| scholarly article | Q13442814 |
| P356 | DOI | 10.1155/2017/4901017 |
| P8608 | Fatcat ID | release_47bp4fhkkzchrffqirgsbuif2y |
| P932 | PMC publication ID | 5516746 |
| P698 | PubMed publication ID | 29065613 |
| P50 | author | Sang-Woong Lee | Q89723582 |
| Jeong-Seon Park | Q96071552 | ||
| Unsang Park | Q96071554 | ||
| P2093 | author name string | Jeong-Seon Park | |
| Sang-Woong Lee | |||
| Unsang Park | |||
| P2860 | cites work | R-peaks detection based on stationary wavelet transform. | Q50893758 |
| QRS detection using S-Transform and Shannon energy. | Q51083803 | ||
| The impact of the MIT-BIH arrhythmia database | Q74169034 | ||
| Removal of base-line wander and power-line interference from the ECG by an efficient FIR filter with a reduced number of taps | Q93660058 | ||
| Characteristic wave detection in ECG signal using morphological transform | Q24815861 | ||
| ECG R-R peak detection on mobile phones. | Q30365818 | ||
| Shannon's Energy Based Algorithm in ECG Signal Processing | Q37618252 | ||
| A real-time QRS detection algorithm | Q39316325 | ||
| Envelopment filter and K-means for the detection of QRS waveforms in electrocardiogram. | Q41001795 | ||
| QRS detection based on wavelet coefficients. | Q46669458 | ||
| QRS complexes detection for ECG signal: the Difference Operation Method | Q47641086 | ||
| P275 | copyright license | Creative Commons Attribution 4.0 International | Q20007257 |
| P6216 | copyright status | copyrighted | Q50423863 |
| P304 | page(s) | 4901017 | |
| P577 | publication date | 2017-07-05 | |
| P1433 | published in | Hindawi Journal of Engineering | Q15816371 |
| P1476 | title | R Peak Detection Method Using Wavelet Transform and Modified Shannon Energy Envelope | |
| P478 | volume | 2017 |
| Q90190711 | A Survey of Heart Anomaly Detection Using Ambulatory Electrocardiogram (ECG) |
| Q57493134 | An Efficient Teager Energy Operator-Based Automated QRS Complex Detection |
| Q58610954 | Deep Deterministic Learning for Pattern Recognition of Different Cardiac Diseases through the Internet of Medical Things |
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