ArticleBiomedical engineering online2016
Blood pulsation measurement using cameras operating in visible light: limitations.
Article in Biomedical engineering online, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Effectiveness of consumer-grade contactless vital signs monitors: a systematic review and meta-analysis.Journal of clinical monitoring and computing · 2022Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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).
methodsThe 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. RESULTS AND
conclusionsThe 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).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.