Name
Title | ||
|---|---|---|
Automated detection of atrial fibrillation in ECG signals based on wavelet packet transform and correlation function of random process |
Abstract | ||
|---|---|---|
•The detection of some key parameters is not need.•The scheme has more solid and reliable medical basis. It can be considered as an essential reference for physicians to accurately and quickly diagnose AF.•It is a first attempt to combine machine learning technology with the correlation function in random process theory for AF detection.•The method does not need the complicated hyper-parameter tuning and high hardware facilities such as GPU. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.bspc.2019.101662 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
92R20,97M60 | Signal processing,Histogram,Receiver operating characteristic,Pattern recognition,Feature extraction,Robustness (computer science),Artificial intelligence,Artificial neural network,Wavelet packet decomposition,Mathematics,Wavelet | Journal |
Volume | ISSN | Citations |
55 | 1746-8094 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jibin Wang | 1 | 3 | 1.72 |
| Ping Wang | 2 | 10 | 12.69 |
| Suping Wang | 3 | 0 | 0.68 |