wfdb-to-csv 0.1.0

Convert WFDB ECG (.hea/.dat) to CSV with UNIX epoch nanosecond timestamps

HEA to CSV Converter

A Python package and CLI to convert WFDB ECG recordings (.HEA/.DAT) to CSV format with timestamped entries using UNIX epoch nanoseconds.

WFDB Format

The WFDB format consists of two files per recording:

• .hea: Header file containing metadata about the recording (number of leads, sampling rate, start time, etc.)
• .dat: Binary file containing the actual ECG signal samples.

For complete details, refer to WFDB Format Documentation.

Features

• Converts all leads with precise timestamp for each sample (UNIX epoch in nanoseconds)
• Handles multiple leads and variable durations
• Progress bar for large datasets
• Metadata printed and saved in JSON format (filename, leads, sampling rate, start time, etc.)
• CLI support for direct command-line use
• Output CSV includes time column as the first column (nanoseconds)

Installation

Install from PyPI:

pip install hea_to_csv

Usage

As a Python Module

from hea_to_csv import wfdb_to_csv

# Basic usage
wfdb_to_csv("recording.hea")  # Save as recording.csv

# With parameters
wfdb_to_csv(
    "recording.hea",
    output_file="example.csv",
    metadata_file="recording.json",
    verbose=True
)

CLI Usage

python -m hea_to_csv <input_file> [-o <output_file>] [-m <metadata_file>] [-q]

CLI Parameters

Argument	Description
input_file	Path to the input HEA file (required)
--output, -o <file_path>	Optional output CSV file path (default: same as input file but with .csv)
--metadata, -m <file_path>	Optional JSON metadata output path (default: same as input file but with .json)
--quiet, -q	Suppress console output (default: False)

Change Log

v0.1.0

• Initial release
• Converts HEA/DAT files to CSV with timestamp
• Saves recording metadata in JSON format

License

MIT License