Estimation of respiratory volume from thoracoabdominal breathing distances: comparison of two models of machine learning

Dumond, Rémy; Gastinger, Steven; Rahman, Hala Abdul; Faucheur, Alexis Le; Quinton, Patrice; Kang, Haitao; Prioux, Jacques

doi:10.1007/s00421-017-3630-0

Cited by 19 publications

(37 citation statements)

References 59 publications

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“…Additionally, female volunteers will be included in next experimental tests. Nevertheless, the authors recognize that future work has to be done in order to evaluate the accuracy of volume measurements between tests on the same volunteer by adopting the same calibration matrix; this investigation will allow figuring out the intra‐subject variability within different trials .…”

Section: Discussionmentioning

confidence: 99%

Smart textile for respiratory monitoring and thoraco‐abdominal motion pattern evaluation

Massaroni

Venanzi

Silvatti

et al. 2018

Journal of Biophotonics

104

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The use of wearable systems for monitoring vital parameters has gained wide popularity in several medical fields. The focus of the present study is the experimental assessment of a smart textile based on 12 fiber Bragg grating sensors for breathing monitoring and thoraco-abdominal motion pattern analysis. The feasibility of the smart textile for monitoring several temporal respiratory parameters (ie, breath-by-breath respiratory period, breathing frequency, duration of inspiratory and expiratory phases), volume variations of the whole chest wall and of its compartments is performed on 8 healthy male volunteers. Values gathered by the textile are compared to the data obtained by a motion analysis system, used as the reference instrument. Good agreement between the 2 systems on both respiratory period (bias of 0.01 seconds), breathing frequency (bias of -0.02 breaths/min) and tidal volume (bias of 0.09 L) values is demonstrated. Smart textile shows good performance in the monitoring of thoraco-abdominal pattern and its variation, as well.

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Section: Discussionmentioning

confidence: 99%

Smart textile for respiratory monitoring and thoraco‐abdominal motion pattern evaluation

Massaroni

Venanzi

Silvatti

et al. 2018

Journal of Biophotonics

104

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“…Moreover, in RMP sensors can become non-linear at higher intensities resulting in outcomes outside the calibrated range (38). In the studies mentioned earlier, the bias and limits of agreement increase with increased activity (39,52,55). However, during exercise measurement of dynamic volume with RIP are still comparable to spirometry values.…”

Section: Movementmentioning

confidence: 95%

“…Multiple systems are commercially available (40,(68)(69)(70), and an even greater number of systems is self-made (33,39). Not all systems have the same accuracy.…”

Section: How Accurate Are Telemonitoring Systems?mentioning

confidence: 99%

Telemonitoring Techniques for Lung Volume Measurement: Accuracy, Artifacts and Effort

Mannée

Jongh

Helvoort

2020

Front. Digit. Health

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Telemonitoring becomes more important in pulmonary research. It can be used to decrease the pressure on the health care system, to lower the costs of health care and to increase quality of life of patients. Previous studies show contradictory results regarding the effectiveness of telemonitoring. According to multiple researchers, inefficiency can be a result of poor study design, low data quality and usability issues. To counteract these issues, this review proves for an in-depth explanation of four (potential) telemonitoring systems in terms of work principle, accuracy, disturbing factors and usability. The evaluated systems are portable spirometry/breath-by-breath analyzers, respiratory inductance and magnetic plethysmography and electrical impedance tomography. These insights can be used to select the optimal technique for a specific purpose in future studies.

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“…A comparison between a machine-learning based model and measurements of respiratory rate was performed by Dumond et al [20].…”

Section: Current Statementioning

confidence: 99%

“…As a conclusion, the following average values can be used for adults:  low activity (breathing while lying): 0.45 m 3 /h [19]  low activity (breathing while sitting, standing or talking): 0.54 m 3 /h [19,20]  singing: 0.65 m 3 /h [21]  mid activity (physical work): 0.9 m 3 /h [20]  sports: 1.2 m 3 /h [18,20] For children, the lung volume is smaller. Therefore, the respiratory rate for children aged 14 can be assumed to be 0.45 m 3 /h for low activity (breathing while sitting, standing, talking) [22].…”

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confidence: 99%

Predicted Infection Risk for Aerosol Transmission of SARS-CoV-2

Kriegel

Buchholz

Gastmeier

et al. 2020

Preprint

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Currently, airborne transmission is seen as the most important transmission path for SARS-CoV-2. In this investigation, models of other researchers with the aim to predict an infection risk for exposed persons in a room through aerosols emitted by an infectious case-patient were extended. As a novelty parameters or boundary conditions, namely the non-stationarity of aerosol and the half life of aerosolized virus, were included and a new method for determining the quanta emission rate based on measurements of the particle emission rate and respiratory rate at different types of activities was implemented. As a second step, the model was applied to twelve outbreaks to compare the predicted infection risk with the observed attack rate. To estimate a 'credible interval' of the predicted infection risk the quanta emission rate, the respiratory rate as well as the air volume flow were varied. In nine out of twelve outbreaks, the calculated predicted infection risk via aerosols was found to be in the range the attack rate (with the variation of the boundary conditions) and reasons for the observed larger divergence were discussed. The validation was considered successful and therefore, the use of the model could be recommended to predict the risk of an infection via aerosols in given situations. Furthermore, appropriate preventive measures can be designed.

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Estimation of respiratory volume from thoracoabdominal breathing distances: comparison of two models of machine learning

Abstract: Our results demonstrate that this new processing approach for RMP seems to be a valid tool for estimating V with sufficient accuracy during lying, sitting and standing and under various exercise conditions.

Cited by 19 publications

References 59 publications

Smart textile for respiratory monitoring and thoraco‐abdominal motion pattern evaluation

Smart textile for respiratory monitoring and thoraco‐abdominal motion pattern evaluation

Telemonitoring Techniques for Lung Volume Measurement: Accuracy, Artifacts and Effort

Predicted Infection Risk for Aerosol Transmission of SARS-CoV-2

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