Monitoring respiratory rate in adults

Hill, Barry; Annesley, Sarah H

doi:10.12968/bjon.2020.29.1.12

Cited by 39 publications

(27 citation statements)

References 7 publications

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“…Blood pressure was measured using an automatic blood pressure monitor (HEM-8712, Omron healthcare Co., Ltd., Kyoto, Japan). Respiratory rate was investigated by observation, watching the rise and fall of the chest of each subject and counting the number of times that they complete a breath cycle including inhalation and exhalation within a fixed period of time to define the number of breaths per minute [ 20 ]. Borg rating of perceived exertion scale (6–20 scales) was used to evaluate perceived exertion.…”

Section: Methodsmentioning

confidence: 99%

Effects of Wearing Face Masks on Cardiorespiratory Parameters at Rest and after Performing the Six-Minute Walk Test in Older Adults

Amput

Wongphon

2022

Geriatrics

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The effects of wearing cloth masks and surgical masks were investigated on respiratory rate, heart rate, blood pressure, oxygen saturation and perceived exertion at rest and after performing a six-minute walk test (6MWT) in older adults. Forty older adults were recruited and randomized into six groups including wearing no mask, cloth masks and surgical masks, at rest and during the 6MWT. At rest, all subjects sat quietly wearing no mask, a cloth mask or a surgical mask. All subjects performed a 6MWT by walking as fast as possible without running while wearing no mask, a cloth mask or a surgical mask. Respiratory rate, heart rate, blood pressure, oxygen saturation and perceived exertion were assessed before and after the rest and the 6MWT. Results showed that cloth masks and surgical masks did not impact cardiorespiratory parameters at rest or after performing a 6MWT, while an increase in perceived exertion was apparent in the groups wearing surgical masks and cloth masks after performing the 6MWT (p < 0.01). Cloth masks and surgical masks did not have an impact on cardiorespiratory fitness at rest and after performing the 6MWT in older adults.

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Section: Methodsmentioning

confidence: 99%

Effects of Wearing Face Masks on Cardiorespiratory Parameters at Rest and after Performing the Six-Minute Walk Test in Older Adults

Amput

Wongphon

2022

Geriatrics

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“…Another explanation for the higher MAE relates to the physiological relationship between the breathing rate and the PPG signal. As explained in [ 43 ], breathing rate that is out of the normal range for healthy adults (12–20 bpm) might affect the breathing rate information encoded in the PPG signal. Figure 9 c presents the results achieved when data from both datasets combined was used for evaluation.…”

Section: Resultsmentioning

confidence: 99%

Breathing Rate Estimation from Head-Worn Photoplethysmography Sensor Data Using Machine Learning

Stankoski

Kiprijanovska

Mavridou

et al. 2022

Sensors

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Breathing rate is considered one of the fundamental vital signs and a highly informative indicator of physiological state. Given that the monitoring of heart activity is less complex than the monitoring of breathing, a variety of algorithms have been developed to estimate breathing activity from heart activity. However, estimating breathing rate from heart activity outside of laboratory conditions is still a challenge. The challenge is even greater when new wearable devices with novel sensor placements are being used. In this paper, we present a novel algorithm for breathing rate estimation from photoplethysmography (PPG) data acquired from a head-worn virtual reality mask equipped with a PPG sensor placed on the forehead of a subject. The algorithm is based on advanced signal processing and machine learning techniques and includes a novel quality assessment and motion artifacts removal procedure. The proposed algorithm is evaluated and compared to existing approaches from the related work using two separate datasets that contains data from a total of 37 subjects overall. Numerous experiments show that the proposed algorithm outperforms the compared algorithms, achieving a mean absolute error of 1.38 breaths per minute and a Pearson’s correlation coefficient of 0.86. These results indicate that reliable estimation of breathing rate is possible based on PPG data acquired from a head-worn device.

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“…On the basis of diverse respiratory rates of an adult in a state of calm, there are three types of breathing states including bradypnea (less than 12 breaths/min), normal respiration (12−20 breaths/ min), and tachypnea (more than 20 breaths/min). 8,9 Therefore, Once the response number of times per minute becomes far beyond the range of normal respiration in Figure 6a, it becomes an early warning signal of potential health risks that should be given medical attention. It should be noted that there will be some variation relying on age and medical condition, but it is accepted that a respiratory rate of above 25 breaths/min can indicate that a patient could be deteriorating.…”

Section: Resultsmentioning

confidence: 99%

“…It is mainly on account of the breathing process involving the heart, lungs, blood vessels, and red blood cells throughout the body, and problems with either of those factors may severely affect the frequency of respiration. 7,8 Generally, the normal respiratory rate for a healthy adult is 12−20 breaths per minute. Far beyond the range, certain disease states such as cardiac arrest, asthma, pulmonary embolism, etc.…”

Section: Introductionmentioning

confidence: 99%

Compressible and Stretchable Magnetoelectric Sensors Based on Liquid Metals for Highly Sensitive, Self-Powered Respiratory Monitoring

Zhou

Zou

et al. 2021

ACS Appl. Mater. Interfaces

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Healthcare monitoring, especially for respiration, has attracted tremendous attention from academics considering the great significance of health information feedback. The respiratory rate, as a critical health indicator, has been used to screen and evaluate potential illness risks in early medical diagnoses. A selfpowered sensing system for medical monitoring is critical and imperative due to needless battery replacement and simple assembly. However, the development of a self-powered respiratory sensor with highly sensitive performance is still a daunting challenge. In this work, a compressible and stretchable magnetoelectric sensor (CSMS) with an arch-shaped air gap is reported, enabling self-powered respiratory monitoring driven by exhaled/inhaled breath. The CSMS contains two key functional materials: liquid metals and magnetic powders both with low Young's modulus, allowing for sensing compressibility and stretchability simultaneously. More importantly, such a magnetoelectric sensor exhibits mechanoelectrical converting capacity under an external force, which has been verified by Maxwell numerical simulation. Owing to the air-layer introduction, the magnetoelectric sensors achieve high sensitivity (up to 17.73 kPa −1 ), fast response, and long-term stability. The highly sensitive and self-powered magnetoelectric sensor can be further applied as a noninvasive, miniaturized, and portable respiratory monitoring system with the aim of warning for potential health risks. We anticipate that this technique will create an avenue for self-powered respiratory monitoring fields.

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Monitoring respiratory rate in adults

Cited by 39 publications

References 7 publications

Effects of Wearing Face Masks on Cardiorespiratory Parameters at Rest and after Performing the Six-Minute Walk Test in Older Adults

Effects of Wearing Face Masks on Cardiorespiratory Parameters at Rest and after Performing the Six-Minute Walk Test in Older Adults

Breathing Rate Estimation from Head-Worn Photoplethysmography Sensor Data Using Machine Learning

Compressible and Stretchable Magnetoelectric Sensors Based on Liquid Metals for Highly Sensitive, Self-Powered Respiratory Monitoring

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