Pilots for Healthy and Active Ageing (PHArA-ON) Project: Definition of New Technological Solutions for Older People in Italian Pilot Sites Based on Elicited User Needs

Assistive Robots for Healthcare and Human-Robot Interaction

Assistive robots are still mostly prototypes that only remotely recall human interactive dynamics [...].

Healthy Ageing: A Decision-Support Algorithm for the Patient-Specific Assignment of ICT Devices and Services

In response to rapid population ageing, digital technology represents the greatest resource in supporting the implementation of active and healthy ageing principles at clinical and service levels. However, digital information platforms that deliver coordinated health and social care services for older people to cover their needs comprehensively and adequately are still not widespread. The present work is part of a project that focuses on creating a new personalised healthcare and social assistance model to enhance older people's quality of life. This model aims to prevent acute events to favour the elderly staying healthy in their own home while reducing hospitalisations. In this context, the prompt identification of criticalities and vulnerabilities through ICT devices and services is crucial. According to the human-centred care vision, this paper proposes a decision-support algorithm for the automatic and patient-specific assignment of tailored sets of devices and local services based on adults' health and social needs. This decision-support tool, which uses a tree-like model, contains conditional control statements. Using sequences of binary divisions drives the assignation of products and services to each user. Based on many predictive factors of frailty, the algorithm aims to be efficient and time-effective. This goal is achieved by adequately combining specific features, thresholds, and constraints related to the ICT devices and patients' characteristics. The validation was carried out on 50 participants. To test the algorithm, its output was compared to clinicians' decisions during the multidimensional evaluation. The algorithm reported a high sensitivity (96% for fall monitoring and 93% for cardiac tracking) and a lower specificity (60% for fall monitoring and 27% for cardiac monitoring). Results highlight the preventive and protective behaviour of the algorithm.

Design and Evaluation of Personalized Services to Foster Active Aging: The Experience of Technology Pre-Validation in Italian Pilots

Assistive devices could promote independent living and support the active and healthy aging of an older population; however, several factors can badly influence the long-term use of new technologies. In this context, this paper presents a two-step methodology called “pre-validation” that aims to identify the factors that can bias the use of new services, thus minimizing the risk of an unsuccessful longer trial. The proposed pre-validation methodology is composed of two main phases that aim to assess the usability and the reliability of the technology assessed in a laboratory environment and the usability, acceptability, user experience, and reliability of the technology in real environments. The tested services include the socialization scenario, in which older adults are better connected to the community via technological solutions (i.e., socialization applications), and the monitoring scenario, which allows for the introduction of timely interventions (technologies involved include environmental monitoring sensors, a telepresence robot, wearable sensors, and a personalized dashboard). The obtained results underline an acceptable usability level (average System Usability Scale score > 65) for the tested technologies (i.e., socialization applications and a telepresence robot). Phase Two also underlines the good acceptability, user experience, and usability of the tested services. The statistical analysis underlines a correlation between the stress related to the use of technology, digital skills, and intention of use, among other factors. Qualitative feedback also remarks on a correlation between older adults with low digital skills and an anxiety about using technology. Positive correlation indexes were highlighted between the trust and usability scores. Eventually, future long-term trials with assistive technology should rely on motivated caregivers, be founded on a strong recruitment process, and should reassure older adults—especially the ones with low digital literacy—about the use of technology by proposing personalized training and mentoring, if necessary, to increase the trust.

Double-Bind of Recruitment of Older Adults Into Studies of Successful Aging via Assistive Information and Communication Technologies: Mapping Review

BACKGROUND

Two fields of research and development targeting the needs of the aging population of the world are flourishing, successful aging and assistive information and communication technologies (A-ICTs). The risks of ageist stereotypes emerging from how we communicate in both discourses are long known. This raises questions about whether using specific age criteria in the context of "aging deficits" can bias participation in, or compliance with, the research process by older adults who try to avoid age-related stigma.

OBJECTIVE

This study aimed to examine subject recruitment, study designs (based on age >65 years criteria), as well as discourses in research objectives and conclusions in health research on affordances of A-ICTs for older adults.

METHODS

A systematic mapping approach was used to characterize rationales, methods, stated objectives, and expected outcomes of studies indexed in PubMed and retrieved through the search logic (["Older Adults" OR Seniors OR Elderly] AND [ICT OR gerontechnology OR "Assistive Technology")] AND ("Healthy Aging" OR "Successful Aging" OR "healthy ageing" OR "successful ageing"). Inclusion criteria were as follows: the study should have recruited older participants (aged >65 years), been qualitative or quantitative research, and involved the introduction of at least one A-ICT for health-related improvements. Exclusion criteria were as follows: reviews, viewpoints, surveys, or studies that used information and communication technology for data collection instead of lifestyle interventions. Content, thematic, and discourse analyses were used to map the study characteristics and synthesize results with respect to the research question.

