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You may use the source code of the developed analytical tool *PPGraw* for scientific, non-commercial purposes, provided that you give credit to the owners when publishing any work based on it. We would also be very interested to hear back from you if you use our tool or metrics in any way and are happy to answer any questions or address any remarks related to it.

### Presentation Video
<a href="https://www.youtube.com/watch?v=RshKMVtH7P0" target="_blank"><img src="https://raw.githubusercontent.com/fwolling/PPGraw/main/figures/youtube.png" alt="DATA'20 - The Quest for Raw Signals - A Quality Review of Photoplethysmography Datasets" width="600" style="float: center;" /></a>
<a href="https://www.youtube.com/watch?v=RshKMVtH7P0" target="_blank"><img src="https://raw.githubusercontent.com/fwolling/PPGraw/main/fig/youtube.png" alt="DATA'20 - The Quest for Raw Signals - A Quality Review of Photoplethysmography Datasets" width="600" style="float: center;" /></a>

<br>

### Reference Data
**REF:** MAX86140EVSYS# [<a href="https://ubicomp.eti.uni-siegen.de/home/datasets/data20/index.html.en" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/00_max86140.png" alt="Reference Data: MAX86140EVSYS#" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/00_max86140.png" alt="Reference Data: MAX86140EVSYS#" style="float: left; margin-right: 10px;" />

### Evaluated Datasets

The following figures show excerpts from the reviewed datasets: Short close-up of few pulses on the left, a 30-second window in the middle, and its respective frequency spectrum (FFT) on the right. Note that the PPG-BP dataset (S05) contains only snippets of 2.1 s length. Frequency bands: very low frequency (VLF, < 0.167 Hz, red), low frequency (LF, 0.167 to 0.667 Hz, orange), and intermediate frequency (IF, 0.5 to 3.0 Hz , green) while the high frequency (HF, > 3.0 Hz) noise and harmonics are clipped.

**S01:** MAXREFDES100# [<a href="#ref_s01">Biagetti et al.</a>, <a href="https://www.sciencedirect.com/science/article/pii/S2352340919314003" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/01_maxrefdes100.png" alt="S01: MAXREFDES100#" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/01_maxrefdes100.png" alt="S01: MAXREFDES100#" style="float: left; margin-right: 10px;" />
**S02:** PPG-DaLiA [<a href="#ref_s02">Reiss et al.</a>, <a href="https://ubicomp.eti.uni-siegen.de/home/datasets/sensors19/index.html.en" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/02_dalia.png" alt="S02: PPG-DaLiA" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/02_dalia.png" alt="S02: PPG-DaLiA" style="float: left; margin-right: 10px;" />
**S03:** WESAD [<a href="#ref_s03">Schmidt et al.</a>, <a href="https://ubicomp.eti.uni-siegen.de/home/datasets/icmi18/index.html.en" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/03_wesad.png" alt="S03: WESAD" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/03_wesad.png" alt="S03: WESAD" style="float: left; margin-right: 10px;" />
**S04:** BloodLossSVM [<a href="#ref_s04">Reljin et al.</a>, <a href="https://figshare.com/articles/NR_bloodlosssvm_zip/5594644" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/04_nrblsvm.png" alt="S04: BloodLossSVM" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/04_nrblsvm.png" alt="S04: BloodLossSVM" style="float: left; margin-right: 10px;" />
**S05:** PPG-BP [<a href="#ref_s05">Liang et al.</a>, <a href="https://figshare.com/articles/PPG-BP_Database_zip/5459299" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/05_ppgbp.png" alt="S05: PPG-BP" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/05_ppgbp.png" alt="S05: PPG-BP" style="float: left; margin-right: 10px;" />
**S06:** BIDMC [<a href="#ref_s06">Pimentel et al.</a>, <a href="https://physionet.org/content/bidmc/1.0.0/" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/06_bidmc.png" alt="S06: BIDMC" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/06_bidmc.png" alt="S06: BIDMC" style="float: left; margin-right: 10px;" />
**S07:** Wrist PPG During Exercise [<a href="#ref_s07">Jarchi et al.</a>, <a href="https://physionet.org/content/wrist/1.0.0/" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/07_wpde.png" alt="S07: Wrist PPG During Exercise" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/07_wpde.png" alt="S07: Wrist PPG During Exercise" style="float: left; margin-right: 10px;" />
**S08:** Cuff-Less Blood Pressure Estimation [<a href="#ref_s08">Kachuee et al.</a>, <a href="https://archive.ics.uci.edu/ml/datasets/Cuff-Less+Blood+Pressure+Estimation" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/08_clbpe.png" alt="S08: Cuff-Less Blood Pressure Estimation" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/08_clbpe.png" alt="S08: Cuff-Less Blood Pressure Estimation" style="float: left; margin-right: 10px;" />
**S09:** IEEE SPC 2015 (TROIKA) [<a href="#ref_s09">Zhang et al.</a>, <a href="https://sites.google.com/site/researchbyzhang/ieeespcup2015" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/09_spc2015.png" alt="S09: IEEE SPC 2015 (TROIKA)" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/09_spc2015.png" alt="S09: IEEE SPC 2015 (TROIKA)" style="float: left; margin-right: 10px;" />
**S10:** IEEE SPC 2013 [<a href="#ref_s10">Karlen et al.</a>, <a href="http://www.capnobase.org/index.php?id=857" target="_blank">data</a>]
<img src="https://github.com/fwolling/PPGraw/blob/main/figures/10_spc2013.png" alt="S10: IEEE SPC 2013" style="float: left; margin-right: 10px;" />
<img src="https://github.com/fwolling/PPGraw/blob/main/fig/10_spc2013.png" alt="S10: IEEE SPC 2013" style="float: left; margin-right: 10px;" />

