ecg_features-matlab
所属分类：matlab编程
开发工具：matlab
文件大小：439KB
下载次数：29
上传日期：2018-12-06 12:52:34
上 传 者：
diligent
说明： 用于提取心电信号的特征，包含时域，频域，RR interval相关特征
(used for ECG signal feature extraction, including time domain, frequency domain and RR interval related features)
文件列表:
.idea (0, 2018-07-13)
.idea\dictionaries (0, 2018-07-13)
.idea\dictionaries\rosie.xml (546, 2018-07-13)
LICENSE.txt (1083, 2018-07-13)
data (0, 2018-07-13)
data\features (0, 2018-07-13)
data\features\features.csv (10522, 2018-07-13)
data\labels (0, 2018-07-13)
data\labels\labels.csv (89, 2018-07-13)
data\waveforms (0, 2018-07-13)
data\waveforms\A00021.mat (18024, 2018-07-13)
data\waveforms\A00022.mat (18024, 2018-07-13)
data\waveforms\A00023.mat (18024, 2018-07-13)
data\waveforms\A00024.mat (18024, 2018-07-13)
data\waveforms\A00025.mat (18024, 2018-07-13)
data\waveforms\A00026.mat (18024, 2018-07-13)
data\waveforms\A00027.mat (18024, 2018-07-13)
data\waveforms\A00028.mat (36024, 2018-07-13)
data\waveforms\A00029.mat (18024, 2018-07-13)
data\waveforms\A00030.mat (36024, 2018-07-13)
features (0, 2018-07-13)
features\__init__.py (0, 2018-07-13)
features\feature_extractor.py (9485, 2018-07-13)
features\full_waveform_features.py (9659, 2018-07-13)
features\rri_features.py (34492, 2018-07-13)
figures (0, 2018-07-13)
figures\waveform_examples.png (306584, 2018-07-13)
notebooks (0, 2018-07-13)
notebooks\example.ipynb (24474, 2018-07-13)
requirements.txt (98, 2018-07-13)
utils (0, 2018-07-13)
utils\__init__.py (0, 2018-07-13)
utils\plotting (0, 2018-07-13)
utils\plotting\__init__.py (0, 2018-07-13)
utils\plotting\waveforms.py (1566, 2018-07-13)
utils\tools (0, 2018-07-13)
utils\tools\__init__.py (0, 2018-07-13)
... ...
# ECG Features
A library for extracting a wide range of features from single-lead ECG waveforms. These feature are grouped into three
main categories: (1) Template Features, (2) RR Interval Features, and (3) Full Waveform Features. This repository
contains the feature extraction code we used for our submission to the
[2017 Physionet Challenge](https://www.physionet.org/challenge/2017/).
## Dataset
In the [2017 Physionet Challenge](https://www.physionet.org/challenge/2017/), competitors were asked to build a model to
classify a single lead ECG waveform as either Normal Sinus Rhythm, Atrial Fibrillation, Other Rhythm, or Noisy. The
dataset consisted of 12,186 ECG waveforms that were donated by AliveCor. Data were acquired by patients using one of
three generations of [AliveCor](https://www.alivecor.com/)'s single-channel ECG device. Waveforms were recorded for an
average of 30 seconds with the shortest waveform being 9 seconds, and the longest waveform being 61 seconds. The figure
below presents examples of each rhythm class and the [AliveCor](https://www.alivecor.com/) acquisition device.
Download Training Dataset: [training2017.zip](https://www.physionet.org/challenge/2017/training2017.zip)
*Left: AliveCor hand held ECG acquisition device. Right: Examples of ECG recording for each rhythm class,
Goodfellow et al. (2018).*
## Publications
1. Goodfellow, S. D., A. Goodwin, R. Greer, P. C. Laussen, M. Mazwi, and D. Eytan (2018), Atrial fibrillation
classification using step-by-step machine learning, Biomed. Phys. Eng. Express, 4, 045005.
[DOI: 10.1088/2057-1976/aabef4](http://iopscience.iop.org/article/10.1088/2057-1976/aabef4)
2. Goodfellow, S. D., A. Goodwin, R. Greer, P. C. Laussen, M. Mazwi, and D. Eytan, Classification of atrial fibrillation
using multidisciplinary features and gradient boosting, Computing in Cardiology, Sept 24“27, 2017, Rennes, France.
[DOI](http://www.cinc.org/archives/2017/pdf/361-352.pdf)
## Research Affiliations
1. The Hospital for Sick Children
Department of Critical Care Medicine
Toronto, Ontario, Canada
2. Laussen Labs
www.laussenlabs.ca
Toronto, Ontario, Canada
## License
[MIT](LICENSE.txt)
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