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Related Concept Videos

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
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Related Experiment Video

Updated: Feb 7, 2026

Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments
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Extreme value analysis has the potential to improve spirometry interpretation.

Brian L Graham1, Sanja Stanojevic2

  • 1Respiratory Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada brian.graham@usask.ca.

Thorax
|February 5, 2026
PubMed
Summary
This summary is machine-generated.

Lung function impairment may not follow a typical Gaussian distribution. Extreme value analysis using a Gumbel distribution offers a more objective way to differentiate healthy versus impaired lung function.

Keywords:
Respiratory Function Tests

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Area of Science:

  • Pulmonary Medicine
  • Biostatistics
  • Respiratory Physiology

Background:

  • Spirometry is crucial for diagnosing and managing respiratory diseases.
  • Interpretation often assumes healthy lung function follows a Gaussian distribution.
  • This assumption may not accurately reflect impaired lung function.

Purpose of the Study:

  • To investigate if lung function impairment follows a non-Gaussian distribution.
  • To apply extreme value analysis for modeling impaired lung function.
  • To develop a more objective method for interpreting spirometry results.

Main Methods:

  • Hypothesized non-Gaussian distribution for impaired lung function.
  • Utilized Gumbel distribution to model lung function impairment.
  • Calculated relative probability comparing healthy (Gaussian) and impaired (Gumbel) distributions.

Main Results:

  • Demonstrated the utility of relative probability in simulated cases.
  • Provided objective delineation of the uncertainty zone between normal and impaired function.
  • Showcased a more analytic assessment of lung function impairment.

Conclusions:

  • Treating impaired lung function as a separate distribution improves assessment.
  • Extreme value analysis and relative probability offer objective discrimination.
  • A more precise definition of the uncertainty zone enhances interpretation accuracy.