Compressed Sensing Framework for Multi-channel ECG Signals
No Thumbnail Available
Date
2017
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Electrocardiogram (ECG) signals are the manifestation of underlying electrical phenomena of heart, which are responsible for its various functionalities. ECG is used as an important non-invasive tool by the cardiologists to diagnose and assess a wide range of cardiac ailments. With advancements in wireless body area network (WBAN) technologies, significant research has been done in recent decades to develop low-cost personalized remote health monitoring systems for next-generation of e-healthcare solutions. With ever increasing number of cardiovascular patients, WBAN-enabled ECG telemonitoring has generated significant interest among the biomedical community. Ambulatory ECG enables remote monitoring of vital heart parameters and allows early medical interventions in case of life-threatening heart diseases. However, existing ECG monitoring systems still suffer from various challenges, such as limited autonomy, bulkiness, limited functionalities, etc. In recent years, compressed sensing (CS) has emerged as a promising framework to address these challenges. Low-complex and highly energy-efficient data reduction procedure of CS makes it an attractive choice over traditional wavelet-based techniques for embedded on-node ECG data compression in resource-constrained telemonitoring applications.
Description
Supervisor: Samarendra Dandapat
Keywords
ELECTRONICS AND ELECTRICAL ENGINEERING