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Sensor Selection for Tidal Volume Determination via Linear Regression-Impact of Lasso versus Ridge Regression.

Bernhard Laufer1, Paul D Docherty1,2, Rua Murray3

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This study optimized smart shirt sensor placement for respiratory volume measurement using regression analysis. The Lasso method proved more effective than Ridge regression, enabling convenient respiratory monitoring.

Keywords:
LassoRidge regressionlinear regressionsensor selectionsmart clothingtidal volumewearables

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Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Respiratory Physiology

Background:

  • Respiratory volume measurement is crucial for medical diagnostics and monitoring.
  • Traditional spirometry can be inconvenient, especially in home care or hospital settings.
  • Smart shirts offer a potential non-invasive alternative for respiratory monitoring.

Purpose of the Study:

  • To determine optimal sensor selection and placement on a smart shirt for accurate respiratory volume estimation.
  • To compare the efficacy of Ridge regression and Lasso regression methods for sensor optimization.
  • To assess the feasibility of using a smart shirt to replace or supplement spirometry.

Main Methods:

  • Utilized upper body surface motion data captured by a motion capture system.
  • Applied Ridge regression and Least Absolute Shrinkage and Selection Operator (Lasso) regression techniques.
  • Compared sensor subset selection and performance between the two regression methods.

Main Results:

  • Lasso regression demonstrated advantages over Ridge regression, offering sparse solutions and improved robustness to outliers.
  • Both methods identified similar sensor subsets, reducing computational demand significantly compared to exhaustive search.
  • The optimized sensor placement on a smart shirt can recover respiratory parameters accurately.

Conclusions:

  • A smart shirt equipped with optimally placed sensors can provide a convenient and accurate method for respiratory volume estimation.
  • The Lasso regression method is advantageous for smart shirt sensor optimization in respiratory monitoring.
  • This technology holds promise for replacing spirometry in certain clinical and home-care scenarios.