| Title |
Blood pulsation measurement using cameras operating in visible light: limitations
|
|---|---|
| Published in |
BioMedical Engineering OnLine, October 2016
|
| DOI | 10.1186/s12938-016-0232-8 |
| Pubmed ID | |
| Authors |
Robert Koprowski |
| Abstract |
The paper presents an automatic method for analysis and processing of images from a camera operating in visible light. This analysis applies to images containing the human facial area (body) and enables to measure the blood pulse rate. Special attention was paid to the limitations of this measurement method taking into account the possibility of using consumer cameras in real conditions (different types of lighting, different camera resolution, camera movement). The proposed new method of image analysis and processing was associated with three stages: (1) image pre-processing-allowing for the image filtration and stabilization (object location tracking); (2) main image processing-allowing for segmentation of human skin areas, acquisition of brightness changes; (3) signal analysis-filtration, FFT (Fast Fourier Transformation) analysis, pulse calculation. The presented algorithm and method for measuring the pulse rate has the following advantages: (1) it allows for non-contact and non-invasive measurement; (2) it can be carried out using almost any camera, including webcams; (3) it enables to track the object on the stage, which allows for the measurement of the heart rate when the patient is moving; (4) for a minimum of 40,000 pixels, it provides a measurement error of less than ±2 beats per minute for p < 0.01 and sunlight, or a slightly larger error (±3 beats per minute) for artificial lighting; (5) analysis of a single image takes about 40 ms in Matlab Version 7.11.0.584 (R2010b) with Image Processing Toolbox Version 7.1 (R2010b). |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 22% |
| Researcher | 9 | 22% |
| Student > Ph. D. Student | 5 | 12% |
| Student > Bachelor | 3 | 7% |
| Student > Postgraduate | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 9 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 12 | 29% |
| Computer Science | 8 | 20% |
| Medicine and Dentistry | 5 | 12% |
| Neuroscience | 2 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 2 | 5% |
| Unknown | 11 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 November 2016.
All research outputs
#16,756,191
of 24,647,023 outputs
Outputs from BioMedical Engineering OnLine
#447
of 852 outputs
Outputs of similar age
#209,952
of 327,509 outputs
Outputs of similar age from BioMedical Engineering OnLine
#6
of 11 outputs
Altmetric has tracked 24,647,023 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 34th percentile – i.e., 34% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 327,509 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.