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Reliable respiratory rate estimation from a bed pressure array.

Megam Howell Jones1, Rafik Goubran, Frank Knoefel

  • 1Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, Ont., Canada. mhowellj@sce.carleton.ca

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
|October 20, 2007
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This study presents a novel method for reliable respiratory rate estimation in older adults using bed sensors. The system effectively suppresses movement artifacts, enhancing monitoring accuracy for at-home sleep analysis.

Area of Science:

  • Biomedical Engineering
  • Sleep Science
  • Gerontology

Background:

  • Continuous sleep monitoring is crucial for older adults living independently.
  • Accurate respiratory rate estimation is a key indicator of sleep health.
  • Existing methods can be intrusive or affected by movement artifacts.

Purpose of the Study:

  • To develop and validate a reliable method for estimating respiratory rate in older adults using unobtrusive, bed-based pressure sensors.
  • To improve the accuracy and validity of respiratory rate estimation by detecting and suppressing movement artifacts.
  • To introduce a reliability metric for assessing the quality of respiratory rate estimates.

Main Methods:

  • Utilized a bed-based pressure sensor array for unobtrusive sleep monitoring.

Related Experiment Videos

  • Implemented a novel algorithm to detect and suppress movement artifacts before respiratory rate estimation.
  • Developed a reliability metric, scored out of 100, based on movement during estimation and data weighting.
  • Analyzed nocturnal data from human participants, comparing methods with and without movement suppression and data fusion.

    • Main Results:

    • The proposed method demonstrated superior accuracy and validity compared to analyses without movement suppression or postprocessing data fusion.
    • While over 50% of estimates initially contained movement corruption, only 15% were deemed unreliable.
    • Removal of unreliable estimates significantly reduced the variance of respiratory rate measurements and improved validity.

    Conclusions:

    • The developed method provides a reliable and unobtrusive approach for estimating respiratory rate in older adults during sleep.
    • The integrated reliability metric effectively identifies and allows for the exclusion of corrupted data, enhancing overall monitoring quality.
    • This technology holds promise for improved remote sleep health assessment in geriatric populations.