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

Challenges and opportunities in diabetes self-management education and support : the analyses of diabetes mobile applications and provider documentation patterns

Diabetes mellitus is one of the most prevalent chronic diseases in the United States. As a disease with long-term complications requiring changes in management, diabetes requires not only education at the time of diagnosis, but ongoing diabetes self-management education. The goal of this dissertation is to identify challenges and opportunities in diabetes self-management education and support through the analyses of diabetes mobile applications and provider documentation patterns. This dissertation includes three specific areas. First, we compared features of current diabetes mobile apps to the American Association of Diabetes Educators Self-Care Behaviors(TM) guidelines. A multidisciplinary team analyzed and classified the features of each eligible app based on the guidelines. The results show an unbalanced diabetes mobile apps development trend. Many apps were designed to support the behavior of Healthy Eating, Monitoring, Taking Medication and Being Active. Few apps explore the behavior of Problem Solving, Healthy Coping and Reducing Risks. Second, we identified barriers in features and usability related to the needs of older people with diabetes for diabetes self-management applications. We conducted focus groups with 10 older people with diabetes. The features that participants liked most for the diabetes self-management applications were documentation, information and goal setting. Thematic analysis revealed that usability was their primary concern about diabetes self-management applications in managing diabetes conditions. The average System Usability Scale score was 48 out of 100, which is considered not acceptable. It suggests current diabetes self-management applications do not provide evidence-based, usable features for diabetes self-management and may not fulfill the needs of older people with diabetes. Third, we collected 200 clinic notes of follow-up visits for 100 adults with diabetes and studied the History of Present Illness (HPI) and Impression and Plan (I&P) sections. The results show that Monitoring was the most common self-care behavior mentioned in both HPI and I&P sections. Being Active was the least common self-care behavior mentioned in the HPI section and Healthy Coping was the least common self-care behavior mentioned in the I&P section. We found providers delivered more information on Healthy Eating to men compared to women in I&P section. Generally, providers delivered diabetes self-management education to people with diabetes regardless of patient characteristics. It indicates a lack of patient-centered education when people with diabetes visit providers for ongoing management. In summary, the main contribution of this dissertation to the field of health informatics is the identification of challenges and opportunities in diabetes self-management education when people with diabetes, especially for older people, using diabetes mobile apps. It also provides verification whether healthcare providers deliver evidence-based and patient-centered diabetes education during follow-up visiting

Studies on Inequalities in Information Society. Proceedings of the Conference, Well-Being in the Information Society

