Compressed Sensing Framework for Multi-channel ECG Signals
dc.contributor.author | Singh, Anurag | |
dc.date.accessioned | 2017-08-10T10:38:17Z | |
dc.date.accessioned | 2023-10-20T07:28:37Z | |
dc.date.available | 2017-08-10T10:38:17Z | |
dc.date.available | 2023-10-20T07:28:37Z | |
dc.date.issued | 2017 | |
dc.description | Supervisor: Samarendra Dandapat | en_US |
dc.description.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. | en_US |
dc.identifier.other | ROLL NO.11610230 | |
dc.identifier.uri | https://gyan.iitg.ac.in/handle/123456789/826 | |
dc.language.iso | en | en_US |
dc.relation.ispartofseries | TH-1578; | |
dc.subject | ELECTRONICS AND ELECTRICAL ENGINEERING | en_US |
dc.title | Compressed Sensing Framework for Multi-channel ECG Signals | en_US |
dc.type | Thesis | en_US |
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