Version 1 - September 2017
When referencing this material, please cite:
@article{OSV, author = {Amar S. Bhogal and Ali R. Mani}, title = {Pattern Analysis of Oxygen Saturation Variability in Healthy Individuals: Entropy of Pulse Oximetry Signals Carries Information about Mean Oxygen Saturation}, journal = {Frontiers in Physiology}, volume = {8}, issue = {1}, pages = {555}, year = {2017} }
Please also include the standard citation for PhysioNet:
@article{PhysioNet, author = {Goldberger, Ary L. and Amaral, Luis A. N. and Glass, Leon and Hausdorff, Jeffrey M. and Ivanov, Plamen Ch. and Mark, Roger G. and Mietus, Joseph E. and Moody, George B. and Peng, Chung-Kang and Stanley, H. Eugene}, title = {{PhysioBank}, {PhysioToolkit}, and {PhysioNet}: Components of a New Research Resource for Complex Physiologic Signals}, journal = {Circulation}, publisher = {American Heart Association, Inc.}, volume = {101}, number = {23}, year = {2000}, month = {June}, pages = {e215--e220}, doi = {10.1161/01.CIR.101.23.e215}, issn = {0009-7322}, url = {http://circ.ahajournals.org/content/101/23/e215} }
This database contains one hour oxygen saturation measurements of 36 patients, used for the analysis of oxygen saturation variability.
Background
Pulse oximetry is routinely used for monitoring patients' oxygen saturation levels with little regard to the variability of this physiological variable. There are few published studies on oxygen saturation variability (OSV), with none describing the variability and its pattern in a healthy adult population. The aim of this study was to characterise the pattern of OSV using several parameters: the regularity (sample entropy analysis), the self-similarity (detrended fluctuation analysis (DFA)), and the complexity (multiscale entropy (MSE) analysis). Secondly, to determine if there were any changes that occur with age.
The study population consisted of 36 individuals. The 'young' population consisted of 20 individuals [Mean age = 21.0 (SD = 1.36 years)] and the 'old' population consisted of 16 individuals [Mean age = 50.0 (SD = 10.4 years)]. Through DFA analysis, OSV was shown to exhibit fractal-like patterns. The sample entropy revealed the variability to be more regular than heart rate variability and respiratory rate variability. There was a significant inverse correlation between mean oxygen saturation and sample entropy in healthy individuals. Additionally, the MSE analysis described a complex fluctuation pattern, which was reduced with age (p < 0.05). These findings suggest partial "uncoupling" of the cardio-respiratory control system that occurs with ageing. Overall, this study has characterized OSV using pre-existing tools. We have showed that entropy analysis of pulse oximetry signals carries information about body oxygenation. This may have the potential to be used in clinical practice to detect differences in diseased patient subsets.
Data Collection
Before starting the recording, the participants are interviewed to obtain:
- Age
- BMI (use their weight and height on the NHS BMI calculator tool)
- Gender
- Smoking history and/or current smoking status
- Any significant medical conditions that could affect reading
Measurement Setup:
- In the LabChart software, switch off all input sources except input 1,2, and 3.
- Set the sampling frequency to 1KHz.
- Plug Pulse Oximeter into Power Lab input 1.
- Plug the Pulse pressure transducer into Power Lab input 2.
- Attach Respiratory band into Power Lab input 3.
- Connect personal computer to the PowerLab data acquisition system.
Procedure for recording:
- Clean the pulse oximeter and place on finger of participants choosing
- Place the pulse pressure transducer on the adjacent finger
- Wrap the Respiratory band around the umbilicus of the participant
- Preferably have participant sitting with the fingers relatively still
- Test equipment to ensure correct readings
- Once the equipment has been checked stop the test and start the official recording
- Add a comment to show when the data collection has started and once again when it has ended
- After the hour has passed stop the recording, then remove and clean the equipment
- Save the file ensuring complete anonymity by using the date of collection (i.e if 1st participant on January 1st 2017, then save file as 010117A)
Extracting Oxygen Saturation Data for Analysis:
- Select the 1 hour recorded segment
- File > Export As – select LabChart Text FIle
- Choose channel 1 and select the option for current selection
- Down sample by 1000 and remove comments
- Save file in a separate file with the other samples
Data Files
The oxygen saturation data files are provided in standard WFDB format. The sampling frequency of the measurements is 1Hz as specified in the header files.
