All ETDs from UAB

Advisory Committee Chair

Mohammad R Haider

Advisory Committee Members

Leon Jololian

Nasim Uddin

Document Type

Thesis

Date of Award

2019

Degree Name by School

Master of Science in Electrical Engineering (MSEE) School of Engineering

Abstract

The patented vascular access is critical for successful hemodialysis. Patients with renal failure undergoing dialysis have increased the risk of acute arteriovenous fistula (AVF) and graft (AVG) thrombosis, placing them with severe morbidity, mortality, and financial burden. In most cases, dialysis vascular access thrombosis leading to non-functional AVG/AVF occurs in a non-health environment and is usually not detected until the patient is seen at the next dialysis appointment. This leads to the loss of opportunities for early identification and timely intervention. Studies have shown that, the results of treatment are poor in patients who have undergone thrombectomy after coagulation, and the results are much better in early rescue patients. There is currently no wearable device to detect dialysis vascular access thrombosis in real-time to speed up the intervention. The device of this thesis aims to identify dialysis into thrombosis in real-time and will help to increase patient awareness and reduce complications associated with dialysis into thrombosis. The proposed wearable device uses a small sensor to monitor the patient's vascular access in real-time and send the data to a local microcontroller for signal processing. Machine learning algorithms classify input data and output it to a secure Internet of Things (IoT) database that patients and healthcare teams can access. This non-invasive device will reduce the financial costs, morbidity and mortality associated with thrombotic-related complications and ultimately improve the delivery of care.

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