Open source data for smartphone camera oximetry, sensing SpO2 and hypoxemia risk on a clinically relevant spread of data
This repository contains the open source data from the smartphone camera oximetry study by Hoffman et al in 2021 [include link]. It can be used to attempt to compute SpO2 and predict risk of hypoxemia using a smartphone camera via machine learning or analytical methods. The data is the first gathered using a smartphone camera on a clinically relevant spread of SpO2 levels (65%-100%).
The data was gathered by researchers at the University of Washington and the University of California, San Diego, and is provided free and open source for the community to use for future projects.
Clone the repo and run ??.ipynb to get started!
More example code can be found in the examples directory.
- fill out on a fresh run
There were 6 patients in this study (numbered 10001-10006).
The smartphone oximetry data was collected in the form of MP4 videos, downloadable from: http://bit.ly/oxy-raw-z. Each frame's R, G, and B values were averaged to create the csv files in data/ppg-csv.
The ground truth data was collected from a few standard pulse oximeters attached to the subjects' other fingers. That data can be found in data/gt.
- Camera framerate = 30 Hz
- Ground truth pulse oximeters framerate = 1 Hz
- Recording was started and stopped on the camera and the pulse oximeters at the same time
SpO We performed a clinical development validation induced hypoxemia study, in which test subjects were given a controlled mixture of oxygen and nitrogen to lower their SpO2 level over a period of 12-16 minutes. The patients had one finger from each hand on a phones camera, while the camera flash transmitted light through their fingertips for reflectance photoplethysmography. The camera recorded
For more details, see the publication in IMWUT from 2020: [include link].
Go ahead and try different models:
- Analytical (eg. ratio-of-ratios)
- Deep Learning
- Linear Regression
- Or, think of your own!
If you use this data or code in your project, please cite it. Here's the ACM format:
- Add citation later when it's ready.
This data is provided open-source via the MIT license. For more details, see the license file. We want you to use it for whatever creative projects you can come up with!