2019
DOI: 10.1016/j.jtbi.2019.03.001
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Sources of breathing pattern variability in the respiratory feedback control loop

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Cited by 9 publications
(5 citation statements)
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References 36 publications
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“…5 and Table II). The results of previous studies indicate that COPD patients had a restricted breathing pattern due to the disease [16], [17], [35]. This hypothesis together with our results suggest that the breathing pattern variability decreases with COPD severity, reflecting the impairment of the breathing control mechanisms.…”
Section: Breathing Pattern Characterizationsupporting
confidence: 80%
See 1 more Smart Citation
“…5 and Table II). The results of previous studies indicate that COPD patients had a restricted breathing pattern due to the disease [16], [17], [35]. This hypothesis together with our results suggest that the breathing pattern variability decreases with COPD severity, reflecting the impairment of the breathing control mechanisms.…”
Section: Breathing Pattern Characterizationsupporting
confidence: 80%
“…Therefore, these previous results suggest that COPD has a direct effect on the mechanism involved in the respiratory control, making it more difficult for the patients to adapt to different breathing demands. Jaworski et al developed a computational model to evaluate the sources of breathing pattern variability [35]. The model evidenced that the main changes in variability of breathing pattern were caused by an increase in lung resistance and impairments in gas exchange, which are known to be commonly caused by pulmonary diseases.…”
Section: Breathing Pattern Characterizationmentioning
confidence: 99%
“…One notable limitation within the current version of the task is the lack of physiological measures of respiratory flow and pressure, as the pressure differential generated across any static inspiratory resistance will be flow-dependent. Therefore, measures of interoceptive sensitivity (via the number of filters that were able to be detected) may be subject to the natural variations in breathing patterns across participants and between trials ( Benchetrit, 2000 , Bruce, 1996 , Daubenspeck, 1981 , Jaworski and Bates, 2019 , Mador and Tobin, 1991 ). Therefore, measures of inspiratory pressure and flow could be recorded throughout this task, which would capture and allow us to quantify the changes in both the inspiratory pressure and flow (relative to the baseline breaths) that each participant utilised to detect the number of filters present.…”
Section: Discussionmentioning
confidence: 99%
“…This respiratory rate is not completely regular as it can change due to external factors such as: speech, exercise, walking, stress or even environmental changes. Respiratory rate can also be voluntarily forced by the subject to maintain (hyperapnoea) or to exhale (apnoea) all the air from the lungs [39,23,40].…”
Section: Breathingmentioning
confidence: 99%
“…Studies involving the respiratory signal have been traditionally performed to assess sleeping disorders such as sleep apnoea or related to cardiovascular diseases [43,22,44,45]. Nowadays the analysis of this signal has exceeded the medical practice [40] to reach new fields of study such as: drowsiness detection [26] or even to asses the contribution of the respiratory rate to concentration on meditation practice [46].…”
Section: Respiratory Signalmentioning
confidence: 99%