<br>

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# fig
# Figures

### Reference Data
**REF:** MAX86140EVSYS# [<a href="https://ubicomp.eti.uni-siegen.de/home/datasets/data20/index.html.en" target="_blank">data</a>]
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# PPGraw

*PPGraw* is a Python tool developed for the analytical quality review of supposedly raw, unfiltered photoplethysmography signals. This directory contains an excerpt from the raw, unfiltered reference data [ref_sample.p](ref_sample.p), the Python tool itself [PPGraw.py](PPGraw.py), a Jupyter notebook [show_ref.ipynb](show_ref.ipynb) to visualize the reference signal, and a Jupyter notebook [how_review.ipynb](show_review.ipynb) that runs a quality review on the reference data and details the 7 multi-varied decision metrics.
*PPGraw* is a Python tool developed for the analytical quality review of supposedly raw, unfiltered photoplethysmography signals. This directory contains an excerpt from the raw, unfiltered reference data [ref_sample.p](ref_sample.p), the Python tool itself [PPGraw.py](PPGraw.py), a Jupyter notebook [ref_show.ipynb](ref_show.ipynb) to visualize the reference signal, and a Jupyter notebook [ref_review.ipynb](ref_review.ipynb) that runs a quality review on the reference data and details the 7 multi-varied decision metrics.

* **ref_sample.p** is a Python Pickle file containing a 3-minute excerpt of the raw, unfiltered photoplethysmography reference data
* **PPGraw.py** contains the Python class of the analytical tool *PPGraw* for the automated quality review of raw photoplethysmography signals
* **show_ref.ipynb** is a Jupyter notebook that visualizes the provided reference data
* **show_review.ipynb** is a Jupyter notebook that runs the quality review on the reference data and details the 7 multi-varied decision metrics
* **ref_show.ipynb** is a Jupyter notebook that visualizes the provided reference data
* **ref_review.ipynb** is a Jupyter notebook that runs the quality review on the reference data and details the 7 multi-varied decision metrics

### Download
This GitHub repository provides the developed analytical tool *PPGraw*.
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