The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Thomas Similowski - One of the best experts on this subject based on the ideXlab platform.
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Physiological Validation of an Airborne Ultrasound Based Surface Motion Camera for a Contactless Characterization of Breathing Pattern in Humans
Frontiers in Physiology, 2019Co-Authors: Marie-cecile Nierat, Pierantonio Laveneziana, Bruno-pierre Dubé, Pavel Shirkovskiy, Ros-kiri Ing, Thomas SimilowskiAbstract:Characterizing the breathing pattern in naturally breathing humans brings important information on respiratory mechanics, respiratory muscle, and breathing control. However, measuring breathing modifies breathing (observer effect) through the effects of instrumentation and awareness: measuring human breathing under true ecological conditions is currently impossible. This study tested the hypothesis that non-contact vibrometry using airborne ultrasound (SONAR) could measure breathing movements in a contactless and invisible manner. Thus, first, we evaluated the validity of SONAR measurements by testing their interchangeability with pneumotachograph (PNT) measurements obtained at the same time. We also aimed at evaluating the observer effect by comparing breathing variability obtained by SONAR versus SONAR-PNT measurements. Twenty-three healthy subjects (12 men and 11 women; mean age 33 years - range: 20-54) were studied during resting breathing while sitting on a chair. Breathing activity was described in terms of ventilatory flow measured using a PNT and, either simultaneously or sequentially, with a SONAR device measuring the velocity of the surface motion of the chest wall. SONAR was focused either anteriorly on the xiphoid process or posteriorly on the lower part of the Costal Margin. Discrete ventilatory temporal and volume variables and their coefficients of variability were calculated from the flow signal (PNT) and the velocity signal (SONAR) and tested for interchangeability (Passing-Bablok regression). Tidal volume (VT) and displacement were linearly related. Breathing frequency (BF), total cycle time (TT), inspiratory time (TI), and expiratory time (TE) met interchangeability criteria. Their coefficients of variation were not statistically significantly different with PNT and SONAR-only. This was true for both the anterior and the posterior SONAR measurements. Non-contact vibrometry using airborne ultrasound is a valid tool for measuring resting breathing pattern.
Marie-cecile Nierat - One of the best experts on this subject based on the ideXlab platform.
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Physiological Validation of an Airborne Ultrasound Based Surface Motion Camera for a Contactless Characterization of Breathing Pattern in Humans
Frontiers in Physiology, 2019Co-Authors: Marie-cecile Nierat, Pierantonio Laveneziana, Bruno-pierre Dubé, Pavel Shirkovskiy, Ros-kiri Ing, Thomas SimilowskiAbstract:Characterizing the breathing pattern in naturally breathing humans brings important information on respiratory mechanics, respiratory muscle, and breathing control. However, measuring breathing modifies breathing (observer effect) through the effects of instrumentation and awareness: measuring human breathing under true ecological conditions is currently impossible. This study tested the hypothesis that non-contact vibrometry using airborne ultrasound (SONAR) could measure breathing movements in a contactless and invisible manner. Thus, first, we evaluated the validity of SONAR measurements by testing their interchangeability with pneumotachograph (PNT) measurements obtained at the same time. We also aimed at evaluating the observer effect by comparing breathing variability obtained by SONAR versus SONAR-PNT measurements. Twenty-three healthy subjects (12 men and 11 women; mean age 33 years - range: 20-54) were studied during resting breathing while sitting on a chair. Breathing activity was described in terms of ventilatory flow measured using a PNT and, either simultaneously or sequentially, with a SONAR device measuring the velocity of the surface motion of the chest wall. SONAR was focused either anteriorly on the xiphoid process or posteriorly on the lower part of the Costal Margin. Discrete ventilatory temporal and volume variables and their coefficients of variability were calculated from the flow signal (PNT) and the velocity signal (SONAR) and tested for interchangeability (Passing-Bablok regression). Tidal volume (VT) and displacement were linearly related. Breathing frequency (BF), total cycle time (TT), inspiratory time (TI), and expiratory time (TE) met interchangeability criteria. Their coefficients of variation were not statistically significantly different with PNT and SONAR-only. This was true for both the anterior and the posterior SONAR measurements. Non-contact vibrometry using airborne ultrasound is a valid tool for measuring resting breathing pattern.
