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

Learning Disabilities01:25

Learning Disabilities

466
Learning disabilities are cognitive disorders caused by neurological impairments that affect cognitive functions like language and reading, without indicating overall intellectual or developmental challenges. These disabilities differ from global intellectual or developmental disabilities as they are limited to distinct cognitive functions. Common learning disabilities include dysgraphia, dyslexia, and dyscalculia, each of which impacts unique aspects of learning.
Dyslexia
Dyslexia is a...
466
Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

673
Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
673

You might also read

Related Articles

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

Sort by
Same author

Development of a small mobilizable plasmid system: A foundation for genetic engineering of Bacillus subtilis strains.

The Journal of general and applied microbiology·2026
Same author

Contrast-enhanced ultrasound findings are associated with tumor viability and depth of response in selected patients with unresectable hepatocellular carcinoma treated with immunotherapy-based combination therapy.

Journal of medical ultrasonics (2001)·2026
Same author

Biotin Dependency Shapes Sporulation Kinetics in Bacillus subtilis var. natto.

The Journal of general and applied microbiology·2026
Same author

A novel humanized FIX/FX hemophilia A mouse model for preclinical evaluation of FVIIIa-mimetic bispecific antibodies.

Blood advances·2026
Same author

Electrocardiographic Characteristics Associated With Lead Position Variations in Left Bundle Branch Area Pacing.

Pacing and clinical electrophysiology : PACE·2026
Same author

Giant surface potentials in organic films enable electrode-free self-driven water droplets.

Materials horizons·2026

Related Experiment Video

Updated: Dec 6, 2025

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

743

A wheeze recognition algorithm for practical implementation in children.

Chizu Habukawa1, Naoto Ohgami2, Naoki Matsumoto3

  • 1Department of Paediatrics, Minami Wakayama Medical Center, Wakayama, Japan.

Plos One
|October 8, 2020
PubMed
Summary
This summary is machine-generated.

A new algorithm accurately detects wheezes in children, aiding respiratory illness management. This automated wheeze detection shows high sensitivity and specificity, proving useful for home-based monitoring devices.

More Related Videos

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
09:24

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

Published on: May 17, 2024

1.9K
Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
14:05

Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

Published on: January 23, 2017

29.5K

Related Experiment Videos

Last Updated: Dec 6, 2025

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

743
Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable
09:24

Quantified Assessment of Infant's Gross Motor Abilities Using a Multisensor Wearable

Published on: May 17, 2024

1.9K
Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses
14:05

Behavioral Assessment of Hearing in 2 to 4 Year-old Children: A Two-interval, Observer-based Procedure Using Conditioned Play-based Responses

Published on: January 23, 2017

29.5K

Area of Science:

  • Pediatric Pulmonology
  • Medical Device Technology
  • Computational Health

Background:

  • Wheeze detection is crucial for managing respiratory diseases in children.
  • Current clinical methods for automatic wheeze detection in children lack high accuracy.
  • There is a need for practical, automated solutions for wheeze detection in pediatric respiratory care.

Purpose of the Study:

  • To develop and evaluate a novel algorithm for automatic wheeze detection in children.
  • To assess the algorithm's accuracy and reliability compared to specialist physician assessments.
  • To determine the algorithm's suitability for practical implementation in pediatric respiratory illness management.

Main Methods:

  • Developed a wheeze recognition algorithm based on established Computerized Respiratory Sound Analysis guidelines.
  • Recorded 30-second lung sound samples from 214 children (2 months to 12 years) in a pediatric setting.
  • Compared algorithm's wheeze detection performance against consensus diagnoses from two specialist physicians, calculating sensitivity, specificity, PPV, and NPV.

Main Results:

  • The wheeze recognition algorithm demonstrated high performance across all tested sound files.
  • Achieved sensitivity of 100%, specificity of 95.7%, positive predictive value (PPV) of 90.3%, and negative predictive value (NPV) of 100%.
  • Age did not significantly influence the algorithm's wheeze detection sensitivity.

Conclusions:

  • The developed wheeze recognition algorithm effectively differentiates wheezes from noise in pediatric lung sound recordings.
  • The algorithm's high accuracy suggests its potential utility in home-based respiratory illness management devices.
  • This technology could enhance remote monitoring and early intervention for respiratory conditions in children.