Estimation of respiratory variables from thoracoabdominal breathing distance: a review of different techniques and calibration methods

Houssein, Aya; Ge, Di; Gastinger, Steven; Dumond, Rémy; Prioux, Jacques

doi:10.1088/1361-6579/ab0b63

Cited by 15 publications

(15 citation statements)

References 58 publications

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“…Patients may perceive intolerable dyspnea during exercise before criteria defining ventilatory limitation are reached. In chronic obstructive pulmonary disease (COPD), 20–50% of patients experience exercise-limiting dyspnea in the setting of sufficient breathing reserve ( 3 , 4 ). Relying solely on breathing reserve to assess ventilatory response may therefore underestimate physiologic impairment.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of Dynamic Respiratory Mechanical Abnormalities During Conventional CPET

et al. 2020

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Assessment of the ventilatory response to exercise is important in evaluating mechanisms of dyspnea and exercise intolerance in chronic cardiopulmonary diseases. The characteristic mechanical derangements that occur during exercise in chronic respiratory conditions have previously been determined in seminal studies using esophageal catheter pressure-derived measurements. In this brief review, we examine the emerging role and clinical utility of conventional assessment of dynamic respiratory mechanics during exercise testing. Thus, we provide a physiologic rationale for measuring operating lung volumes, breathing pattern, and flow–volume loops during exercise. We consider standardization of inspiratory capacity-derived measurements and their practical implementation in clinical laboratories. We examine the evidence that this iterative approach allows greater refinement in evaluation of ventilatory limitation during exercise than traditional assessments of breathing reserve. We appraise the available data on the reproducibility and responsiveness of this methodology. In particular, we review inspiratory capacity measurement and derived operating lung volumes during exercise. We demonstrate, using recent published data, how systematic evaluation of dynamic mechanical constraints, together with breathing pattern analysis, can provide valuable insights into the nature and extent of physiological impairment contributing to exercise intolerance in individuals with common chronic obstructive and restrictive respiratory disorders.

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Section: Introductionmentioning

confidence: 99%

“…Other non-invasive methods of assessing respiratory mechanics (e.g., gas dilution techniques and optoelectronic plethysmography) are beyond the scope of this mini-review targeted for clinicians. We direct the interested reader to other recently published reviews on this topic ( 3 , 4 ).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Dynamic Respiratory Mechanical Abnormalities During Conventional CPET

et al. 2020

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“…This study is part of the Sherpam (Sensors for Health Recording and Physical Activity Monitoring) project (https: //project.inria.fr/sherpam/) that aims to develop a new generation monitoring system to allow health monitoring at home, during indoor and outdoor activities (at work, shopping, sports practicing, etc). Concretely, the project has the ambition to improve the recognition of PA (Rahman et al 2017) and the estimation of associated energy expenditure in healthy subjects (Khreis et al 2020;Houssein et al 2019). A modular Android application aggregates data from various types of sensors and transmits these data to a remote aggregation server for storage and analysis.…”

Section: Methodsmentioning

confidence: 99%

A novel algorithm for minute ventilation estimation in remote health monitoring with magnetometer plethysmography

Houssein

Gastinger

et al. 2021

Computers in Biology and Medicine

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Purpose The purpose of this study was to evaluate the accuracy of minute ventilation (̇ ) estimation using a novel method based on a non-linear algorithm coupled with cycle-based features. The experiment protocol was well adapted for remote health monitoring applications by exploiting data streams from respiratory magnetometer plethysmography (RMP) during different physical activity (PA) types. Methods Thirteen subjects with an age distribution of 24.1 ± 3.4 years performed thirteen PA ranging from sedentary to moderate intensity (walking at 4 and 6 km/h, running at 9 and 12 km/h, biking at 90 W and 110 W). In total, 3359 temporal segments of 10s were acquired using the Nomics RMP device while the iWorx spirometer was used for referencė measurements. An artificial neural network (ANN) model based on respiration features was used to estimatė and compared to the multiple linear regression (MLR) model. We also compared the subject-specific approach with the subject-independent approach. Results The ANN model using subject-specific approach achieved better accuracy for thė estimation. The bias was between 0.20 ± 0.87 and 0.78 ± 3 l/min with the ANN model as compared to 0.73 ± 3.19 and 4.17 ± 2.61 l/min with the MLR model. Conclusion Our results demonstrated the pertinence of processing data streams from wearable RMP device to estimate thė with sufficient accuracy for various PA types. Due to its low-complexity and real-time algorithm design, the current approach can be easily integrated into most remote health monitoring applications coupled with wearable sensors.

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“…Spirometry consists in the measurement of the air flow produced during the respiration, when the subject is asked to breath into a mask; thus, it is objective, noninvasive, sensitive to early change, and reproducible [7,8]. On the contrary, optoelectronic plethysmography consists of a motion analysis system which measures the changes in the chest wall during breathing by modelling the thoraco-abdominal surface [9,10].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Tidal Volume during Exercise Stress Test from Wearable-Device Measures of Heart Rate and Breathing Rate

et al. 2022

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Tidal volume (TV), defined as the amount of air that moves in or out of the lungs with each respiratory cycle, is important in evaluating the respiratory function. Although TV can be reliably measured in laboratory settings, this information is hardly obtainable under everyday living conditions. Under such conditions, wearable devices could provide valuable support to monitor vital signs, such as heart rate (HR) and breathing rate (BR). The aim of this study was to develop a model to estimate TV from wearable-device measures of HR and BR during exercise. HR and BR were acquired through the Zephyr Bioharness 3.0 wearable device in nine subjects performing incremental cycling tests. For each subject, TV during exercise was obtained with a metabolic cart (Cosmed). A stepwise regression algorithm was used to create the model using as possible predictors HR, BR, age, and body mass index; the model was then validated using a leave-one-subject-out cross-validation procedure. The performance of the model was evaluated using the explained variance (R2), obtaining values ranging from 0.65 to 0.72. The proposed model is a valid method for TV estimation with wearable devices and can be considered not subject-specific and not instrumentation-specific.

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Estimation of respiratory variables from thoracoabdominal breathing distance: a review of different techniques and calibration methods

Cited by 15 publications

References 58 publications

Evaluation of Dynamic Respiratory Mechanical Abnormalities During Conventional CPET

Evaluation of Dynamic Respiratory Mechanical Abnormalities During Conventional CPET

A novel algorithm for minute ventilation estimation in remote health monitoring with magnetometer plethysmography

Estimation of Tidal Volume during Exercise Stress Test from Wearable-Device Measures of Heart Rate and Breathing Rate

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