Siirretty Doriast

MOTIBOT: IL COACH VIRTUALE PER INTERVENTI DI COPING SANO PER ADULTI CON DIABETE MELLITO

Il diabete mellito (DM) è una malattia metabolica autogestita, in cui se l'individuo non è motivato o non è in grado di gestire regolarmente il proprio DM, i risultati medici e psicosociali saranno scarsi. Il DM è più di una condizione di salute fisica: ha impatti comportamentali, fisiologici, psicologici e sociali, e richiede alti livelli di motivazione per seguire le raccomandazioni cliniche e adottare comportamenti sani. A questo scopo, le linee guida dell'American Association of Diabetes Educators (AADE) hanno introdotto il costrutto di coping sano per identificare le strategie di coping per ridurre i sintomi di depressione, ansia, stress e disagio emotivo legato al diabete, migliorando anche il benessere degli adulti con DM. In questo contesto, i Virtual Coaches (VCs) sono diventati un importante risorsa nel supporto e nella gestione delle barriere comuni nel contesto dell'aderenza ai comportamenti sani tra gli adulti con DM. Tuttavia, pochi sono i VC specificamente sviluppati a fornire supporto psicosociale agli adulti con DM. L'obiettivo principale della presente tesi è stato, infatti, lo sviluppo di un VC per fornire supporto psicosociale agli adulti con DM di tipo 1 (T1DM) o DM di tipo 2 (T2DM). Più specificamente, questo VC mirava a motivare gli adulti con DM a ridurre sintomi di depressione, ansia, stress, il disagio emotivo legato al diabete, e a migliorare il loro benessere, incoraggiandoli ad acquisire e coltivare strategie di coping psicosociale sano. Queste abilità di coping facevano riferimento alle linee guida dell'AADE e quindi alla pratica della meditazione; in questo studio è stata, infatti, applicata la Mindfulness-Based Cognitive Therapy. La presente tesi è articolata secondo tre studi. Lo studio 1 mirava a fornire prove meta-analitiche sull'efficacia degli interventi eHealth nel sostenere il benessere psicosociale e medico degli adulti con T1DM o T2DM. Lo studio 2 mirava a testare il prototipo del VC simulato, cioè Wizard of Oz (WOZ), attraverso la piattaforma di messaggistica WhatsApp per 6 settimane, con due sessioni a settimana. In particolare, questo studio ha indagato l'accettabilità preliminare e la User Experience (UX) del protocollo di intervento, che sarà incorporato nel futuro VC. Infatti, il metodo di progettazione è stato duplice. Da un lato, è stato applicato il metodo WOZ, in cui gli studenti di psicologia credevano di interagire con un VC; invece, stavano comunicando con un essere umano. Dall'altro lato, è stato utilizzato il modello Obesity-Related Behavioural Intervention Trials (ORBIT), in particolare le sue prime fasi, poiché favorisce un approccio iterativo. Lo studio 3, seguendo le fasi successive del modello ORBIT, mirava a valutare l'efficacia preliminare del VC, chiamato Motibot - abbreviazione di Motivational bot - sviluppato attraverso una combinazione di Natural Language Processing (NLU) e regole pre-strutturate. Un totale di 13 adulti italiani con DM (Mage = 30.08, SD = 10.61) hanno interagito con Motibot attraverso l'applicazione di messaggistica Telegram per 12 sessioni, in cui il paziente poteva pianificare l'appuntamento secondo le sue esigenze: ha interagito con Motibot una o due sessioni a settimana. Motibot è stato percepito come motivante, incoraggiante e capace di innescare un'auto-riflessione sulle proprie emozioni: gli utenti e i pazienti hanno riferito di aver avuto un'esperienza molto positiva con Motibot. Motibot può essere uno strumento utile per fornire supporto psicosociale agli adulti con DM; potrebbe essere prescritto dal diabetologo come misura preventiva per il benessere del paziente e/o quando il paziente presenta sintomi psicosociali lievi e moderati. L'approccio di design centrato sull'utente e il concetto di bidirezionalità tra fattori psicosociali e medici sono punti chiave nello sviluppo di un trattamento digitale personalizzato.Diabetes Mellitus (DM) is a self-managed, metabolic disease, in which if the individual is unwilling, unmotivated, or unable to regularly self-manage their DM, the medical and psychosocial outcomes will be poor. Indeed, DM is more than a physical health condition: it has behavioural, physiological, psychological, and social impacts, and demands high levels of motivation in order to follow the clinical recommendations and adopt healthy behaviours. To this end, the American Association of Diabetes Educators (AADE) guidelines introduced the healthy coping construct to identify healthy coping strategies for reducing symptoms of depression, anxiety, stress, and diabetes-related emotional distress while also improving the well-being of adults with DM. Virtual Coaches (VCs) have recently become more prevalent in the support and management of common barriers in the context of adherence to healthy behaviours among adults with DM, in particular those regarding medical and physical behaviours. However, few VCs were found to be specifically aimed at providing psychosocial support to adults with DM. The main aim of the present thesis was, indeed, the development and implementation of a VC for the provision of psychosocial support to adults with Type 1 (T1DM) or Type 2 DM (T2DM). More specifically, this VC aimed at motivating adults with DM to reduce depression, anxiety, perceived stress symptoms, diabetes-related emotional distress, and improve their well-being, by encouraging them to acquire and cultivate psychosocial healthy coping strategies. These coping skills referred to the AADE guidelines and thus to practicing meditation; in this study, the Mindfulness-Based Cognitive Therapy has been applied. The present thesis is articulated according to three studies. Study 1 aimed at providing meta-analytical evidence on the efficacy of eHealth interventions in supporting the psychosocial and medical well-being of adults with T1DM or T2DM. Study 2 aimed at testing the prototype of the simulated VC, namely Wizard of Oz (WOZ), via the WhatsApp messaging platform for 6-week, with two sessions per week. In particular, this study investigated the preliminary acceptability and the User Experience (UX) of the intervention protocol, which will be incorporated into the future VC. Indeed, the design method was two-fold. On the one hand, the WOZ method was applied, in which psychology students believed that they were interacting with a VC, instead they were communicating with a human being. On the other hand, the Obesity-Related Behavioural Intervention Trials (ORBIT) model was used, particularly its early phases, since it favours an iterative approach. Study 3, following the next phases of the ORBIT model, aimed at assessing the preliminary efficacy of the VC, called Motibot—the abbreviation for Motivational bot—developed through a combination of Natural Language Processing (NLU) and hand-crafted rules. A total of 13 Italian adults with DM (Mage = 30.08, SD = 10.61) interacted with Motibot through the Telegram messaging application for 12 sessions, in which the patient planned the appointment according to his/her needs: he/she interacted with Motibot one or two sessions per week. Therefore, Motibot was perceived as motivating, encouraging and able to trigger self-reflection on one’s own emotions: users and patients reported having a very positive experience with Motibot. Motibot, thus, can be a useful tool to provide psychosocial support to adults with DM; as such, it might be prescribed by the diabetologist as a preventive measure for the patient’s well-being and/or when the patient presents mild and moderate psychosocial symptoms. The user-centred design approach and the concept of bidirectionality between psychosocial and medical factors are key points in the development of a personalised treatment within the digital intervention

