Background: Stroke is one of the most common cerebral vascular diseases, usually affecting people aged 60 years and older. It leads to a variety of disabilities requiring motor and cognitive rehabilitation. Poststroke rehabilitation is critical for recovery, particularly for upper limb impairments, which affect approximately 80% of stroke survivors. Conventional rehabilitation often faces barriers such as cost, accessibility, and patient adherence. In contrast, eHealth technologies offer a promising alternative by providing accessible, cost-effective, and engaging rehabilitation solutions. Objective: While numerous systematic reviews have explored various aspects of technology-based rehabilitation for poststroke upper limb recovery, there is a notable lack of comprehensive synthesis of these findings. This gap presents challenges, primarily due to the focus on specific technologies, which complicates understanding the overall effectiveness of these interventions. Consequently, clinicians and researchers may find it difficult to assess the field holistically, potentially hindering informed decision-making in clinical practice. This review synthesizes evidence from systematic reviews evaluating the effectiveness of eHealth technology–based interventions for upper limb recovery in poststroke individuals. Two main questions are examined: (1) Are eHealth technology–based therapies more or equally effective than conventional therapies for stroke rehabilitation? (2) What are the main clinical considerations for low-cost eHealth technology–based rehabilitation? Methods: Comprehensive literature searches were conducted in PubMed, Web of Science, Scopus, Embase, and Google Scholar using predefined inclusion criteria based on the Population, Intervention, Comparison, Outcome, and Study Design (PICOS) framework. Systematic reviews published in English without date restrictions were included. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flowchart guided study selection. Methodological quality was assessed using the Assessment of Multiple Systematic Reviews (AMSTAR 2) criteria. Results: A total of 1792 records were screened, resulting in 7 systematic reviews published between 2019 and 2023 being included. These reviews encompassed 95 studies involving 2995 participants with a mean age of 58.8 years across acute, subacute, and chronic stroke phases. Interventions included telerehabilitation, mobile health (mHealth) apps, augmented reality (AR), virtual reality (VR), wearable devices, and exergames. While AR and VR demonstrated potential benefits when combined with conventional therapies (eg, AR showing significant improvements in upper limb function with a standardized mean difference 0.657; P<.001), evidence for stand-alone effectiveness remained inconclusive due to heterogeneity in study designs, intervention protocols, and outcome measures. Most reviews were rated as critically low quality due to methodological limitations. Conclusions: eHealth technologies hold promise for enhancing upper limb rehabilitation post stroke by addressing barriers such as cost and accessibility while providing engaging interventions. However, the field remains fragmented with insufficient evidence to establish clear efficacy. Future research should focus on standardizing protocols, optimizing neurorehabilitation principles such as dosage and task specificity, and improving methodological rigor to evaluate these interventions’ long-term impact better.

This paper describes CAREUP, a novel older adult healthy aging support platform based on Intrinsic Capacity (IC) monitoring. Besides standard functionalities like storing health measurement data or providing users with personalized recommendations, the platform includes novel intrinsic capacity assessment and prediction algorithms. Older adults’ performance is continuously monitored in all five IC domains—locomotion, psychology, cognition, vitality, and sensory capacity—based on measurement results and answers to questionnaires gathered using the platform’s mobile applications. The users are also presented with a machine learning-based prediction of how their intrinsic capacity might change over the following years. The platform’s operation was successfully tested with the participation of older adults and their caregivers in three countries: Austria, Italy, and Romania.

BACKGROUND By 2050, nearly 22% of the world's population will be 60 years of age or older, with Europe experiencing remarkably rapid demographic ageing. This demographic shift coincides with the increasing prevalence of chronic diseases and functional decline among older adults, challenging traditional healthcare delivery models. The World Health Organization's concept of healthy aging emphasizes the preservation of functional capabilities through the optimization of Intrinsic Capacity (IC), the totality of all physical and mental abilities across five domains: locomotion, vitality, sensory, cognition, and psychology. Digital Health Solutions (DHS) offers promising approaches to support aging populations through remote monitoring and integrated care; however, significant barriers remain, including low digital literacy and usability challenges among older adults. OBJECTIVE To evaluate the impact of a multidimensional, AI-driven digital health platform (CAREUP) on the dynamic monitoring and personalized enhancement of Intrinsic Capacity in community-dwelling older adults, integrating real-time physiological, cognitive, and behavioral data streams. METHODS A mixed-methods pilot study was conducted across three European countries (Italy, Romania, and Austria) from September to December 2024, enrolling 66 primary users (older adults aged 65 years or older) and 17 secondary users (caregivers). The CAREUP platform integrates Android applications (Careplan and Positive Health apps), smart devices for health monitoring, and an online dashboard. Primary outcomes included system usability, assessed by the System Usability Scale (SUS); user experience, measured by the User Experience Questionnaire short version (UEQ-S); and acceptance, evaluated through qualitative questionnaires. Secondary outcomes encompassed physical and mental health measures, quality of life indicators, and caregiver workload assessments at three-time points (T0, T1, T2). RESULTS Of 66 enrolled participants, 61 primary users (37 women, 24 men; mean age 73.9 years) completed the study. The overall SUS score was 68, indicating acceptable but improvable usability, with significant variations across countries. The UEQ-S score of 1.45 indicated a good overall user experience, with high Hedonic Quality (1.66) suggesting emotional appeal and Pragmatic Quality (1.23) reflecting above-average usability. Most participants (49/61, 80.3%) evaluated the platform as interesting, helpful, and efficient, with 48/61 (78.7%) willing to recommend it to friends. Secondary outcomes demonstrated stable physical and mental health, as well as maintained independence in daily activities. Technical connectivity issues and device complexity emerged as primary barriers to adoption. CONCLUSIONS The CAREUP platform demonstrated the feasibility of monitoring Intrinsic Capacity in older adults, achieving an acceptable level of usability and a positive user experience despite technical challenges. Country-specific variations in acceptance highlight the importance of cultural adaptation and digital literacy considerations in platform deployment. Future iterations should prioritise technical reliability, interface simplification, and enhanced user support to optimise adoption and sustained engagement among ageing populations. CLINICALTRIAL The study was registered on ClinicalTrials.gov with the ID number NCT05963399.

Background: Due to the high burden on health care, home-based rehabilitation (HBR) has gained increasing interest. A new HBR program for stroke survivors, containing a gaming app with upper-limb exercises, monitoring system, and virtual coach was being developed. Objective: This study aimed to assess the user requirements of an HBR tool including a gaming app, monitoring system, and virtual coach, and to examine potential differences between end users and countries. Methods: Thirteen stroke survivors, 12 caregivers, and 15 health care professionals from centers in the Netherlands, Italy, and Spain, participated in focus groups or interviews. Each center used the same interview guide with open questions about each component. An inductive thematic analysis was conducted separately at each center, and results were combined during a physical meeting. Results: User requirements were categorized into three main themes: (1) customization: aligning with individual preferences and capabilities; (2) motivational elements: these included reminders, a variety of levels and games, and ease of use; and (3) feedback elements: maintaining interactions with therapists. These themes apply to both home-based exercises as well as daily-life activities during HBR. There were minor differences between end users or centers. Conclusions: All end users across the participating countries emphasized the importance of integrating gamified exercises, monitoring, and virtual coaching into an HBR system. The user requirements for such a system can be categorized into three key areas: customization, motivational elements, and feedback elements.