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Assessment of Ventilation I: Respiratory Rate

Assessment of Ventilation I: Respiratory Rate

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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Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
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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.
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Assessment of Ventilation II: Respiratory Depth and Rhythm

Assessment of Ventilation II: Respiratory Depth and Rhythm

Respiratory Depth
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Correction: Vitazkova et al. Transforming Sleep Monitoring: Review of Wearable and Remote Devices Advancing Home Polysomnography and Their Role in Predicting Neurological Disorders. <i>Biosensors</i> 2025, <i>15</i>, 117.

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Updated: Jun 26, 2026

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

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

Published on: May 17, 2024

Respiratory Monitoring in Motion: An Overview of Wearable Methods and Algorithmic Approaches for Reliable Assessment.

Michal Pecik¹, Erik Vavrinsky¹, Diana Vitazkova¹

¹Institute of Electronics and Photonics, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovicova 3, 81219 Bratislava, Slovakia.

|June 25, 2026

Summary

Wearable sensors offer advanced respiratory monitoring during physical activity. This review examines methods for accurate respiratory rate and tidal volume tracking, addressing challenges in dynamic environments.

Keywords:

chest wall motion derived respiration motion robustness respiration sensor fusion wearable

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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

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Published on: December 11, 2015

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Last Updated: Jun 26, 2026

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

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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Area of Science:

Biomedical Engineering
Physiological Monitoring
Wearable Technology

Background:

Respiratory monitoring is transitioning from clinical settings to real-world applications using wearable devices.
Accurate diagnostics are enabled by these technologies, but challenges remain during dynamic activities due to motion artifacts and signal variability.
Reliable respiratory monitoring during strenuous physical exertion is crucial for health and performance assessment.

Purpose of the Study:

To review wearable methodologies for determining respiratory rate and tidal volume during strenuous physical activities.
To analyze signal processing, machine learning, and sensor fusion algorithms enhancing monitoring robustness.
To identify emerging trends and guide the development of next-generation adaptive respiratory monitoring systems.

Main Methods:

Review of direct sensing approaches (chest/abdominal belts, bioimpedance, inertial sensors).
Analysis of indirect methods using electrocardiogram (ECG) and photoplethysmogram (PPG) signals.
Discussion of hybrid systems and advanced algorithms (signal processing, machine learning, sensor fusion).

Main Results:

Wearable sensors show promise for respiratory monitoring during dynamic activities.
Signal processing and sensor fusion techniques are key to overcoming motion artifacts and improving reliability.
Hybrid systems offer a promising avenue for robust respiratory monitoring.

Conclusions:

Wearable technology is advancing respiratory monitoring capabilities for real-world, dynamic conditions.
Further development in adaptive algorithms and multimodal sensor fusion is needed for next-generation systems.
This review provides insights into hardware-software combinations, validation, and limitations in wearable respiratory monitoring.