The Paradigmatic Shift in Chronic Disease Management: A Longitudinal Analysis of Sensor-Based Monitoring, IoMT Architecture, and Clinical Outcomes - Debmalya Mukherjee,; Ranjan Banerjee,; Amartya Ghosh,; Pranab Gharai,; Ria pyne,; Piyali De,; Avijit Kumar Chaudhuri,; Payel Sengupta,; Soumodip Das, (The Bioscan, 2026)
The global healthcare infrastructure is currently undergoing a transformative redirection, transitioning from a reactive, episodic model of care toward a proactive, continuous, and data-driven paradigm. This evolution is necessitated by the burgeoning epidemiological burden of chronic conditions—specifically diabetes mellitus, congestive heart failure, and chronic obstructive pulmonary disease (COPD)—which historically have been managed through infrequent clinical consultations and retrospective patient self- reporting.1 Such traditional methodologies often fail to capture the transient physiological fluctuations that herald acute exacerbations, leading to suboptimal therapeutic adjustments and increased hospital readmission rates. The emergence of sensor-based monitoring, underpinned by the Internet of Medical Things (IoMT), provides a resolution to these information gaps by enabling the real-time acquisition and analysis of high-fidelity physiological data.1