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

Physical Assessment of the Respiratory Tract IV: Auscultation01:28

Physical Assessment of the Respiratory Tract IV: Auscultation

3.7K
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.
3.7K
Respiratory System Abnormal Finding II: Palpation and Auscultation01:31

Respiratory System Abnormal Finding II: Palpation and Auscultation

2.1K
In assessing respiratory abnormalities, palpation and auscultation are critical tools for detecting and interpreting various pathophysiological changes. These techniques provide insight into underlying disorders by evaluating tactile sensations and sounds produced by the respiratory system.
Palpation Findings
During a respiratory assessment, palpation can reveal several vital abnormalities:
2.1K
Trachea01:22

Trachea

6.5K
The trachea, commonly known as the windpipe, is a vital part of the human respiratory system. It serves as a passageway for air to travel between the larynx and the bronchi, allowing oxygen to reach the lungs. Let's explore its anatomical features, dimensions, layers of the tracheal wall, associated muscles, and the functions of its parts.
Anatomical Features:
Location: About half of the trachea is situated in the neck, anterior to the esophagus, and extends from the larynx (at the level of...
6.5K
Assessment of Respiration01:23

Assessment of Respiration

2.5K
The respiratory system's basic structures and primary functions lay the foundation for nurses' comprehensive respiratory assessments. This assessment includes subjective and objective data to gauge the patient's respiratory health.
Subjective Assessment: Nurses interview the patient to gather information directly during the subjective assessment. It includes questions about the individual's medical history, medications, and symptoms, focusing on past respiratory conditions like...
2.5K
Physical Assessment of the Respiratory Tract II: Palpation01:24

Physical Assessment of the Respiratory Tract II: Palpation

3.1K
Physical assessment of the respiratory tract is critical in identifying potential health issues. One key component of this assessment is palpation, a technique healthcare providers use to assess the body for abnormalities. This content explores the method of palpation in evaluating the respiratory tract, focusing on thoracic palpation and tactile fremitus.
Thoracic Palpation
Thoracic palpation detects tenderness, masses, lesions, respiratory excursions, and vocal fremitus. The nurse assesses...
3.1K
Physical Assessment of the Respiratory Tract III: Percussion01:29

Physical Assessment of the Respiratory Tract III: Percussion

4.8K
The respiratory system, fundamental to life, consists of complex structures responsible for gas exchange. The percussion assessment is critical to understanding this system's health and functionality. This non-invasive assessment technique allows healthcare providers to evaluate the density or aeration of the lungs, thereby identifying potential abnormalities.
Percussion in Respiratory Assessment
Percussion evaluates underlying tissue composition with audible and tactile vibrations,...
4.8K

You might also read

Related Articles

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

Sort by
Same author

An Adaptive Element-Level Impedance-Matched ASIC With Improved Acoustic Reflectivity for Medical Ultrasound Imaging.

IEEE transactions on biomedical circuits and systems·2022
Same author

Design and Preliminary Evaluation of a Tongue-Operated Exoskeleton System for Upper Limb Rehabilitation.

International journal of environmental research and public health·2021
Same author

Supply-Inverted Bipolar Pulser and Tx/Rx Switch for CMUTs Above the Process Limit for High Pressure Pulse Generation.

IEEE sensors journal·2021
Same author

A Trimodal Wireless Implantable Neural Interface System-on-Chip.

IEEE transactions on biomedical circuits and systems·2020
Same author

A Power-Efficient Bridge Readout Circuit for Implantable, Wearable, and IoT Applications.

IEEE sensors journal·2020
Same author

A mm-Sized Free-Floating Wireless Implantable Opto-Electro Stimulation Device.

Micromachines·2020

Related Experiment Video

Updated: Apr 18, 2026

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

1.3K

Tracheal activity recognition based on acoustic signals.

Temiloluwa Olubanjo, Maysam Ghovanloo

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 9, 2015
    PubMed
    Summary

    Neck-worn sensors can recognize tracheal activities for continuous health monitoring. This research achieved high accuracy (86.6%-87.4%) for various activities and excellent speech recognition (97.2%-99.4%) using simple classifiers.

    More Related Videos

    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

    720
    Image Acquisition using Portable Sonography for Emergency Airway Management
    07:31

    Image Acquisition using Portable Sonography for Emergency Airway Management

    Published on: September 28, 2022

    3.2K

    Related Experiment Videos

    Last Updated: Apr 18, 2026

    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

    1.3K
    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

    720
    Image Acquisition using Portable Sonography for Emergency Airway Management
    07:31

    Image Acquisition using Portable Sonography for Emergency Airway Management

    Published on: September 28, 2022

    3.2K

    Area of Science:

    • Biomedical Engineering
    • Wearable Technology
    • Health Monitoring

    Background:

    • Neck-worn systems offer unique physiological data acquisition capabilities for personalized healthcare.
    • Tracheal activity recognition is crucial for continuous health monitoring and advanced wearable systems.
    • Existing methods may not fully leverage the rich data available from the neck region.

    Purpose of the Study:

    • To explore tracheal activity recognition using acoustic features and simple classifiers.
    • To evaluate the performance of K-Nearest Neighbors (KNN) and Naive Bayes classifiers for tracheal activity classification.
    • To assess the feasibility of low-power, sub-optimal sampling rates for wearable health monitoring.

    Main Methods:

    • Utilized promising acoustic features from existing research.
    • Applied K-Nearest Neighbors (1-NN, 3-NN, 5-NN) and Naive Bayes classifiers.
    • Employed a sub-optimal sampling rate of 16 kHz to address power consumption concerns in wearable systems.

    Main Results:

    • Achieved average classification accuracies ranging from 86.6% to 87.4% for various tracheal activities.
    • Demonstrated high recognition rates between 97.2% and 99.4% specifically for speech classification.
    • Validated the effectiveness of simple classifiers even with reduced sampling rates.

    Conclusions:

    • Tracheal activity recognition is feasible and effective using neck-worn sensors and basic machine learning algorithms.
    • The developed system shows promise for privacy-preserving health monitoring by accurately identifying speech.
    • Low sampling rates can be utilized without significantly compromising classification performance, supporting low-power wearable applications.