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Related Concept Videos

Respiratory System Abnormal Finding II: Palpation and Auscultation01:31

Respiratory System Abnormal Finding II: Palpation and Auscultation

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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.
Palpation Findings
During a respiratory assessment, palpation can reveal several vital abnormalities:
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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.
Breath Sounds
Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
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Assessment of Ventilation II: Respiratory Depth and Rhythm01:29

Assessment of Ventilation II: Respiratory Depth and Rhythm

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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.
To assess respiratory depth, observe the degree of chest excursion or movement:
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Respiratory System Abnormal Finding I: Inspection and Percussion01:30

Respiratory System Abnormal Finding I: Inspection and Percussion

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Respiratory system abnormalities are a significant concern in healthcare due to their potential to indicate underlying severe conditions like Chronic Obstructive Pulmonary Disease (COPD), asthma, and pneumonia. These abnormalities can often be detected through physical examination methods like inspection and percussion.
Inspection Findings
During an inspection, several findings may suggest the presence of respiratory distress or disease. Pursed-lip breathing, where exhalation is slowed by...
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Assessment of Respiration01:23

Assessment of Respiration

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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.
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...
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Assessment of Ventilation I: Respiratory Rate01:20

Assessment of Ventilation I: Respiratory Rate

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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:
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Related Experiment Video

Updated: Dec 30, 2025

A Protocol for Comprehensive Assessment of Bulbar Dysfunction in Amyotrophic Lateral Sclerosis ALS
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A Novel Stuttering Disfluency Classification System Based on Respiratory Biosignals.

Bruno Villegas, Kevin M Flores, Kevin Jose Acuna

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |January 18, 2020
    PubMed
    Summary

    This study developed a system using respiratory biosignals to automatically classify stuttering events in adults who stutter (AWS). The system achieved 82.6% accuracy, showing promise for stuttering assessment and interventions.

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    Area of Science:

    • Speech-Language Pathology
    • Biomedical Engineering
    • Computational Linguistics

    Background:

    • Stuttering is a prevalent fluency disorder impacting quality of life for adults who stutter (AWS).
    • Accurate assessment of stuttering severity is crucial for effective therapeutic management.
    • Respiratory biosignals offer a potential, yet under-evidenced, avenue for automatic stuttering assessment.

    Purpose of the Study:

    • To develop and validate a classification system for stuttering disfluencies using respiratory biosignals.
    • To differentiate between block and non-block stuttering states based on respiratory patterns.
    • To explore the feasibility of using respiratory data for automated stuttering analysis.

    Main Methods:

    • Sixty-eight participants (adults who stutter (AWS) and adults who do not stutter (AWNS)) performed a reading task.
    • Respiratory patterns and pulse were recorded using a standardized system.
    • A Multilayer Perceptron Neural Network (MLP) was employed for classification after segmentation and feature extraction.

    Main Results:

    • The developed system achieved an 82.6% classification accuracy in differentiating block and non-block states.
    • Respiratory biosignal analysis demonstrated effectiveness in classifying stuttering events during reading tasks.
    • The system successfully distinguished between stuttered and non-stuttered speech segments.

    Conclusions:

    • The study presents an accurate system for classifying stuttering states from respiratory biosignals in adults who stutter (AWS).
    • This technology shows significant promise for future applications in stuttering screening, monitoring, and biofeedback interventions.
    • Respiratory biosignal analysis represents a viable approach for objective stuttering assessment.