The participants.csv
file contains metadata about each participant.
Contributors
This data was contributed by Amar S. Bhogal and Ali R. Mani from the UCL Division of Medicine, University College London.
Name Last modified Size Description
Parent Directory - DOI 2018-08-29 16:19 19 090217A.hea 2017-09-27 12:07 135 header file 250117A.hea 2017-09-27 12:07 135 header file 150317A.hea 2017-09-27 12:07 138 header file 301116B.hea 2017-09-27 12:07 138 header file 010217A.hea 2017-09-27 12:07 139 header file 010217C.hea 2017-09-27 12:07 139 header file 101216A.hea 2017-09-27 12:07 139 header file 121216A.hea 2017-09-27 12:07 139 header file 150317B.hea 2017-09-27 12:07 139 header file 210217B.hea 2017-09-27 12:07 139 header file 301116A.hea 2017-09-27 12:07 139 header file 010317A.hea 2017-09-27 12:07 141 header file 210217A.hea 2017-09-27 12:07 141 header file 230117A.hea 2017-09-27 12:07 141 header file 081216A.hea 2017-09-27 12:07 143 header file 090217B.hea 2017-09-27 12:07 143 header file 101216B.hea 2017-09-27 12:07 143 header file 250117C.hea 2017-09-27 12:07 143 header file 101216C.hea 2017-09-27 12:07 144 header file 121216B.hea 2017-09-27 12:07 144 header file 160217A.hea 2017-09-27 12:07 144 header file 160217B.hea 2017-09-27 12:07 144 header file 160217C.hea 2017-09-27 12:07 144 header file 160217D.hea 2017-09-27 12:07 144 header file 230117B.hea 2017-09-27 12:07 144 header file 250117B.hea 2017-09-27 12:07 144 header file 010217B.hea 2017-09-27 12:07 145 header file 010317B.hea 2017-09-27 12:07 145 header file 070217A.hea 2017-09-27 12:07 145 header file 080217A.hea 2017-09-27 12:07 145 header file 080217B.hea 2017-09-27 12:07 145 header file 140317A.hea 2017-09-27 12:07 145 header file 160217E.hea 2017-09-27 12:07 145 header file 210217C.hea 2017-09-27 12:07 145 header file 300117A.hea 2017-09-27 12:07 145 header file 051216A.hea 2017-09-27 12:07 146 header file RECORDS 2017-09-27 12:07 288 list of record names matlab-script.m 2017-09-27 12:07 738 participants.csv 2017-09-27 12:07 1.2K MD5SUMS 2018-08-30 16:37 5.1K SHA1SUMS 2018-08-30 16:37 6.0K 010217A.dat 2017-09-27 12:07 7.0K digitized signal(s) 010317A.dat 2017-09-27 12:07 7.0K digitized signal(s) 160217A.dat 2017-09-27 12:07 7.0K digitized signal(s) 070217A.dat 2017-09-27 12:07 7.0K digitized signal(s) 250117B.dat 2017-09-27 12:07 7.0K digitized signal(s) 140317A.dat 2017-09-27 12:07 7.0K digitized signal(s) 150317B.dat 2017-09-27 12:07 7.0K digitized signal(s) 090217A.dat 2017-09-27 12:07 7.0K digitized signal(s) 121216A.dat 2017-09-27 12:07 7.0K digitized signal(s) 150317A.dat 2017-09-27 12:07 7.0K digitized signal(s) 160217D.dat 2017-09-27 