Challenges with Voice Assistants for the Elderly in Semi-Public Spaces

Voice Assistants such as Amazon Alexa and Google Home have recently made inroads into all walks of life as is evident from their popularity, and the growing number of users. Traditionally, research on elderly people with voice assistants has focused on private spaces - bedrooms, kitchens, and living rooms. Due to privacy concerns, ethical issues, legal issues, and noisy environments, their use in public and semi-public spaces are discouraged. However, by carefully mitigating these concerns, voice assistants could still find applications in semi-public spaces for elderly people. This paper summarizes the preliminary insights from 8 interviews that we conducted with elderly people and throws light on the potential areas where voice assistants could be used in semi-public spaces.Peer reviewe

Development and comparison of customized voice-assistant systems for independent living older adults

Voice-controlled in-home personal assistants have great potential to assist older adults. This thesis explores the aspects of human-computer interface design, specifically a voice assistant, to help older adults manage their personal health, especially in the case of chronic health conditions. In our previous work, we have built a web interface for caregivers to monitor older adults' health changes based on in-home sensor data from motion sensors, bed sensors, and depth sensors. Data collected from these sensors are stored in servers and processed using several algorithms to obtain health and activity parameters including gait, fall risk, detect fall, motion patterns, sleep, heart rate, and respiration rate, as well as to generate health alerts. The sensor system with automated health alerts and care coordination has been shown to help seniors maintain better functionality. In our current research project, we focus on developing a consumer interface for older adults and their designated trusted others that can provide health information on-demand, based on spoken queries. The health information is presented as both audio and visual displays and uses graphical visualizations and linguistic summaries of the sensor data trends and changes. The goal is to present data in a form that is simple to understand. To accomplish our objective of creating an easy-to-use-and-understand health data interface for older adults, we explore voice-controlled, in-home personal assistants as a solution. Two voice assistant platforms with displays were selected for implementation and testing, namely, the Amazon Echo Show and the Lenovo Smart Display with Google Assistant.by Shradha ShaliniIncludes bibliographical reference

Smart Health Internet of Thing for Continuous Glucose Monitoring: a Survey

Health monitoring system allows patients to monitor the health-related problem to avoid further complications which could result in loss of life. Smart health is one of the categories of a health monitoring system that uses Smartphone’s and sensors to effectively monitor patient health status. However, the smart health internet of thing methods for glucose monitoring still does not provide accurate glucose reading. Hence, diabetes patient can easily loss life. To help understand this challenge, a comprehensive survey focused on smart health internet of thing methods for continuous glucose monitoring was conducted. The paper discusses the benefit and challenge of each method applicable to glucose monitoring. It was observed that several smart health methods required sensor to function. Smart vehicles and remote monitoring have less attention. However, when accommodates can provide future opportunities

Design and formative evaluation of a virtual voice-based coach for problem-solving treatment: Observational study

BACKGROUND: Artificial intelligence has provided new opportunities for human interactions with technology for the practice of medicine. Among the recent artificial intelligence innovations, personal voice assistants have been broadly adopted. This highlights their potential for health care-related applications such as behavioral counseling to promote healthy lifestyle habits and emotional well-being. However, the use of voice-based applications for behavioral therapy has not been previously evaluated. OBJECTIVE: This study aimed to conduct a formative user evaluation of Lumen, a virtual voice-based coach developed as an Alexa skill that delivers evidence-based, problem-solving treatment for patients with mild to moderate depression and/or anxiety. METHODS: A total of 26 participants completed 2 therapy sessions-an introductory (session 1) and a problem-solving (session 2)-with Lumen. Following each session with Lumen, participants completed user experience, task-related workload, and work alliance surveys. They also participated in semistructured interviews addressing the benefits, challenges and barriers to Lumen use, and design recommendations. We evaluated the differences in user experience, task load, and work alliance between sessions using 2-tailed paired t tests. Interview transcripts were coded using an inductive thematic analysis to characterize the participants\u27 perspectives regarding Lumen use. RESULTS: Participants found Lumen to provide high pragmatic usability and favorable user experience, with marginal task load during interactions for both Lumen sessions. However, participants experienced a higher temporal workload during the problem-solving session, suggesting a feeling of being rushed during their communicative interactions. On the basis of the qualitative analysis, the following themes were identified: Lumen\u27s on-demand accessibility and the delivery of a complex problem-solving treatment task with a simplistic structure for achieving therapy goals; themes related to Lumen improvements included streamlining and improved personalization of conversations, slower pacing of conversations, and providing additional context during therapy sessions. CONCLUSIONS: On the basis of an in-depth formative evaluation, we found that Lumen supported the ability to conduct cognitively plausible interactions for the delivery of behavioral therapy. Several design suggestions identified from the study including reducing temporal and cognitive load during conversational interactions, developing more natural conversations, and expanding privacy and security features were incorporated in the revised version of Lumen. Although further research is needed, the promising findings from this study highlight the potential for using Lumen to deliver personalized and accessible mental health care, filling a gap in traditional mental health services

