Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jaeseok | - |
dc.contributor.author | Kim, Kyungsoo | - |
dc.contributor.author | Choi, Ji-Woong | - |
dc.date.available | 2017-06-29T08:07:35Z | - |
dc.date.created | 2017-04-10 | - |
dc.date.issued | 2017-01 | - |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/2058 | - |
dc.description.abstract | Due to the necessity of the low-power implementation of newly-developed electrocardiogram (ECG) sensors, exact ECG data reconstruction from the compressed measurements has received much attention in recent years. Our interest lies in improving the compression ratio (CR), as well as the ECG reconstruction performance of the sparse signal recovery. To this end, we propose a sparse signal reconstruction method by pruning-based tree search, which attempts to choose the globally-optimal solution by minimizing the cost function. In order to achieve low complexity for the real-time implementation, we employ a novel pruning strategy to avoid exhaustive tree search. Through the restricted isometry property (RIP)-based analysis, we show that the exact recovery condition of our approach is more relaxed than any of the existing methods. Through the simulations, we demonstrate that the proposed approach outperforms the existing sparse recovery methods for ECG reconstruction. © 2017 by the authors; licensee MDPI, Basel, Switzerland. | - |
dc.language | English | - |
dc.publisher | MDPI AG | - |
dc.title | Pruning-Based Sparse Recovery for Electrocardiogram Reconstruction from Compressed Measurements | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/s17010105 | - |
dc.identifier.wosid | 000393021000105 | - |
dc.identifier.scopusid | 2-s2.0-85012065304 | - |
dc.identifier.bibliographicCitation | Sensors, v.17, no.1 | - |
dc.description.isOpenAccess | TRUE | - |
dc.subject.keywordAuthor | biomedical signal processing | - |
dc.subject.keywordAuthor | electrocardiogram | - |
dc.subject.keywordAuthor | compressed sensing | - |
dc.subject.keywordAuthor | sparse signal recovery | - |
dc.subject.keywordAuthor | tree pruning | - |
dc.subject.keywordPlus | Algorithm | - |
dc.subject.keywordPlus | BEST-1ST SEARCH | - |
dc.subject.keywordPlus | Biomedical Signal Processing | - |
dc.subject.keywordPlus | Compressed Sensing | - |
dc.subject.keywordPlus | Cost Functions | - |
dc.subject.keywordPlus | ECG | - |
dc.subject.keywordPlus | Electrocardiogram | - |
dc.subject.keywordPlus | Electrocardiogram (ECG) Sensors | - |
dc.subject.keywordPlus | Electrocardiography | - |
dc.subject.keywordPlus | Low Power Implementation | - |
dc.subject.keywordPlus | Matrix Algebra | - |
dc.subject.keywordPlus | Optimal Solutions | - |
dc.subject.keywordPlus | ORTHOGONAL MATCHING PURSUIT | - |
dc.subject.keywordPlus | Real-Time Implementations | - |
dc.subject.keywordPlus | Real Time Control | - |
dc.subject.keywordPlus | RECOVERY | - |
dc.subject.keywordPlus | Restricted Isometry Properties (RIP) | - |
dc.subject.keywordPlus | RESTRICTED ISOMETRY PROPERTY | - |
dc.subject.keywordPlus | Signal Processing | - |
dc.subject.keywordPlus | Signal Reconstruction | - |
dc.subject.keywordPlus | SIGNAL RECOVERY | - |
dc.subject.keywordPlus | Sparse Signal Reconstruction | - |
dc.subject.keywordPlus | Sparse Signal Recoveries | - |
dc.subject.keywordPlus | Sparse Signal Recovery | - |
dc.subject.keywordPlus | Tree Pruning | - |
dc.citation.number | 1 | - |
dc.citation.title | Sensors | - |
dc.citation.volume | 17 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Chemistry; Engineering; Instruments & Instrumentation | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical; Engineering, Electrical & Electronic; Instruments & Instrumentation | - |
dc.type.docType | Article | - |