APAP, BPAP, CPAP, and New Modes of Positive Airway Pressure Therapy

Johnson, Karin G.

doi:10.1007/978-3-031-06413-5_18

Cited by 9 publications

(5 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…APAP devices are the most complex, with automatic PEEP adjustments performed on a breath-by-breath basis from additional inline and auditory sensor measurements to detect periods without breathing [18] . Adjustments between clinician-set boundaries of 4–20 cmH2O are performed through algorithms based on the detection of inspiratory flow limitation, snoring, apnea events, and obstructive pressure in device sensor measurements [12] . These algorithms are normally based on average male breathing patterns, with limited information provided to researchers on how they function, impeding evaluation and usefulness outside of the set demographic.…”

Section: Hardware In Contextmentioning

confidence: 99%

Design, manufacture, and control of a low-cost positive airway pressure device

Hill,

Jackson,

Uluilelata

et al. 2024

HardwareX

View full text Add to dashboard Cite

Section: Hardware In Contextmentioning

confidence: 99%

Design, manufacture, and control of a low-cost positive airway pressure device

Hill,

Jackson,

Uluilelata

et al. 2024

HardwareX

View full text Add to dashboard Cite

“…The control variables are usually pressure and volume. However, there are special cases, such as hybrid modes (average volume-assured pressure support -AVAPS-or intelligent volume-assured pressure support-iVAPS-) in which the control variable (pressure) is modified in a predetermined pressure range depending on the estimation of a parameter (tidal volume), see Section 3 [9]. Thus, ventilatory modes can be categorized into volume-targeted ventilation and pressure-targeted ventilation [10].…”

Section: Overview Of Ventilatory Modes and Settingsmentioning

confidence: 99%

“…In most models, the transition criterion from inspiration to expiration is time, although some manufacturers maintain the flow criterion for both assisted and controlled breaths. Finally, some hybrid modes, such iVAPS and AVAPS have auto backup rates with iVAPS targeting 2/3 of the set rate and increasing during central apnea and AVAPS based on recent breathing patterns (only in automatic mode) [9].…”

Section: Backup Respiratory Rate (Burr)mentioning

confidence: 99%

“…These criteria are a percentage of peak (maximum) flow in pressure support mode and a fixed inspiratory time in pressure control mode. In PS mode, an expiratory trigger can be set directly as a percentage of peak inspiratory flow or in a numerical (1)(2)(3)(4)(5)(6)(7)(8)(9) or nominal scale (sensitive, medium, low sensitive) depending on the manufacturer. In the first case (direct setting of the percentage of peak flow) it is usually set high if a short inspiratory time is desired (e.g., in COPD patients, where a short inspiratory time/total time ratio is desirable) and lower if a longer inspiratory time is desired (e.g., in restrictive patients).…”

Section: Cycling To Expirationmentioning

confidence: 99%

See 1 more Smart Citation

Ventilators, Settings, Autotitration Algorithms

Luján

Lalmolda²

2023

JCM

View full text Add to dashboard Cite

The choice of a ventilator model for a single patient is usually based on parameters such as size (portability), presence or absence of battery and ventilatory modes. However, there are many details within each ventilator model about triggering, pressurisation or autotitration algorithms that may go unnoticed, but may be important or may justify some drawbacks that may occur during their use in individual patients. This review is intended to emphasize these differences. Guidance is also provided on the operation of autotitration algorithms, in which the ventilator is able to take decisions based on a measured or estimated parameter. It is important to know how they work and their potential sources of error. Current evidence on their use is also provided.

show abstract

“…Positive airway pressure (PAP) is the primary treatment for OSA. It provides a positive airflow to the upper airway to prevent airway collapse and obstruction, thereby improving respiratory events, sleep quality, and quality of life [7]. To improve treatment compliance and effectiveness, in addition to the original continuous PAP (CPAP), more PAP therapy modes have been developed, including automatic titration CPAP and bi-level PAP.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Sleep Apnea Events Using a CNN–Transformer Network and Contactless Breathing Vibration Signals

Chen

Yang

et al. 2023

Bioengineering

View full text Add to dashboard Cite

It is estimated that globally 425 million subjects have moderate to severe obstructive sleep apnea (OSA). The accurate prediction of sleep apnea events can offer insight into the development of treatment therapies. However, research related to this prediction is currently limited. We developed a covert framework for the prediction of sleep apnea events based on low-frequency breathing-induced vibrations obtained from piezoelectric sensors. A CNN-transformer network was utilized to efficiently extract local and global features from respiratory vibration signals for accurate prediction. Our study involved overnight recordings of 105 subjects. In five-fold cross-validation, we achieved an accuracy of 85.9% and an F1 score of 85.8%, which are 3.5% and 5.3% higher than the best-performed classical model, respectively. Additionally, in leave-one-out cross-validation, 2.3% and 3.8% improvements are observed, respectively. Our proposed CNN-transformer model is effective in the prediction of sleep apnea events. Our framework can thus provide a new perspective for improving OSA treatment modes and clinical management.

show abstract

APAP, BPAP, CPAP, and New Modes of Positive Airway Pressure Therapy

Cited by 9 publications

References 77 publications

Design, manufacture, and control of a low-cost positive airway pressure device

Design, manufacture, and control of a low-cost positive airway pressure device

Ventilators, Settings, Autotitration Algorithms

Prediction of Sleep Apnea Events Using a CNN–Transformer Network and Contactless Breathing Vibration Signals

Contact Info

Product

Resources

About