NeuroCare Nexus-Intelligent Remote Patient Monitoring for Home Healthcare: A Review of AI-Driven Physiological Monitoring, Anomaly Detection, Clinical Decision Support, and Connected Care

Remote patient monitoring (RPM) is increasingly used to extend clinical oversight into the home, particularly for people living with chronic disease. Connectivity alone does not make monitoring clinically useful: readings must be trustworthy, interpreted against the individual patient, routed to the right person, and acted upon. This focused narrative review examines intelligent RPM for home healthcare across connected themes: care-delivery evidence, physiological and activity sensing, artificial intelligence (AI) and machine learning (ML), physiological anomaly detection, alerting and alarm fatigue, clinical decisionsupport, medication adherence, patient–caregiver–clinician collaboration, and security, interoperability, and reliability. Literature was identified through ScienceDirect, SpringerLink, PubMed, JMIR, and Crossref-indexed IEEE and other publisher records, with emphasis on work published from 2020 to 2026. The evidence indicates that structured RPM can benefit selected opulations, but effects vary across conditions and outcomes. Algorithm studies often report strong retrospective performance, whereas evaluated RPM interventions still rely mostly on heuristic thresholds, and few validated algorithms have been tested in clinical trials. Baseline-relative detection on wearable data has shown promise in large cohort studies, while signal artefact, false alerts, limited external validation, and weak integration of adherence and caregiver roles remain unresolved. The review identifies the comparison between generic fixed thresholds and personalized temporal models, evaluated under realistic data-quality and alert-burden conditions, as a central open question. Future home-health platforms should combine quality-aware sensing, transparent safety rules, individualized trend analysis, tiered role-aware alerting, and clinician oversight.