12:07 7.0K digitized signal(s) 210217B.dat 2017-09-27 12:07 7.0K digitized signal(s) 210217C.dat 2017-09-27 12:07 7.0K digitized signal(s) 230117B.dat 2017-09-27 12:07 7.0K digitized signal(s) 300117A.dat 2017-09-27 12:07 7.0K digitized signal(s) 010217C.dat 2017-09-27 12:07 7.0K digitized signal(s) 081216A.dat 2017-09-27 12:07 7.0K digitized signal(s) 080217B.dat 2017-09-27 12:07 7.0K digitized signal(s) 301116B.dat 2017-09-27 12:07 7.0K digitized signal(s) 210217A.dat 2017-09-27 12:07 7.0K digitized signal(s) 010317B.dat 2017-09-27 12:07 7.1K digitized signal(s) 080217A.dat 2017-09-27 12:07 7.1K digitized signal(s) 090217B.dat 2017-09-27 12:07 7.1K digitized signal(s) 101216C.dat 2017-09-27 12:07 7.1K digitized signal(s) 121216B.dat 2017-09-27 12:07 7.1K digitized signal(s) 160217C.dat 2017-09-27 12:07 7.1K digitized signal(s) 160217E.dat 2017-09-27 12:07 7.1K digitized signal(s) 230117A.dat 2017-09-27 12:07 7.1K digitized signal(s) 250117A.dat 2017-09-27 12:07 7.1K digitized signal(s) 250117C.dat 2017-09-27 12:07 7.1K digitized signal(s) 051216A.dat 2017-09-27 12:07 7.1K digitized signal(s) 160217B.dat 2017-09-27 12:07 7.1K digitized signal(s) 101216A.dat 2017-09-27 12:07 7.1K digitized signal(s) 101216B.dat 2017-09-27 12:07 7.1K digitized signal(s) 301116A.dat 2017-09-27 12:07 7.1K digitized signal(s) 010217B.dat 2017-09-27 12:07 7.1K digitized signal(s) SHA256SUMS 2018-08-30 16:37 8.6K 010217C.txt 2018-07-17 13:29 17K 081216A.txt 2018-07-17 13:29 17K 010217A.txt 2018-07-17 13:29 17K 300117A.txt 2018-07-17 13:29 17K 150317A.txt 2018-07-17 13:29 18K 160217D.txt 2018-07-17 13:29 18K 250117B.txt 2018-07-17 13:29 18K 121216A.txt 2018-07-17 13:29 18K 051216A.txt 2018-07-17 13:29 18K 250117C.txt 2018-07-17 13:29 18K 090217B.txt 2018-07-17 13:29 18K 301116A.txt 2018-07-17 13:29 18K 101216A.txt 2018-07-17 13:29 18K 101216C.txt 2018-07-17 13:29 18K 230117A.txt 2018-07-17 13:29 18K 121216B.txt 2018-07-17 13:29 18K 250117A.txt 2018-07-17 13:29 18K 230117B.txt 2018-07-17 13:29 18K 101216B.txt 2018-07-17 13:29 18K 010217B.txt 2018-07-17 13:29 18K 010317A.txt 2018-07-17 13:29 21K 160217A.txt 2018-07-17 13:29 21K 070217A.txt 2018-07-17 13:29 21K 140317A.txt 2018-07-17 13:29 21K 150317B.txt 2018-07-17 13:29 21K 090217A.txt 2018-07-17 13:29 21K 210217B.txt 2018-07-17 13:29 21K 210217C.txt 2018-07-17 13:29 21K 080217B.txt 2018-07-17 13:29 21K 210217A.txt 2018-07-17 13:29 21K 010317B.txt 2018-07-17 13:29 21K 160217C.txt 2018-07-17 13:29 21K 160217E.txt 2018-07-17 13:29 21K 160217B.txt 2018-07-17 13:29 21K 301116B.txt 2018-07-17 13:29 25K 080217A.txt 2018-07-17 13:29 28K
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