Junseok Chae - One of the best experts on this subject based on the ideXlab platform.
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machine learning enabled wireless wearable sensors to study individuality of respiratory behaviors
Biosensors and Bioelectronics, 2021Co-Authors: Ang Chen, Jianwei Zhang, Liangkai Zhao, Rachel Diane Rhoades, Dongyun Kim, Jianming Liang, Junseok ChaeAbstract:Abstract Respiratory behaviors provide useful measures of lung health. The current methods have limited capabilities of continuous characterization of respiratory behaviors, often required to assess respiratory disorders and diseases. This work presents a system equipped with a machine learning algorithm, capable of continuously monitoring respiratory behaviors. The system, consisting of two wireless wearable sensors, accurately extracts and classifies the features of respiratory behaviors of subjects within various postures, wirelessly transmitting the temporal respiratory behaviors to a laptop. The sensors were attached on the midway of the xiphoid process and the Costal Margin, and 1 cm above the umbilicus, respectively. The wireless wearable sensor, consisting of ultrasound emitter, ultrasound receiver, data acquisition and wireless transmitter, has a small footprint and light weight. The sensors correlate the mechanical strain at wearing sites to lung volume by measuring the local circumference changes of the chest and abdominal walls simultaneously. Eleven subjects were recruited to evaluate the wireless wearable sensors. Three different random forest classifiers, including generic, individual, and weighted-adaptive classifiers, were used to process the wireless data of the subjects at four different postures. The results demonstrate the respiratory behaviors are individual- and posture-dependent. The generic classifier merely reaches the accuracy of classifying postures of 21.9 ± 1.7% while individual and weighted-adaptive classifiers mark substantially high, up to 98.9 ± 0.6% and 98.8 ± 0.6%, respectively. The accurate monitoring of respiratory behaviors can track the progression of respiratory disorders and diseases, including chronic respiratory obstructive disease (COPD), asthma, apnea, and others for timely and objective approaches for control.
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Wireless Wearable Ultrasound Sensor on a Paper Substrate to Characterize Respiratory Behavior
2019Co-Authors: Ang Chen, Rachel Diane Rhoades, Andrew Joshua Halton, Jayden Charles Booth, Xinhao Shi, Junseok ChaeAbstract:Respiratory behavior contains crucial parameters to feature lung functionality, including respiratory rate, profile, and volume. The current well-adopted method to characterize respiratory behavior is spirometry using a spirometer, which is bulky, heavy, expensive, requires a trained provider to operate, and is incapable of continuous monitoring of respiratory behavior, which is often critical to assess chronic respiratory diseases. This work presents a wireless wearable sensor on a paper substrate that is capable of continuous monitoring of respiratory behavior and delivering the clinically relevant respiratory information to a smartphone. The wireless wearable sensor was attached on the midway of the xiphoid process and the Costal Margin, corresponding to the abdomen-apposed rib cage, based on the anatomical and experimental analysis. The sensor, with a footprint of 40 × 35 × 6 mm3 and weighing 6.5 g, including a 2.7 g battery, consists of three subsystems, (i) ultrasound emitter, (ii) ultrasound receiver, and (iii) data acquisition and wireless transmitter. The sensor converts the linear strain at the wearing site to the lung volume change by measuring the change in ultrasound pressure as a function of the distance between the emitter and the receiver. The temporal lung volume change data, directly converted from the ultrasound pressure, is wirelessly transmitted to a smartphone where a custom-designed app computes to show volume-time and flow rate-volume loop graphs, standard respiratory analysis plots. The app analyzes the plots to show the clinically relevant respiratory behavioral parameters, such as forced vital capacity (FVC) and forced expiratory volume delivered in the first second (FEV1). Potential user-induced error on sensor placement and temperature sensitivity were studied to demonstrate the sensor maintains its performance within a reasonable range of those variables. Eight volunteers were recruited to evaluate the sensor, which showed the mean deviation of the FEV1/FVC ratio in the range of 0.00–4.25% when benchmarked by the spirometer. The continuous measurement of respiratory behavioral parameters helps track the progression of the respiratory diseases, including asthma progression to provide alerts to relevant caregivers to seek needed timely treatment
Pierantonio Laveneziana - One of the best experts on this subject based on the ideXlab platform.
