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

Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

1.9K
Assessment of Ventilation
A Ventilation assessment is critical for monitoring a patient's health status. Respiration, one of the most accessible vital signs, provides insights into the function of numerous body systems and can indicate serious health issues, such as brainstem injuries from head trauma.
Critical Guidelines for Assessing Ventilation:
1.9K
Special considerations while measuring oxygen saturation01:19

Special considerations while measuring oxygen saturation

891
Assessing respiratory rate concurrently with pulse measurement is fundamental to patient care, providing valuable insights into the patient's respiratory function. The normal breathing rate for an adult usually falls within a normal range of 12 to 20 breaths per minute. Abnormal respiratory rates can signal underlying health conditions or the need for immediate intervention.
Ensuring accuracy in vital sign recordings while prioritizing patient comfort and minimizing anxiety is...
891
Respiratory Volumes and Capacities I01:26

Respiratory Volumes and Capacities I

1.6K
Assessing the respiratory rate and rhythm for a complete minute is crucial for evaluating the breathing pattern. Even a minor increase in the patient's average respiratory rate, by as little as three to five breaths per minute, is an early and vital indicator of respiratory distress. Patients with a respiratory rate exceeding twenty-four breaths per minute require close monitoring to determine the physiological alterations. This careful observation is essential for prompt recognition and...
1.6K
Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

Assessment of Ventilation II: Respiratory Depth and Rhythm

2.4K
Respiratory Depth
Respiratory depth measures the volume of air inhaled or exhaled during a breath. It can vary from shallow to deep and typically remains consistent when a person is at rest or asleep. Occasionally, individuals will automatically inhale deeply, known as sighing, which inflates the lungs with more air than normal breathing.
To assess respiratory depth, observe the degree of chest excursion or movement:
2.4K
Assessment of Airway, Skin Color, and Use of Accessory Muscles01:30

Assessment of Airway, Skin Color, and Use of Accessory Muscles

1.6K
A thorough assessment of respiratory health is paramount in clinical settings to identify and manage respiratory distress and ensure adequate oxygenation. This article elaborates on the critical aspects of respiratory evaluation, including airway assessment, skin color examination, and the observation of accessory muscle use, which are integral to effectively diagnosing and managing patients with respiratory conditions.
Introduction
The initial evaluation of a patient's respiratory system...
1.6K
Physical Assessment of the Respiratory Tract IV: Auscultation01:28

Physical Assessment of the Respiratory Tract IV: Auscultation

2.1K
Auscultation is a crucial component of the physical assessment of the respiratory tract. It offers valuable insights into airflow through the bronchial tree and potential lung obstructions. This process involves careful listening to breath, voice, and adventitious sounds, which can reveal a wealth of information about a patient's respiratory health.
Breath Sounds
Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
2.1K

You might also read

Related Articles

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

Sort by
Same author

Sustained Reduction in Cardiopulmonary Fitness in Long COVID: A Report from the RECOVER-adult Cohort Study.

JACC. Advances·2026
Same author

Patient communication during the emergency department visit: is text messaging preferred?

European journal of emergency medicine : official journal of the European Society for Emergency Medicine·2025
Same author

Introduction to special issue on acoustic cue-based perception and production of speech by humans and machines.

The Journal of the Acoustical Society of America·2025
Same author

Current use of push-dose epinephrine: Survey and interview results from academic clinicians in emergency medicine.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine·2025
Same author

Determining Correlations Between Emergency Department Health Care Workers and their Associated Burnout and Post-Traumatic Stress Disorder Scores: A Pilot Study.

Journal of emergency nursing·2024
Same author

Using articulatory feature detectors in progressive networks for multilingual low-resource phone recognitiona).

The Journal of the Acoustical Society of America·2024

Related Experiment Video

Updated: Jan 13, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

423

Multimodal Respiratory Rate Estimation From Audio and Video in Emergency Department Patients.

John Harvill1, Moitreya Chatterjee2, Shaveta Khosla3

  • 1Department of Electrical and Computer EngineeringUniversity of Illinois Urbana-Champaign (UIUC) Champaign IL 61801 USA.

IEEE Journal of Translational Engineering in Health and Medicine
|January 8, 2026
PubMed
Summary

Video-based estimation of respiratory rates offers more accurate remote patient monitoring than audio methods. This contactless vital sign measurement is crucial for reliable telehealth applications.

Keywords:
Audiomultimodalrespiratory rate estimationsignal processingvideo

More Related Videos

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

914
Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

8.3K

Related Experiment Videos

Last Updated: Jan 13, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

423
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

914
Conducting Respiratory Oscillometry in an Outpatient Setting
14:49

Conducting Respiratory Oscillometry in an Outpatient Setting

Published on: April 8, 2022

8.3K

Area of Science:

  • Biomedical Engineering
  • Medical Signal Processing
  • Remote Patient Monitoring

Background:

  • The COVID-19 pandemic accelerated the need for reliable remote medical care solutions.
  • Smartphones enable interest in estimating patient vital signs using audio or video signals.
  • Contactless vital sign monitoring is essential for remote and efficient healthcare delivery.

Purpose of the Study:

  • To estimate and compare respiratory rates using video, audio, and combined audio-video signals.
  • To evaluate the accuracy of different methods for respiratory rate estimation in emergency department patients.

Main Methods:

  • Video-based respiratory rate estimation utilized signal processing techniques.
  • Audio-based respiratory rate estimation compared signal processing and learning-based methods.
  • Respiratory rate estimation was performed on a collected audio-video corpus and a public audio corpus.

Main Results:

  • The best Mean Absolute Error (MAE) achieved was 2.53 using video features on the collected corpus.
  • On the public respiratory rate corpus, signal processing methods yielded an MAE of 1.63.
  • Video modality demonstrated superior accuracy in estimating respiratory rates compared to audio modality.

Conclusions:

  • Video-based estimation provides more accurate respiratory rate readings than audio-based methods for clinical data.
  • Contactless vital sign estimation via video or audio is significant for remote healthcare.
  • This technology eliminates the need for extra measurement equipment, enhancing patient comfort and accessibility.