Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Sleep Apnea01:21

Sleep Apnea

836
Sleep apnea is a condition where breathing stops intermittently during sleep, often leading to significant health issues. Each episode can last from 10 to 20 seconds or more and is frequently accompanied by a brief arousal from sleep. This disturbance, largely unnoticed by the individual, can lead to severe daytime fatigue. Commonly, individuals seek help after being informed by their partners about loud snoring and noticeable breathing pauses during sleep.
The condition is more prevalent among...
836
Mechanical Ventilation III: Noninvasive Ventilation01:23

Mechanical Ventilation III: Noninvasive Ventilation

933
Noninvasive positive-pressure ventilation (NIPPV), continuous positive airway pressure (CPAP), and bilevel positive airway pressure (BiPAP) are essential methods in respiratory care. These ventilation techniques offer unique benefits for patients with various respiratory conditions, providing adequate support without requiring intubation. Let's explore how each method is crucial in improving patient outcomes and enhancing respiratory therapy.
Noninvasive Positive-Pressure Ventilation...
933
Neural Control of Respiration01:18

Neural Control of Respiration

6.1K
The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
6.1K
Ventilatory Modes01:14

Ventilatory Modes

2.2K
Mechanical ventilators are life-saving devices that support or replace spontaneous breathing. They deliver breaths to patients through varying methods known as ventilator modes. Understanding these modes is critical for healthcare providers managing patients with respiratory failure.
There are three ventilatory modes: full support, partial support, and spontaneous. These are described below.
Full Support Modes
Full support modes include controlled mechanical ventilation, continuous mandatory...
2.2K
Sleep-Wake Cycles01:24

Sleep-Wake Cycles

3.5K
Sleep is an essential physiological process vital to maintaining overall well-being. The reticular activating system (RAS), a network of neurons in the brainstem, regulates wakefulness and sleep. While it may seem passive, sleep consists of distinct cycles, each with its unique characteristics and functions. Two key sleep phases are non-rapid eye movement (NREM) and  rapid eye movement (REM).
NREM Sleep
NREM sleep comprises four progressive stages that seamlessly merge:
3.5K
Stages of Sleep01:22

Stages of Sleep

1.8K
Sleep progresses through distinct stages, each characterized by specific brain wave patterns and physiological responses ranging from wakefulness to stages of non-rapid eye movement, known as non-REM, to rapid eye movement, referred to as REM. Understanding these stages helps in recognizing how sleep supports various bodily and cognitive functions.
Before sleep begins, in wakefulness, the brain exhibits primarily beta waves, which are high in frequency and low in amplitude, indicating alertness...
1.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Sleep Stage Classification During CPAP Therapy from CPAP-Airflow and Wearable Fingertip Signals.

Sensors (Basel, Switzerland)·2026
Same author

External validation of a fingertip wearable device for obstructive sleep apnea diagnosis and split-night tracking of CPAP treatment response.

Sleep medicine·2026
Same author

Predicting sleep state from continuous positive airway pressure flow in patients with obstructive sleep apnea.

Sleep medicine·2026
Same author

Characterizing circadian rest-activity rhythm patterns across Alzheimer's disease continuum in Down syndrome.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Latent classes of sleep deficiency and correlates among patients receiving methadone treatment: A longitudinal study.

Addiction (Abingdon, England)·2026
Same author

Performance of an electroencephalography-measuring headband or actigraphy compared with polysomnography in older adults with sleep disturbances.

Sleep·2026

Related Experiment Video

Updated: Apr 18, 2026

Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

8.4K

Automatic sleep staging from CPAP airflow using a dual fusion multi-period convolutional neural network.

Hsin-Yu Chen1, Muneeb Ahsan2, Andrey V Zinchuk2

  • 1PranaQ Pte. Ltd., Singapore, Singapore.

Physiological Measurement
|April 16, 2026
PubMed
Summary

A new deep learning model, DFMP-CNN, enables unobtrusive sleep monitoring using Continuous Positive Airway Pressure (CPAP) devices. This dual-purpose platform enhances sleep therapy and assessment by analyzing CPAP-flow signals effectively.

Keywords:
ablation analysiscontinuous positive airway pressuredual fusion multi-period CNNhome sleep monitoringzero-shot cross-dataset transfer

Related Experiment Videos

Last Updated: Apr 18, 2026

Multi-Modal Home Sleep Monitoring in Older Adults
07:40

Multi-Modal Home Sleep Monitoring in Older Adults

Published on: January 26, 2019

8.4K

Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence in Medicine
  • Sleep Science

Background:

  • Continuous Positive Airway Pressure (CPAP) is standard for obstructive sleep apnea-hypopnea syndrome.
  • Repurposing CPAP devices for sleep dynamics monitoring is challenging due to signal artifacts and variability.
  • Existing CPAP devices primarily record airflow (CPAP-flow) signals, limiting their use beyond therapy.

Purpose of the Study:

  • To develop a novel deep learning model for passive sleep dynamics monitoring using CPAP devices.
  • To overcome limitations of traditional models in analyzing CPAP-flow signals for sleep staging.
  • To create a dual-purpose platform for both CPAP therapy and longitudinal sleep assessment.

Main Methods:

  • Introduced a Dual Fusion Multi-Period Convolutional Neural Network (DFMP-CNN) model.
  • Leveraged multiple period-specific convolutional kernels and a dual-fusion mechanism.
  • Encoded short- and long-range temporal dependencies within CPAP-flow signals.

Main Results:

  • DFMP-CNN achieved state-of-the-art performance in CPAP-based sleep staging.
  • Achieved 78.5% accuracy (κ=0.605) on the Yale dataset and 73.6% accuracy (κ=0.524) on the Duke dataset.
  • Demonstrated cross-dataset transferability across clinical centers and device types, highlighting robustness.

Conclusions:

  • DFMP-CNN offers an unobtrusive method for sleep monitoring via CPAP devices.
  • The model shows potential for improving clinical assessment and optimizing sleep therapy management.
  • This dual-purpose platform integrates therapy delivery with longitudinal sleep assessment capabilities.