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Physiological Validation of an Airborne Ultrasound Based Surface Motion Camera for a Contactless Characterization of Breathing Pattern in Humans
Frontiers in Physiology, 2019Co-Authors: Marie-cecile Nierat, Pierantonio Laveneziana, Bruno-pierre Dubé, Pavel Shirkovskiy, Ros-kiri Ing, Thomas SimilowskiAbstract:Characterizing the breathing pattern in naturally breathing humans brings important information on respiratory mechanics, respiratory muscle, and breathing control. However, measuring breathing modifies breathing (observer effect) through the effects of instrumentation and awareness: measuring human breathing under true ecological conditions is currently impossible. This study tested the hypothesis that non-contact vibrometry using airborne ultrasound (SONAR) could measure breathing movements in a contactless and invisible manner. Thus, first, we evaluated the validity of SONAR measurements by testing their interchangeability with pneumotachograph (PNT) measurements obtained at the same time. We also aimed at evaluating the observer effect by comparing breathing variability obtained by SONAR versus SONAR-PNT measurements. Twenty-three healthy subjects (12 men and 11 women; mean age 33 years - range: 20-54) were studied during resting breathing while sitting on a chair. Breathing activity was described in terms of ventilatory flow measured using a PNT and, either simultaneously or sequentially, with a SONAR device measuring the velocity of the surface motion of the chest wall. SONAR was focused either anteriorly on the xiphoid process or posteriorly on the lower part of the Costal Margin. Discrete ventilatory temporal and volume variables and their coefficients of variability were calculated from the flow signal (PNT) and the velocity signal (SONAR) and tested for interchangeability (Passing-Bablok regression). Tidal volume (VT) and displacement were linearly related. Breathing frequency (BF), total cycle time (TT), inspiratory time (TI), and expiratory time (TE) met interchangeability criteria. Their coefficients of variation were not statistically significantly different with PNT and SONAR-only. This was true for both the anterior and the posterior SONAR measurements. Non-contact vibrometry using airborne ultrasound is a valid tool for measuring resting breathing pattern.
Bruno-pierre Dubé - One of the best experts on this subject based on the ideXlab platform.
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Physiological Validation of an Airborne Ultrasound Based Surface Motion Camera for a Contactless Characterization of Breathing Pattern in Humans
Frontiers in Physiology, 2019Co-Authors: Marie-cecile Nierat, Pierantonio Laveneziana, Bruno-pierre Dubé, Pavel Shirkovskiy, Ros-kiri Ing, Thomas SimilowskiAbstract:Characterizing the breathing pattern in naturally breathing humans brings important information on respiratory mechanics, respiratory muscle, and breathing control. However, measuring breathing modifies breathing (observer effect) through the effects of instrumentation and awareness: measuring human breathing under true ecological conditions is currently impossible. This study tested the hypothesis that non-contact vibrometry using airborne ultrasound (SONAR) could measure breathing movements in a contactless and invisible manner. Thus, first, we evaluated the validity of SONAR measurements by testing their interchangeability with pneumotachograph (PNT) measurements obtained at the same time. We also aimed at evaluating the observer effect by comparing breathing variability obtained by SONAR versus SONAR-PNT measurements. Twenty-three healthy subjects (12 men and 11 women; mean age 33 years - range: 20-54) were studied during resting breathing while sitting on a chair. Breathing activity was described in terms of ventilatory flow measured using a PNT and, either simultaneously or sequentially, with a SONAR device measuring the velocity of the surface motion of the chest wall. SONAR was focused either anteriorly on the xiphoid process or posteriorly on the lower part of the Costal Margin. Discrete ventilatory temporal and volume variables and their coefficients of variability were calculated from the flow signal (PNT) and the velocity signal (SONAR) and tested for interchangeability (Passing-Bablok regression). Tidal volume (VT) and displacement were linearly related. Breathing frequency (BF), total cycle time (TT), inspiratory time (TI), and expiratory time (TE) met interchangeability criteria. Their coefficients of variation were not statistically significantly different with PNT and SONAR-only. This was true for both the anterior and the posterior SONAR measurements. Non-contact vibrometry using airborne ultrasound is a valid tool for measuring resting breathing pattern.
