Blood Oxygen Concentration and Physiological Data Changes During Motion While Wearing Face Masks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F22%3A43924520" target="_blank" >RIV/60461373:22340/22:43924520 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/70883521:28140/22:63556098 RIV/00216208:11150/22:10453349 RIV/68407700:21730/22:00364359

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/9869822" target="_blank" >https://ieeexplore.ieee.org/document/9869822</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ACCESS.2022.3202931" target="_blank" >10.1109/ACCESS.2022.3202931</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Blood Oxygen Concentration and Physiological Data Changes During Motion While Wearing Face Masks

Popis výsledku v původním jazyce

The study of physiological changes recorded by wearable devices during physical exercises belongs to very important research topics in neurology for the detection of motion disorders or monitoring of the fitness level during sports activities. This paper contributes to this area with studies of the effect of face masks and respirators on blood oxygen concentration, breathing frequency, and the heart rate changes. Experimental data sets include 296 segments of their total length of 60 hours, recorded on a home exercise bike under different motion conditions. Wearable instruments with oximetric, heart rate, accelerometric, and thermal camera sensors were used to fill the own database of signals recorded with selected sampling frequencies. The proposed methodology includes fundamental signal and image processing methods for signal analysis and machine learning tools for labeling image components and detecting facial temperature changes. Results show the minimal effect of mask wearing on blood oxygen concentration but its substantial influence on the breathing frequency and the heart rate. The use of a respirator substantially increased the respiratory rate for the given set of experiments under the load. This indicates how wearable sensors, computational intelligence, and machine learning can be used for motion monitoring and data analysis of signals recorded in different conditions. © 2013 IEEE.

Název v anglickém jazyce

Blood Oxygen Concentration and Physiological Data Changes During Motion While Wearing Face Masks

Popis výsledku anglicky

The study of physiological changes recorded by wearable devices during physical exercises belongs to very important research topics in neurology for the detection of motion disorders or monitoring of the fitness level during sports activities. This paper contributes to this area with studies of the effect of face masks and respirators on blood oxygen concentration, breathing frequency, and the heart rate changes. Experimental data sets include 296 segments of their total length of 60 hours, recorded on a home exercise bike under different motion conditions. Wearable instruments with oximetric, heart rate, accelerometric, and thermal camera sensors were used to fill the own database of signals recorded with selected sampling frequencies. The proposed methodology includes fundamental signal and image processing methods for signal analysis and machine learning tools for labeling image components and detecting facial temperature changes. Results show the minimal effect of mask wearing on blood oxygen concentration but its substantial influence on the breathing frequency and the heart rate. The use of a respirator substantially increased the respiratory rate for the given set of experiments under the load. This indicates how wearable sensors, computational intelligence, and machine learning can be used for motion monitoring and data analysis of signals recorded in different conditions. © 2013 IEEE.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/LTAIN19007" target="_blank" >LTAIN19007: Vývoj pokročilých výpočetních algoritmů pro objektivní posouzení pooperační rehabilitace</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Access

ISSN

2169-3536

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

Neuveden

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

8

Strana od-do

91763-91770

Kód UT WoS článku

000852480700001

EID výsledku v databázi Scopus

2-s2.0-85137583288