Cargando…
Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing
Mathematical and signal-processing methods were used to obtain reliable measurements of the heartbeat pulse rate and information on oxygen concentration in the blood using short video recordings of the index finger attached to a smartphone built-in camera. Various types of smartphones were used with...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863359/ https://www.ncbi.nlm.nih.gov/pubmed/36679533 http://dx.doi.org/10.3390/s23020737 |
_version_ | 1784875314549096448 |
---|---|
author | Antoniou, Panayiotis Nestoros, Marios Polycarpou, Anastasis C. |
author_facet | Antoniou, Panayiotis Nestoros, Marios Polycarpou, Anastasis C. |
author_sort | Antoniou, Panayiotis |
collection | PubMed |
description | Mathematical and signal-processing methods were used to obtain reliable measurements of the heartbeat pulse rate and information on oxygen concentration in the blood using short video recordings of the index finger attached to a smartphone built-in camera. Various types of smartphones were used with different operating systems (e.g., iOS, Android) and capabilities. A range of processing algorithms were applied to the red-green-blue (RGB) component signals, including mean intensity calculation, moving average smoothing, and quadratic filtering based on the Savitzky–Golay filter. Two approaches—gradient and local maximum methods—were used to determine the pulse rate, which provided similar results. A fast Fourier transform was applied to the signal to correlate the signal’s frequency components with the pulse rate. We resolved the signal into its DC and AC components to calculate the ratio-of-ratios of the AC and DC components of the red and green signals, a method which is often used to estimate the oxygen concentration in blood. A series of measurements were performed on healthy human subjects, producing reliable data that compared favorably to benchmark data obtained by commercial and medically approved oximeters. Furthermore, the effect of the video recording duration on the accuracy of the results was investigated. |
format | Online Article Text |
id | pubmed-9863359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98633592023-01-22 Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing Antoniou, Panayiotis Nestoros, Marios Polycarpou, Anastasis C. Sensors (Basel) Article Mathematical and signal-processing methods were used to obtain reliable measurements of the heartbeat pulse rate and information on oxygen concentration in the blood using short video recordings of the index finger attached to a smartphone built-in camera. Various types of smartphones were used with different operating systems (e.g., iOS, Android) and capabilities. A range of processing algorithms were applied to the red-green-blue (RGB) component signals, including mean intensity calculation, moving average smoothing, and quadratic filtering based on the Savitzky–Golay filter. Two approaches—gradient and local maximum methods—were used to determine the pulse rate, which provided similar results. A fast Fourier transform was applied to the signal to correlate the signal’s frequency components with the pulse rate. We resolved the signal into its DC and AC components to calculate the ratio-of-ratios of the AC and DC components of the red and green signals, a method which is often used to estimate the oxygen concentration in blood. A series of measurements were performed on healthy human subjects, producing reliable data that compared favorably to benchmark data obtained by commercial and medically approved oximeters. Furthermore, the effect of the video recording duration on the accuracy of the results was investigated. MDPI 2023-01-09 /pmc/articles/PMC9863359/ /pubmed/36679533 http://dx.doi.org/10.3390/s23020737 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Antoniou, Panayiotis Nestoros, Marios Polycarpou, Anastasis C. Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing |
title | Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing |
title_full | Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing |
title_fullStr | Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing |
title_full_unstemmed | Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing |
title_short | Calculation of Heartbeat Rate and SpO(2) Parameters Using a Smartphone Camera: Analysis and Testing |
title_sort | calculation of heartbeat rate and spo(2) parameters using a smartphone camera: analysis and testing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863359/ https://www.ncbi.nlm.nih.gov/pubmed/36679533 http://dx.doi.org/10.3390/s23020737 |
work_keys_str_mv | AT antonioupanayiotis calculationofheartbeatrateandspo2parametersusingasmartphonecameraanalysisandtesting AT nestorosmarios calculationofheartbeatrateandspo2parametersusingasmartphonecameraanalysisandtesting AT polycarpouanastasisc calculationofheartbeatrateandspo2parametersusingasmartphonecameraanalysisandtesting |