The SHAPES Smart Mirror Approach for Independent Living, Healthy and Active Ageing

The benefits that technology can provide in terms of health and support for independent living are in many cases not enough to break the barriers that prevent older adults from accepting and embracing technology. This work proposes a hardware and software platform based on a smart mirror, which is equipped with a set of digital solutions whose main focus is to overcome older adults’ reluctance to use technology at home and wearable devices on the move. The system has been developed in the context of two use cases: the support of independent living for older individuals with neurodegenerative diseases and the promotion of physical rehabilitation activities at home. Aspects such as reliability, usability, consumption of computational resources, performance and accuracy of the proposed platform and digital solutions have been evaluated in the initial stages of the pilots within the SHAPES project, an EU-funded innovation action. It can be concluded that the SHAPES smart mirror has the potential to contribute as a technological breakthrough to overcome the barriers that prevent older adults from engaging in the use of assistive technologies.Los beneficios que la tecnología puede brindar en términos de salud y apoyo para la vida independiente en muchos casos no son suficientes para romper las barreras que impiden que los adultos mayores acepten y adopten la tecnología. Este trabajo propone una plataforma de hardware y software basada en un espejo inteligente, la cual está equipada con un conjunto de soluciones digitales cuyo enfoque principal es superar la reticencia de los adultos mayores a usar tecnología en el hogar y dispositivos portátiles en movimiento. El sistema se ha desarrollado en el contexto de dos casos de uso: el apoyo a la vida independiente de personas mayores con enfermedades neurodegenerativas y la promoción de actividades de rehabilitación física en el hogar. Aspectos como la fiabilidad, la usabilidad, el consumo de recursos informáticos, el rendimiento y la precisión de la plataforma y las soluciones digitales propuestas se han evaluado en las etapas iniciales de los pilotos del proyecto SHAPES, una acción de innovación financiada con fondos europeos. Se puede concluir que el espejo inteligente SHAPES tiene el potencial de contribuir como un avance tecnológico para superar las barreras que impiden que los adultos mayores se involucren en el uso de tecnologías de asistencia

Engaging older adults with age-related macular degeneration in the design and evaluation of mobile assistive technologies

Ongoing advances in technology are undoubtedly increasing the scope for enhancing and supporting older adults’ daily living. The digital divide between older and younger adults, however, raises concerns about the suitability of technological solutions for older adults, especially for those with impairments. Taking older adults with Age-Related Macular Degeneration (AMD) – a progressive and degenerative disease of the eye – as a case study, the research reported in this dissertation considers how best to engage older adults in the design and evaluation of mobile assistive technologies to achieve sympathetic design of such technologies. Recognising the importance of good nutrition and the challenges involved in designing for people with AMD, this research followed a participatory and user-centred design (UCD) approach to develop a proof–of–concept diet diary application for people with AMD. Findings from initial knowledge elicitation activities contribute to the growing debate surrounding the issues on how older adults’ participation is initiated, planned and managed. Reflections on the application of the participatory design method highlighted a number of key strategies that can be applied to maintain empathic participatory design rapport with older adults and, subsequently, lead to the formulation of participatory design guidelines for effectively engaging older adults in design activities. Taking a novel approach, the final evaluation study contributed to the gap in the knowledge on how to bring closure to the participatory process in as positive a way as possible, cognisant of the potential negative effect that withdrawal of the participatory process may have on individuals. Based on the results of this study, we ascertain that (a) sympathetic design of technology with older adults will maximise technology acceptance and shows strong indicators for affecting behaviour change; and (b) being involved in the design and development of such technologies has the capacity to significantly improve the quality of life of older adults (with AMD)