New physiological bench test reproducing nocturnal breathing pattern of patients with sleep disordered breathing


Autoři: Shuo Liu aff001;  Yann Rétory aff001;  Amélie Sagniez aff001;  Sébastien Hardy aff001;  François Cottin aff002;  Gabriel Roisman aff004;  Michel Petitjean aff002
Působiště autorů: Centre EXPLOR, Air Liquide Healthcare, Gentilly, France aff001;  CIAMS, Univ. Paris-Sud, Université Paris-Saclay, Orsay Cedex, France aff002;  CIAMS, Université d’Orléans, Orléans, France aff003;  Centre du Sommeil, Service d’Explorations Fonctionnelles Multidisciplinaires, Hôpital Antoine Béclère, Assistance Publique-Hôpitaux de Paris, Clamart, France aff004
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225766

Souhrn

Previous studies have shown that Automatic Positive Airway Pressure devices display different behaviors when connected to a bench using theoretical respiratory cycle scripts. However, these scripts are limited and do not simulate physiological behavior during the night. Our aim was to develop a physiological bench that is able to simulate patient breathing airflow by integrating polygraph data. We developed an algorithm analyzing polygraph data and transformed this information into digital inputs required by the bench hardware to reproduce a patient breathing profile on bench. The inputs are respectively the simulated respiratory muscular effort pressure input for an artificial lung and the sealed chamber pressure to regulate the Starling resistor. We did simulations on our bench for a total of 8 hours and 59 minutes for a breathing profile from the demonstration recording of a Nox T3 Sleep Monitor. The simulation performance results showed that in terms of relative peak-valley amplitude of each breathing cycle, simulated bench airflow was biased by only 1.48% ± 6.80% compared to estimated polygraph nasal airflow for a total of 6,479 breathing cycles. For total respiratory cycle time, the average bias ± one standard deviation was 0.000 ± 0.288 seconds. For patient apnea events, our bench simulation had a sensitivity of 84.7% and a positive predictive value equal to 90.3%, considering 149 apneas detected both in polygraph nasal simulated bench airflows. Our new physiological bench would allow personalizing APAP device selection to each patient by taking into account individual characteristics of a sleep breathing profile.

Klíčová slova:

Acoustic signals – Algorithms – Breathing – Resistors – Respiratory physiology – Starlings – Apnea


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Článek vyšel v časopise

PLOS One


2019 Číslo 12