A Conceptual Framework for Remote Patient Monitoring Using the Internet of Things
Tannmay Gupta · 2024
Any procedure that must be closely watched to guarantee that the accepted norms and practices are carefully followed must be monitored, and clinical trial management is no different. Given that there are people and subjects involved, this is among the procedures that need to be watched over the most. Technological approaches can be applied to clinical trial monitoring to accelerate the procedure and, as a result, increase accuracy. This study develops a unique mayfly-optimized kernel-adaptive artificial neural network (MFO-KANN) algorithm and a conceptual model for clinical testing surveillance leveraging physiological records from wearable sensors. For pre-processing and feature extraction, accordingly, min-max normalization and principal component analysis (PCA) are used. The proposed approach is then utilized to decide whether or not to enable a person to complete the experiment. This paper provides guidelines for remotely monitoring clinical trials, which the research group can utilize to improve its decision-making.