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Related Concept Videos

Respiratory Volumes01:15

Respiratory Volumes

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Respiratory volumes are crucial metrics, meticulously measured to quantify the air exchanged in and out of the lungs during various phases of the breathing cycle. These precise measurements are vital for assessing lung function, diagnosing respiratory conditions, and monitoring overall respiratory health. Each parameter provides specific insights into the mechanics of breathing and the functional capacity of the lungs.
Tidal Volume (TV) Tidal volume (TV) is the air inhaled or exhaled in a...
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Respiratory Volumes and Capacities01:22

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The respiratory system is responsible for the intake of oxygen and the expulsion of carbon dioxide from the body. Respiratory volumes describe the volume of air in the lungs at different phases of the respiratory cycle. Tidal volume is the air breathed in and out during normal, quiet breathing. Inspiratory reserve volume is the air that can be forcefully inspired beyond the tidal volume. In contrast, expiratory reserve volume refers to the air that can be expelled from the lungs after a normal...
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Respiratory Volumes and Capacities I01:26

Respiratory Volumes and Capacities I

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Assessing the respiratory rate and rhythm for a complete minute is crucial for evaluating the breathing pattern. Even a minor increase in the patient's average respiratory rate, by as little as three to five breaths per minute, is an early and vital indicator of respiratory distress. Patients with a respiratory rate exceeding twenty-four breaths per minute require close monitoring to determine the physiological alterations. This careful observation is essential for prompt recognition and...
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Neural Control of Respiration01:18

Neural Control of Respiration

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The neural regulation of respiration is a meticulously coordinated process primarily controlled by the respiratory centers located within the brainstem. These centers, composed of specialized neurons, transmit nerve impulses that control the contraction and relaxation of our respiratory muscles.
Respiratory Centers in the Brainstem
Two primary areas comprise the respiratory center: the medullary respiratory center in the medulla oblongata and the pontine respiratory group in the pons. The...
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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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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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Respiratory motion compensation with relevance vector machines.

Robert Dürichen1, Tobias Wissel2, Floris Ernst2

  • 1Institute of Robotics and Cognitive Systems, University of Lübeck, Germany. duerichen@rob.uni-luebeck.de

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|March 1, 2014
PubMed
Summary

A new algorithm using relevance vector machines (RVM) improves tumor motion prediction in robotic radiation therapy. Linear RVM significantly enhances accuracy, enabling real-time compensation for more effective cancer treatment.

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Area of Science:

  • Robotics
  • Medical Physics
  • Signal Processing

Background:

  • Respiration-induced tumor motion is a challenge in robotic radiation therapy.
  • Accurate prediction of tumor movement is crucial for effective treatment.
  • External optical surrogates are used to monitor tumor position.

Purpose of the Study:

  • To introduce and evaluate a novel algorithm for time series prediction of tumor motion.
  • To compare the performance of the proposed algorithm against existing methods.
  • To assess the feasibility of real-time prediction for robotic radiation therapy applications.

Main Methods:

  • Development of a relevance vector machine (RVM) based algorithm for motion prediction.
  • Evaluation of RVM with both linear and nonlinear basis functions.
  • Comparison with a wavelet-based least mean square (wLMS) algorithm using a dataset of 304 patient motion traces.

Main Results:

  • Linear RVM demonstrated significant improvement over the wLMS algorithm.
  • The RVM algorithm increased prediction accuracy for 80.3% of the patient data.
  • Real-time prediction was found to be feasible with the linear RVM approach.

Conclusions:

  • Relevance vector machines offer a superior method for predicting respiratory tumor motion in radiation therapy.
  • The proposed RVM algorithm enhances prediction accuracy and enables real-time compensation.
  • Predicted variance from RVM can be utilized to develop hybrid algorithms for further error reduction.