Integrating Eye Gaze Estimation with the Internet of Medical Things (IoMT) for Individualized and Efficient Healthcare

Adding Eye Gaze Estimation to the Internet of Medical Things (IoMT) marks a shift in healthcare diagnostic and treatment procedures. The clinical effects of merging these two breakthrough technologies in pediatric health care are examined in this study. Eye gazing statistics reveal a child's cognitive, emotional, and social development. Healthcare practitioners can remotely view and analyze these visual attention patterns in real-time using the Internet of Medical Things (IoMT) infrastructure to provide timely, evidence-based interventions. This discussion focuses on how technology may improve evaluation tools, customize care regimens, and remotely monitor patients. Privacy and informed permission are also considered ethical elements that validate parents' worries and ensure proper technology use. Our study found that eye gaze estimation with the Internet of Medical Things (IoMT) can improve tailored and efficient healthcare and discusses this integration's clinical uses, technological features, dataset, and ethical considerations, revealing its transformative potential for personalized and efficient treatment. The research examines this integration's clinical, technological, and moral aspects, proposing it could change pediatric healthcare. Finally, the paper emphasizes the importance of datasets in improving gaze estimate algorithms and predicting future advances.