Adaptive Sensor Fusion for Personalized Hypoglycemia Risk Prediction in Elderly Diabetic Patients

Author(s)	Mr. Arun Karthik V, Mr. Raghul Sachin R, Ms. Charulatha R T
Country	India
Abstract	A systematized method for personalized hypoglycaemia risk prediction in elderly diabetic patients using adaptive multi-sensor fusion is disclosed. The wearable apparatus integrates a glucose sensor, a photoplethysmography sensor, an accelerometer-gyroscope unit, and a skin conductance sensor to continuously acquire glucose trends, heart rate variability, gait stability, and autonomic response data. A processor establishes a patient-specific rolling baseline during an onboarding calibration period and derives an autonomic-decline weighting factor that dynamically adjusts the contribution of each sensor channel to a composite risk score, compensating for individual variability in hypoglycemia unawareness commonly observed in elderly patients.
Keywords	Hypoglycemia Unawareness, Adaptive Sensor Fusion, Wearable Devices, Geriatric Diabetes, Inter-net of Things (IoT)
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 4, July-August 2026
Published On	2026-08-16

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research