A Bibliometric Analysis of IoT-Integrated Wearable Systems for Healthcare: Trends, Collaborations and Research Gaps

The integration of wearable devices and Internet of Things (IoT) technologies has transformed healthcare, particularly in patient monitoring. While current systems primarily alert healthcare professionals, they often overlook the critical role of family engagement, which is essential for emotional support and timely intervention. This study investigates research trends and gaps in IoT-integrated wearable healthcare systems, focusing on predictive monitoring and family involvement for ventilator patients. Data was collected from Scopus and Web of Science databases, covering publications from the last decade. We conducted both descriptive and bibliometric analyses using tools such as VOSviewer and Bibliometrix to trace research progress over time, identify leading journals, top authors, and influential countries, and analyze keyword co-occurrence to reveal well-researched areas. Additionally, content analysis was applied to pinpoint emerging research hotspots within the last five years. Findings highlight a growing focus on predictive monitoring technologies and IoT solutions in healthcare but reveal a critical void in family-centered remote monitoring frameworks. Few studies effectively integrate family support with real-time patient care, particularly in ventilator management. This analysis emphasizes the need for collaborative platforms connecting patients, families, and healthcare providers through IoT-enabled wearables. Integrating predictive analytics can further optimize emergency response and mitigate limitations of traditional alarm-based systems, which are susceptible to human oversight. This study offers actionable insights for developing holistic, patient-centric solutions in wearable healthcare technologies.