RESULTS

Of 180 studies that passed the search logic, 31 (17.2%) satisfied the inclusion criteria (6 randomized controlled trials, 4 purely quantitative studies, 9 focus groups, 2 observational studies, and 10 mixed methods studies). In all but one case, recruitment was pragmatic and nonrandom. Thematic analysis of rationales revealed a high likelihood of emphasis on the burdens of aging, such as rising costs of care (12/31, 39%) and age-related deficits (14/31, 45%). The objectives of the research fell under 4 categories: promotion of physical activity, acceptance and feasibility of robots and remote health monitoring systems, risk detection, and the future of A-ICTs in health care for older adults. Qualitative studies were more attentive to the nonageist research guidelines. Heterogeneity in the study results (both qualitative and quantitative) was not related to age but to individual agency, acceptance, and adherence. A combination of research strategies (participatory, longitudinal, playful, flexible, and need-based designs) proved successful in characterizing variations in study outcomes. Studies that documented recruitment dynamics revealed that fear of stigma was a factor that biased participants' engagement.

CONCLUSIONS

This review indicates that age is not an informative criterion for recruitment and retention of participants. Charting the dynamics of adoption of, and interaction with, A-ICTs is critical for advancing research and technology development.

On the Use of Assistive Technology during the COVID-19 Outbreak: Results and Lessons Learned from Pilot Studies

As a consequence of the COVID-19 emergency, frail citizens felt isolated because of social isolation, suspended and/or strongly reduced home assistance, and limited access to hospitals. In this sense, assistive technology could play a pivotal role in empowering frail older adults reducing their isolation, as well as in reinforcing the work of formal caregivers and professionals. In this context, the goal of this paper is to present four pilot studies-conducted from March 2020 to April 2021-to promptly react to COVID-19 by providing assistive technology solutions, aiming to (1) guarantee high-quality service to older adults in-home or in residential facility contexts, (2) promote social inclusion, and (3) reduce the virus transmission. In particular, four services, namely, telepresence service, remote monitoring service, virtual visit, and environmental disinfection, were designed, implemented, and tested in real environments involving 85 end-users to assess the user experience and/or preliminary assess the technical feasibility. The results underlined that all the proposed services were generally accepted by older adults and professionals. Additionally, the results remarked that the use of telepresence robots in private homes and residential facilities increased enjoyment reducing anxiety, whereas the monitoring service supported the clinicians in monitoring the discharged COVID-19 patients. It is also worth mentioning that two new services/products were developed to disinfect the environment and to allow virtual visits within the framework of a hospital information system. The virtual visits service offered the opportunity to expand the portfolio of hospital services. The main barriers were found in education, technology interoperability, and ethical/legal/privacy compliance. It is also worth mentioning the key role played by an appropriate design and customer needs analysis since not all assistive devices were designed for older persons.

Machine Learning-Based Predicted Age of the Elderly on the Instrumented Timed Up and Go Test and Six-Minute Walk Test

A decrease in dynamic balance ability (DBA) in the elderly is closely associated with aging. Various studies have investigated different methods to quantify the DBA in the elderly through DBA evaluation methods such as the timed up and go test (TUG) and the six-minute walk test (6MWT), applying the G-Walk wearable system. However, these methods have generally been difficult for the elderly to intuitively understand. The goal of this study was thus to generate a regression model based on machine learning (ML) to predict the age of the elderly as a familiar indicator. The model was based on inertial measurement unit (IMU) data as part of the DBA evaluation, and the performance of the model was comparatively analyzed with respect to age prediction based on the IMU data of the TUG test and the 6MWT. The DBA evaluation used the TUG test and the 6MWT performed by 136 elderly participants. When performing the TUG test and the 6MWT, a single IMU was attached to the second lumbar spine of the participant, and the three-dimensional linear acceleration and gyroscope data were collected. The features used in the ML-based regression model included the gait symmetry parameters and the harmonic ratio applied in quantifying the DBA, in addition to the features of description statistics for IMU signals. The feature set was differentiated between the TUG test and the 6MWT, and the performance of the regression model was comparatively analyzed based on the feature sets. The XGBoost algorithm was used to train the regression model. Comparison of the regression model performance according to the TUG test and 6MWT feature sets showed that the performance was best for the model using all features of the TUG test and the 6MWT. This indicated that the evaluation of DBA in the elderly should apply the TUG test and the 6MWT concomitantly for more accurate predictions. The findings in this study provide basic data for the development of a DBA monitoring system for the elderly.

Integration and Deployment of Cloud-Based Assistance System in Pharaon Large Scale Pilots—Experiences and Lessons Learned

The EU project Pharaon aims to support older European adults by integrating digital services, tools, interoperable open platforms, and devices. One of the objectives is to validate the integrated solutions in large-scale pilots. The integration of mature solutions and existing systems is one of the preconditions for the successful realization of the different aims of the pilots. One such solution is an intelligent, privacy-aware home-care assistance system, SmartHabits. After briefly introducing the Pharaon and SmartHabits, the authors propose different Pharaon models in the Ambient/Active Assisted Living (AAL) domain, namely the Pharaon conceptual model, Pharaon reference logical architecture view, AAL ecosystem model, meta AAL ecosystem model, and Pharaon ecosystem and governance models. Building on the proposed models, the authors provide details of the holistic integration and deployment process of the SmartHabits system into the Pharaon ecosystem. Both technical and supporting integration challenges and activities are discussed. Technical activities, including syntactic and semantic integration and securing the transfer of the Pharaon sensitive data, are among the priorities. Supporting activities include achieving legal and regulatory compliance, device procurement, and use-case co-designing in COVID-19 conditions.