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Related Concept Videos

Physical Assessment of the Respiratory Tract IV: Auscultation01:28

Physical Assessment of the Respiratory Tract IV: Auscultation

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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.
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Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
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Physical Assessment of the Respiratory Tract III: Percussion01:29

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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.
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Perceiving Loudness, Pitch, and Location01:21

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The human brain perceives pitch through two primary mechanisms reflected in place theory and frequency theory. Each mechanism describes how sound waves are interpreted as specific pitches by the brain, offering insights into the intricate processes of auditory perception.
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Respiratory System Abnormal Finding II: Palpation and Auscultation01:31

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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.
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Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

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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.
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Physical Assessment of the Respiratory Tract II: Palpation01:24

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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.
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Creak Derived from CAPE-V Sentences in Patients with AdLd and pMTD.

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Rehabilitation Treatment Specification System: Reliability and Dosage of Common Ingredients in Standard-of-Care Therapy for Vocal Hyperfunction.

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Characterizing Vocal Hyperfunction Using Ecological Momentary Assessment of Relative Fundamental Frequency.

Ahsan J Cheema1, Katherine L Marks2, Hamzeh Ghasemzadeh3

  • 1Speech and Hearing Bioscience and Technology Program, Harvard University, 25 Shattuck St, Boston 02115, Massachusetts; Harvard Medical School, 25 Shattuck St, Boston 02115, Massachusetts; Mass General Hospital (MGH) Voice Center, 1 Bowdoin Sq, Boston 02114, Massachusetts; Eaton-Peabody Laboratories, Massachusetts Eye and Ear, 243 Charles St, Boston 02114, Massachusetts.

Journal of Voice : Official Journal of the Voice Foundation
|December 15, 2024
PubMed
Summary

This study shows relative fundamental frequency (RFF) can identify vocal hyperfunction (VH) in daily life using smartphone sensors. RFF analysis accurately classified vocal hyperfunction in natural settings, offering a new biomarker for voice disorders.

Keywords:
Relative fundamental frequency—Vocal hyperfunction—Phonotraumatic vocal hyperfunction—Nonphonotraumatic vocal hyperfunction—Vocal effort—Machine learning—Random forest

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Area of Science:

  • Speech and Hearing Sciences
  • Biomedical Engineering
  • Computational Linguistics

Background:

  • Vocal hyperfunction (VH) is linked to common voice disorders, including those causing vocal fold lesions and muscle tension dysphonia.
  • Relative fundamental frequency (RFF) during voice onsets/offsets relates to vocal fold tension and differentiates VH from typical voices in labs.

Purpose of the Study:

  • To assess if RFF's sensitivity to VH persists in naturalistic, in-field settings.
  • To explore ecological momentary assessment of RFF as a correlate of self-reported vocal effort.
  • To apply machine learning for classifying VH using RFF data.

Main Methods:

  • Smartphone-based monitoring of anterior neck-surface vibration using accelerometers in lab and field settings.
  • Supervised machine learning algorithms to combine RFF values for VH classification.
  • Explainability techniques to identify clinically relevant RFF features.

Main Results:

  • RFF-based classification of VH maintained accuracy in naturalistic environments: 81.3% for phonotraumatic VH and 62.5% for nonphonotraumatic VH.
  • Explainability analysis revealed key RFF features for VH classification.
  • No significant correlation was found between RFF and self-reported vocal effort.

Conclusions:

  • Relative fundamental frequency (RFF) shows potential as a biomarker for vocal hyperfunction (VH) in real-world settings.
  • Machine learning integration with RFF monitoring could enable proactive screening and biofeedback voice therapy.
  • Further research can refine RFF analysis for clinical application in voice disorder management.