Modified version of the Physionet database "MIT Normal Sinus Rhythm" as Machine Learning dataset

<p>ECGs from the MIT-NSR database with some modifications to make them more suitable as playground data set for machine learning.</p> <ul> <li>all 18 ECGs are trimmed to approx. 50000 heart beats from a region without recording errors</li> <li>scaled to a range -1 to 1 (non-linear/tanh)</li> <li>heart beats annotation as time series with value 1.0 at the point of the annotated beat and 0.0 for all other times</li> <li>additional heart beat column smoothed by applying a gaussian filter</li> <li>provided as csv with columns &quot;time in sec&quot;, &quot;channel 1&quot;, &quot;channel 2&quot;, &quot;beat&quot; and&nbsp; &quot;smooth&quot;</li> <li>an example that uses the dataset to implement heart-beat detection can be found here: <a href="https://github.com/KnetML/NNHelferlein.jl/blob/main/examples/62-ECG-tagger.ipynb">Heart beat detection with Peephole LSTM</a>.</li> </ul> <p><strong>Original data set description:</strong></p> <p>MIT-BIH Normal Sinus Rhythm Database</p> <p>George Moody, Published: Aug. 3, 1999. Version: 1.0.0</p> <p>This database includes 18 long-term ECG recordings of subjects referred to the Arrhythmia Laboratory at Boston&#39;s Beth Israel Hospital (now the Beth Israel Deaconess Medical Center). Subjects included in this database were found to have had no significant arrhythmias; they include 5 men, aged 26 to 45, and 13 women, aged 20 to 50.</p> <p>DOI: <a href="https://doi.org/10.13026/C2NK5R">https://doi.org/10.13026/C2NK5R</a></p> <p>Link: <a href="https://www.physionet.org/content/nsrdb/1.0.0/">https://www.physionet.org/content/nsrdb/1.0.0/</a></p> <p>Ref: Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... &amp; Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215&ndash;e220.</p> <p>&nbsp;</p>