CINC2017

class torch_ecg.databases.CINC2017(db_dir: str | bytes | PathLike | None = None, working_dir: str | bytes | PathLike | None = None, verbose: int = 1, **kwargs: Any)[source]

Bases: PhysioNetDataBase

AF Classification from a Short Single Lead ECG Recording – The PhysioNet Computing in Cardiology Challenge 2017

ABOUT

  1. training set contains 8,528 single lead ECG recordings lasting from 9 s to just over 60 s, and the test set contains 3,658 ECG recordings of similar lengths

  2. records are of frequency 300 Hz and have been band pass filtered

  3. data distribution:

    Type

    # recording

    Time length (s)

    Mean

    SD

    Max

    Median

    Min

    Normal

    5154

    31.9

    10.0

    61.0

    30

    9.0

    AF

    771

    31.6

    12.5

    60

    30

    10.0

    Other rhythm

    2557

    34.1

    11.8

    60.9

    30

    9.1

    Noisy

    46

    27.1

    9.0

    60

    30

    10.2

    Total

    8528

    32.5

    10.9

    61.0

    30

    9.0

  4. Webpage of the database on PhysioNet [1].

Usage

  1. Atrial fibrillation (AF) detection

References

Citation

10.22489/CinC.2017.065-469

Parameters:

  • db_dir (path-like, optional) – Storage path of the database. If not specified, data will be fetched from Physionet.

  • working_dir (path-like, optional) – Working directory, to store intermediate files and log files.

  • verbose (int, default 1) – Level of logging verbosity.

  • kwargs (dict, optional) – Auxilliary key word arguments.

property database_info: DataBaseInfo

The DataBaseInfo object of the database.

load_ann(rec: str | int, original: bool = False, ann_format: str = 'a') → str[source]

Load the annotation of the record.

Parameters:

  • rec (str or int) – Record name or index of the record in all_records.

  • original (bool, default False) – If True, load annotations from the annotation file REFERENCE-original.csv, otherwise from REFERENCE.csv.

  • ann_format ({"a", "f"}, optional) –

    Format of returned annotation, by default “a”.

    • ”a” - abbreviation

    • ”f” - full name

Returns:

ann – Annotation (label) of the record.

Return type:

str

plot(rec: str | int, data: ndarray | None = None, ann: str | None = None, ticks_granularity: int = 0, rpeak_inds: Sequence[int] | ndarray | None = None) → None[source]

Plot the ECG signal of the record.

Parameters:

  • rec (str or int) – Record name or index of the record in all_records.

  • data (numpy.ndarray, optional) – The ECG signal to plot. If not None, data of rec will not be used. This is useful when plotting filtered data.

  • ann (dict, optional,) – Annotations for data, which is a dict with keys “SPB_indices”, “PVC_indices”, and with ndarray values. Ignored if data is None.

  • ticks_granularity (int, default 0) – Granularity to plot axis ticks, the higher the more ticks. 0 (no ticks) –> 1 (major ticks) –> 2 (major + minor ticks)

  • rpeak_inds (array_like, optional) – Array of indices of R peaks.

Return type:

None