context of virtual companion technology. The findings of this review provide a valuable foundation for further research in this evolving field

Design and Development of the eBear: A Socially Assistive Robot for Elderly People with Depression

There has been tremendous progress in the field of robotics in the past decade and especially developing humanoid robots with social abilities that can assist human at a socio-emotional level. The objective of this thesis is to develop and study a perceptive and expressive animal-like robot equipped with artificial intelligence in assisting the elderly people with depression. We investigated how social robots can become companions of elderly individuals with depression and improve their mood and increase their happiness and well-being. The robotic platform built in this thesis is a bear-like robot called the eBear. The eBear can show facial expression and head gesture, can understand user\u27s emotion using audio-video sensory inputs and machine learning, can speak and show relatively accurate visual speech, and make dialog with users. the eBear can respond to their questions by querying the Internet, and even encourage them to physically be more active and even perform simple physical exercises. Besides building the robot, the eBear was used in running a pilot study in which seven elderly people with mild to severe depression interacted with the eBear for about 45 minutes three times a week over one month. The results of the study show that interacting with the eBear can increase happiness and mood of these human users as measured by Face Scale, and Geriatric Depression Scale (GDS) score systems. In addition, using Almere Model, it was concluded that the acceptance of the social agent increased over the study period. Videos of the users interaction with the eBear was analyzed and eye gaze, and facial expressions were manually annotated to better understand the behavior changes of users with the eBear. Results of these analyses as well as the exit surveys completed by the users at the end of the study demonstrate that a social robot such as the eBear can be an effective companion for the elderly people and can be a new approach for depression treatment