Changelog

Removed due to build error in Windows executable (also yanked from PyPI).

enhancement: updated documentation and docstrings.
enhancement: more convenient PPG benchmarking.
bugfix: resp.ensure_peak_trough_alternation() now considers neighboring extrema with equal amplitude.

enhancement: added support for plain text files (.txt, .csv, .tsv).
enhancement: stream Glasgow University Database (GUDB) for ECG benchmarking (download is no longer required).

enhancement: visibility of configuration panel can now be toggled (more screen space for signals).
bugfix: fixed index-out-of-range error in heart._correct_misaligned().

bugfix: corrected control-flow of artifact classification during auto-correction of ECG and PPG peaks.
bugfix: using PySide2 resources instead of PyQt5 resources

enhancement: using the official Qt Python bindings (PySide2) instead of PyQt5.
bugfix: enforcing minimal figure height to comply with requirements of Matplotlib > 3.2.0.

enhancement: faster auto-correction of ECG and PPG peaks with pandas rolling window.
bugfix: corrected error in calculation of subspace 22 during auto-correction of ECG and PPG peaks.
bugfix: during segmentation, extrema at segment boundaries are now excluded from segment.

enhancement: auto-correction of ECG and PPG peaks is now optional (instead of being applied by default during the calculation of the statistics).
enhancement: improved baseline removal for respiration signals.

enhancement: added peak detection for photoplethysmogram (PPG) (heart.ppg_peaks()), based on Elgendi et al., (2013). The performance of heart.ppg_peaks() has been evaluated on the PPG signals of all 42 subjects in the Capnobase IEEE TBME benchmark dataset. The dataset has not been used to optimize heart.ppg_peaks() in any way prior to the performance evaluation. The tolerance for peak detection was set to 50 milliseconds in accordance with Elgendi et al., (2013).

bugfix: the PATCH version has been reset to 0 after incrementing MINOR version (https://semver.org/)

enhancement: some small improvements of the statistics panel in datadisplay.

enhancement: added support for EDF files.
enhancement: ecg.ecg_peaks() now filters out power-line noise at 50Hz. This further increases the performance on the Glasgow University Database (GUDB). Again, the GUBD has not been used to optimize ecg.ecg_peaks() in any way prior to the performance evaluation. The tolerance for peak detection was set to one sample.

condition	metric	summary	version 1.0.2	version 1.0.3	version 1.1.5
sitting	precision	mean	.999	.998	.998
		std	.002	.005	.002
	sensitivity	mean	.996	.996	.998
		std	.008	.004	.004
handbike	precision	mean	.904	.930	.984
		std	.135	.127	.022
	sensitivity	mean	.789	.857	.984
		std	.281	.247	.025

enhancement: improved sensitivity of ecg.ecg_peaks() without decreasing precision in moderately dynamic conditions (handbike) while maintaining high performance in resting conditions (sitting). Performance has been evaluated on lead 2 of all 25 subjects in the Glasgow University Database (GUDB). The GUBD has not been used to optimize ecg.ecg_peaks() in any way prior to the performance evaluation. The tolerance for peak detection was set to one sample.

condition	metric	summary	version 1.0.2	version 1.0.3
sitting	precision	mean	.999	.998
		std	.002	.005
	sensitivity	mean	.996	.996
		std	.008	.004
handbike	precision	mean	.904	.930
		std	.135	.127
	sensitivity	mean	.789	.857
		std	.281	.247

enhancement: resp.resp_extrema() is now based on zerocrossings and makes fewer assumptions about breathing rate.

bugfix: controller.save_signal() now preserves the header if the data are saved to the same location (i.e., if model.rpathsignal and model.wpathsignal are identical).

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