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Data quality check for physiological recording

This report was generated using Systole v.{{systole_version}}. If you use this package for research, please cite as:
Legrand, N., & Allen, M. (2022). Systole: A python package for cardiac signal synchrony and analysis. In Journal of Open Source Software (Vol. 7, Issue 69, p. 3832). The Open Journal. https://doi.org/10.21105/joss.03832

Electrocardiography (ECG)

{% if show_ecg %}

Instantaneous heart rate

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Artefact detection

Artefact detection is performed using the method described in Lipponen & Tarvainen (2019). This method uses robust adaptative thresholds to classify RR intervals as Missed, Longs, Extra, Short or Ectopic. The left panel show the decision boundaries for ectopic beats. The right panel shows the decision boundaries for long/missed and short/extra beats.
Lipponen, J. A., & Tarvainen, M. P. (2019). A robust algorithm for heart rate variability time series artefact correction using novel beat classification. Journal of Medical Engineering & Technology, 43(3), 173–181. https://doi.org/10.1080/03091902.2019.1640306
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Heart Rate Variability

Time domain

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Frequency domain

The power spectral density was computed from the interpolated instantaneous RR intervals (milliseconds) using the Welch method with 50% ovelap and a segment length of 256 seconds.
The figures highlights the three frequency bands of interest for heart rate variability: the very low frequency (from 0 to 0.04 Hz), the low frequency (from 0.04 to 0.15 Hz) and the high frequency (from 0.15 to 0.4 Hz).
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Non linear domain

{{ div["ecg_plot_poincare"] }}
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{% endif %} {% if show_ppg %}

Photoplethysmography (PPG)

Instantaneous heart rate

{{ div["ppg_rr"] }}

Artefact detection

Artefact detection is performed using the method described in Lipponen & Tarvainen (2019). This method uses robust adaptative thresholds to classify RR intervals as Missed, Longs, Extra, Short or Ectopic. The left panel show the decision boundaries for ectopic beats. The right panel shows the decision boundaries for long/missed and short/extra beats.
Lipponen, J. A., & Tarvainen, M. P. (2019). A robust algorithm for heart rate variability time series artefact correction using novel beat classification. Journal of Medical Engineering & Technology, 43(3), 173–181. https://doi.org/10.1080/03091902.2019.1640306
{{ div["ppg_artefacts"] }}

Heart Rate Variability

Time domain

{% else %}
No PPG signal was found in the recording.
{% endif %}

Respiration

{% if show_respiration %}

Raw signal

{{ div["rsp_raw"] }}
{% else %}
No respiration signal was found in the recording.
{% endif %}