Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design

Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data

Advancements in AI-driven multilingual comprehension for social robot interactions: An extensive review

In the digital era, human-robot interaction is rapidly expanding, emphasizing the need for social robots to fluently understand and communicate in multiple languages. It is not merely about decoding words but about establishing connections and building trust. However, many current social robots are limited to popular languages, serving in fields like language teaching, healthcare and companionship. This review examines the AI-driven language abilities in social robots, providing a detailed overview of their applications and the challenges faced, from nuanced linguistic understanding to data quality and cultural adaptability. Last, we discuss the future of integrating advanced language models in robots to move beyond basic interactions and towards deeper emotional connections. Through this endeavor, we hope to provide a beacon for researchers, steering them towards a path where linguistic adeptness in robots is seamlessly melded with their capacity for genuine emotional engagement

The Emerging Role of Robotics in Personal Health Care: Bringing Smart Health Care Home

Affordable, accessible health care is in short supply in the U.S., due to the rapidly aging population; robotics can provide a solution to this problem. This project developed user requirements for a personal health care robot. From interviews with robotics professionals and focus groups with caregivers and the elderly, the team gained an understanding of potential users’ desired functionalities and acceptance of robots. The team developed a taxonomy to characterize robots’ interaction with users. The requirements generated by the studies were used in conjunction with this taxonomy to recommend a robot for use in personal health care. An in-home monitoring system was found to have the greatest potential to benefit the health care industry and the target demographic

Towards a framework for socially interactive robots

250 p.En las últimas décadas, la investigación en el campo de la robótica social ha crecido considerablemente. El desarrollo de diferentes tipos de robots y sus roles dentro de la sociedad se están expandiendo poco a poco. Los robots dotados de habilidades sociales pretenden ser utilizados para diferentes aplicaciones; por ejemplo, como profesores interactivos y asistentes educativos, para apoyar el manejo de la diabetes en niños, para ayudar a personas mayores con necesidades especiales, como actores interactivos en el teatro o incluso como asistentes en hoteles y centros comerciales.El equipo de investigación RSAIT ha estado trabajando en varias áreas de la robótica, en particular,en arquitecturas de control, exploración y navegación de robots, aprendizaje automático y visión por computador. El trabajo presentado en este trabajo de investigación tiene como objetivo añadir una nueva capa al desarrollo anterior, la capa de interacción humano-robot que se centra en las capacidades sociales que un robot debe mostrar al interactuar con personas, como expresar y percibir emociones, mostrar un alto nivel de diálogo, aprender modelos de otros agentes, establecer y mantener relaciones sociales, usar medios naturales de comunicación (mirada, gestos, etc.),mostrar personalidad y carácter distintivos y aprender competencias sociales.En esta tesis doctoral, tratamos de aportar nuestro grano de arena a las preguntas básicas que surgen cuando pensamos en robots sociales: (1) ¿Cómo nos comunicamos (u operamos) los humanos con los robots sociales?; y (2) ¿Cómo actúan los robots sociales con nosotros? En esa línea, el trabajo se ha desarrollado en dos fases: en la primera, nos hemos centrado en explorar desde un punto de vista práctico varias formas que los humanos utilizan para comunicarse con los robots de una maneranatural. En la segunda además, hemos investigado cómo los robots sociales deben actuar con el usuario.Con respecto a la primera fase, hemos desarrollado tres interfaces de usuario naturales que pretenden hacer que la interacción con los robots sociales sea más natural. Para probar tales interfaces se han desarrollado dos aplicaciones de diferente uso: robots guía y un sistema de controlde robot humanoides con fines de entretenimiento. Trabajar en esas aplicaciones nos ha permitido dotar a nuestros robots con algunas habilidades básicas, como la navegación, la comunicación entre robots y el reconocimiento de voz y las capacidades de comprensión.Por otro lado, en la segunda fase nos hemos centrado en la identificación y el desarrollo de los módulos básicos de comportamiento que este tipo de robots necesitan para ser socialmente creíbles y confiables mientras actúan como agentes sociales. Se ha desarrollado una arquitectura(framework) para robots socialmente interactivos que permite a los robots expresar diferentes tipos de emociones y mostrar un lenguaje corporal natural similar al humano según la tarea a realizar y lascondiciones ambientales.La validación de los diferentes estados de desarrollo de nuestros robots sociales se ha realizado mediante representaciones públicas. La exposición de nuestros robots al público en esas actuaciones se ha convertido en una herramienta esencial para medir cualitativamente la aceptación social de los prototipos que estamos desarrollando. De la misma manera que los robots necesitan un cuerpo físico para interactuar con el entorno y convertirse en inteligentes, los robots sociales necesitan participar socialmente en tareas reales para las que han sido desarrollados, para así poder mejorar su sociabilida

Fostering Resilient Aging with a Self-efficacy and Independence Enabling Robot (FRASIER)

With the percentage of the elderly population rapidly increasing as the Baby Boomer generation reaches retirement, the demand for assistive care will soon override the supply of caregivers available. Additionally, as most individuals age, the number of age-related limitations preventing them from completing everyday tasks independently may increase. Through FRASIER (Fostering Resilient Aging with a Self-efficacy and Independence Enabling Robot), the project team developed an assistive robot with a goal of providing a solution to this challenge

Ambient Assisted Living: Scoping Review of Artificial Intelligence Models, Domains, Technology, and Concerns

Background: Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)—infused applications and platforms that support their users in need in multiple activities, from health to daily living. These systems use different approaches to learn about their users and make automated decisions, known as AI models, for personalizing their services and increasing outcomes. Given the numerous systems developed and deployed for people with different needs, health conditions, and dispositions toward the technology, it is critical to obtain clear and comprehensive insights concerning AI models used, along with their domains, technology, and concerns, to identify promising directions for future work. Objective: This study aimed to provide a scoping review of the literature on AI models in AAL. In particular, we analyzed specific AI models used in AАL systems, the target domains of the models, the technology using the models, and the major concerns from the end-user perspective. Our goal was to consolidate research on this topic and inform end users, health care professionals and providers, researchers, and practitioners in developing, deploying, and evaluating future intelligent AAL systems. Methods: This study was conducted as a scoping review to identify, analyze, and extract the relevant literature. It used a natural language processing toolkit to retrieve the article corpus for an efficient and comprehensive automated literature search. Relevant articles were then extracted from the corpus and analyzed manually. This review included 5 digital libraries: IEEE, PubMed, Springer, Elsevier, and MDPI. Results: We included a total of 108 articles. The annual distribution of relevant articles showed a growing trend for all categories from January 2010 to July 2022. The AI models mainly used unsupervised and semisupervised approaches. The leading models are deep learning, natural language processing, instance-based learning, and clustering. Activity assistance and recognition were the most common target domains of the models. Ambient sensing, mobile technology, and robotic devices mainly implemented the models. Older adults were the primary beneficiaries, followed by patients and frail persons of various ages. Availability was a top beneficiary concern. Conclusions: This study presents the analytical evidence of AI models in AAL and their domains, technologies, beneficiaries, and concerns. Future research on intelligent AAL should involve health care professionals and caregivers as designers and users, comply with health-related regulations, improve transparency and privacy, integrate with health care technological infrastructure, explain their decisions to the users, and establish evaluation metrics and design guidelines. Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42022347590; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022347590This work was part of and supported by GoodBrother, COST Action 19121—Network on Privacy-Aware Audio- and Video-Based Applications for Active and Assisted Living