4. Manually editing data

Physiological data are messy and prone to artifact (e.g., movement in respiration and pulse, ectopic beats in ECG). Despite leaps and bounds in recent algorithms for processing these data there still exists a need for manual inspection to ensure such artifacts have been appropriately removed.

To do this reproducibly, however, we want to ensure there is a record of these manual changes. The edit_physio() function was designed for this exact purpose. Invoking it will open up an interactive viewer that allows you to remove peaks from noisy portions of the time series, or delete peaks/troughs that were erroneously detected.

First, let’s process some pulse photoplethysmography data collected at 25 Hz:

>>> from peakdet import load_physio, operations
>>> data = load_physio('PPG.csv', fs=25.0)
>>> data = operations.interpolate_physio(data, target_fs=250.0)
>>> data = operations.filter_physio(data, cutoffs=1.0, method='lowpass')
>>> data = operations.peakfind_physio(data, thresh=0.1, dist=100)
>>> ax = operations.plot_physio(data)
>>> ax.set_xlim(0, 10)  # doctest: +SKIP

The data looks good, but it would be nice to go through it all quickly and ensure that there are no noisy sections or peaks/troughs that need to be removed. We can do that easily with edit_physio():

>>> data = operations.edit_physio(data)

This function will open up an interactive viewer, which supports scrolling through the time series (with the scroll wheel), rejection of noisy segments of data (left click + drag, red highlight), and deleting peaks / troughs that were erroneously detected and shouldn’t be considered at all (right click + drag, blue highlight):

If you accidentally reject or delete peaks, you can undo the selection with ctrl+z (or command+z if you’re on a Mac). The interactive viewer will track your history of edits as long as it is open, so you can undo multiple selections, if desired. Once done, you can close the interactive viewer by pressing ctrl+q (command+q).

All edits performed in the editor are stored in the history of the data object, as with other operations, ensuring a record of your manual changes are retained.