Exploring real-time patient monitoring and data analytics with IoT-based smart healthcare monitoring

Abstract

This research study endeavours to explore the dynamic temporal variations in patient health parameters, specifically heart rate, temperature, and Systolic Blood Pressure (SBP), within the context of a synthetic patient dataset. The analysis of heart rate data revealed distinct patterns of temporal variation, characterized by cyclic fluctuations within each hour and an overall increasing trend over the observation period. These findings Highlights the influence of circadian rhythms, potential associations with physical activity and stress, and the broader physiological implications for patient health. The examination of temperature data exhibited analogous cyclic patterns and an increasing trend, prompting considerations of circadian rhythms and external factors such as environmental temperature and physiological health. Conversely, SBP data demonstrated fluctuations without a discernible trend, highlighting the complex nature of blood pressure regulation and its susceptibility to a myriad of physiological and external influences. This study provides a foundational understanding of patient health parameter dynamics and emphasizes the need for more extensive research to elucidate the underlying mechanisms and clinical implications. The insights gleaned from this investigation hold the potential to inform healthcare practitioners and researchers in the realms of patient monitoring and personalized healthcare, ultimately enhancing the quality of patient care and decision-making in clinical settings.