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physioKIT
Getting started
HELIA

Getting started

physioKIT is a Python library for processing sampled physiological signals. It can generate synthetic examples, clean recordings, find events such as ECG R-peaks, and calculate derived measures. You can follow the first example without a dataset or sensor. When you have your own recording, use its actual sampling rate with each processing function.

Choose a first step

Section titled “Choose a first step”

Install and run a first analysis

Install with uv or pip, generate a synthetic ECG, find R-peaks, and calculate HRV measures.

Use your own data

Load one ECG channel, check its shape and sampling rate, then locate peaks in your recording.

How the workflow fits together

Section titled “How the workflow fits together”
  1. Provide samples. Start with a generated signal or load an array from your own recording. Record the sampling rate in hertz (samples per second).
  2. Prepare the signal. Choose the cleaning routine for the signal type and pass the sampling rate used to collect the data.
  3. Find events and calculate measures. For ECG, R-peaks are returned as sample positions. Their spacing becomes RR intervals; the sampling rate converts those intervals to time-based measures.
  4. Inspect the result. Compare intermediate signals and detected events before using a derived value. The signal guides pair code examples with saved plots, while the API Reference documents function inputs and outputs.

physioKIT requires Python 3.12–3.14. The quickstart uses synthetic ECG data, so it is the shortest way to check your installation before working with a recording.