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Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

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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.
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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.
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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.
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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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Operatic Singing Biomechanics: Skeletal Tracking Sensor Integration for Pedagogical Innovation.

Sensors (Basel, Switzerland)·2025
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Asthma Detection Research Based on Voice Signal Processing and Machine Learning
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Towards a Singing Voice Multi-Sensor Analysis Tool: System Design, and Assessment Based on Vocal Breathiness.

Evangelos Angelakis1, Natalia Kotsani1, Anastasia Georgaki1

  • 1Laboratory of Music Acoustics and Technology (LabMAT), Music Studies Department, National and Kapodistrian University of Athens, 15784 Athens, Greece.

Sensors (Basel, Switzerland)
|December 10, 2021
PubMed
Summary

This study introduces a new multi-sensor system for analyzing singing voice, finding it practical for assessing vocal breathiness. The system shows promising correlations between acoustic and physiological data and perceptual ratings.

Keywords:
biomedical signal acquisitionbreathinessdata processingelectroglottographyfundamental frequency estimationrespiratory transducersinging voicevocal mechanism

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Area of Science:

  • Acoustic and physiological analysis of singing voice.
  • Development of multi-sensor systems for vocal analysis.

Background:

  • Singing voice relies on complex kinetic functions, producing variable auditory outcomes.
  • Understanding vocal mechanism function is crucial for vocal education, rehabilitation, and health.
  • Multi-sensor systems can reveal correlations between vocal function and voice output.

Purpose of the Study:

  • To present the initial design of a modular multi-sensor system for singing voice analysis.
  • To assess the system's effectiveness in analyzing 'vocal breathiness'.
  • To explore correlations between sensor data and perceptual breathiness ratings.

Main Methods:

  • A case study with two professional singers using a modular multi-sensor system.
  • Sensors included a condenser microphone (CM), Electroglottograph (EGG), and respiratory effort transducers (RET).
  • Analysis involved correlating perceptual breathiness ratings with parameters like Smoothed Cepstral Peak Prominence (CPPS) and Open Quotient (OQ) from CM and EGG data, and evaluating multi-variate models (ABI, CDH).

Main Results:

  • Smoothed Cepstral Peak Prominence (CPPS) and vocal folds' Open Quotient (OQ) showed significant individual correlations with breathiness.
  • A combined model (ABI and CDH) yielded the highest correlation with perceptual breathiness ratings.
  • The system demonstrated practicality and identified relevant correlations for vocal analysis.

Conclusions:

  • The developed multi-sensor system is a practical tool for singing voice analysis, particularly for breathiness assessment.
  • The system shows potential for application in vocal pedagogy and research.
  • Further investigation with larger populations is warranted for certain findings, such as pitch difference correlations.