Background and Objectives: Wearable health technologies have become increasingly important in the remote management of cardiovascular diseases (CVDs); however, their successful implementation depends not only on technical performance but also on patient usability and technology acceptance. This study aimed to evaluate the perceived usability and technology acceptance of a wearable monitoring system among patients with CVDs and to investigate whether demographic and clinical characteristics influenced these outcomes. Materials and Methods: A cross-sectional observational study was conducted among 60 patients with CVDs enrolled in a six-month wearable monitoring program at the Medical Rehabilitation Outpatient Clinic of the Avram Iancu Clinical Hospital, Oradea, Romania. Participants used a Garmin vívosmart^® 5 fitness tracker to continuously monitor physiological and behavioral parameters. At the end of the monitoring period, perceived ease of use (PEU) was assessed using the System Usability Scale (SUS), while technology acceptance was evaluated using a Technology Acceptance Model (TAM)-based questionnaire. Descriptive statistics, reliability analysis, Spearman’s rank correlation, and multiple linear regression analyses were performed. Results: The wearable monitoring system demonstrated high PEU, with a median SUS score of 82.5 (IQR = 23.1) and a mean score of 75.5 ± 17.6. Overall, 75.0% of participants rated the system as having good or excellent usability. The SUS questionnaire demonstrated acceptable internal consistency (Cronbach’s α = 0.730; McDonald’s ω = 0.741). Technology acceptance was generally favorable, with an overall median TAM-based score of 1.33 (IQR = 0.78). Age and comorbidity burden were not associated with PEU, and no participant characteristics independently predicted SUS scores. Although the overall regression model was not statistically significant, age showed a statistically significant association with the overall TAM-based score (β = 0.328, p = 0.037). Significant positive correlations were observed between PU, self-efficacy (SE), and reverse-scored technology anxiety (TA) measure (p < 0.001). Conclusions: Patients with CVDs reported high PEU and favorable acceptance of wearable monitoring technology. While usability appeared independent of demographic and clinical characteristics, technology acceptance showed an exploratory association with age, although the overall regression model was not statistically significant. These findings support the integration of wearable monitoring systems into routine cardiovascular care and highlight the importance of patient-centered implementation strategies to promote long-term engagement.

Background: Aging is associated with increased adiposity, sarcopenia risk, and metabolic vulnerability. Digital tools may enhance adherence to nutritional strategies, but their impact on detailed body composition remains insufficiently explored. Methods: This 6-month prospective controlled longitudinal intervention study included 60 middle-aged and older adults. All participants received a smart watch and smart scale for self-monitoring. The control group attended evaluations only at baseline and study completion, while the intervention group received monthly follow-up and remote feedback. Body composition was assessed using multi-frequency BIA. Statistical analyses included paired tests, effect sizes, correlations, and linear mixed-effects models. Results: Significant reductions were observed in BMI (p < 0.001), fat mass (p = 0.003), and visceral fat (p = 0.003; Cohen’s d = 0.41). The sarcopenic index improved (p = 0.001), while skeletal muscle mass remained stable. ECW increased significantly (p = 0.010). Age was inversely associated with the magnitude of improvement. Mixed-effects modeling confirmed a time-dependent reduction in visceral fat independent of age and sex. Conclusions: A 6-month digitally assisted nutritional monitoring program was associated with favorable changes in adiposity, muscle quality, and hydration status. Multi-frequency BIA provides valuable integrative markers for monitoring nutritional interventions in aging populations.