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

ECGs from the MIT-NSR database with some modifications to make them more suitable as playground data set for machine learning.

all 18 ECGs are trimmed to approx. 50000 heart beats from a region without recording errors

scaled to a range -1 to 1 (non-linear/tanh)

heart beats annotation as time series with value 1.0 at the point of the annotated beat and 0.0 for all other times

additional heart beat column smoothed by applying a gaussian filter

provided as csv with columns "time in sec", "channel 1", "channel 2", "beat" and  "smooth"

an example that uses the dataset to implement heart-beat detection can be found here: Heart beat detection with Peephole LSTM.

Original data set description:

MIT-BIH Normal Sinus Rhythm Database

George Moody, Published: Aug. 3, 1999. Version: 1.0.0

This database includes 18 long-term ECG recordings of subjects referred to the Arrhythmia Laboratory at Boston'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.

DOI: https://doi.org/10.13026/C2NK5R

Link: https://www.physionet.org/content/nsrdb/1.0.0/

Ref: Goldberger, A., Amaral, L., Glass, L., Hausdorff, J., Ivanov, P. C., Mark, R., ... & Stanley, H. E. (2000). PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation [Online]. 101 (23), pp. e215–e220.