Estimation of the respiratory rate from ballistocardiograms using the Hilbert transform

Biomed Eng Online. 2022 Aug 4;21(1):54. doi: 10.1186/s12938-022-01024-4.

Abstract

Background: Measuring the respiratory rate is usually associated with discomfort for the patient due to contact sensors or a high time demand for healthcare personnel manually counting it.

Methods: In this paper, two methods for the continuous extraction of the respiratory rate from unobtrusive ballistocardiography signals are introduced. The Hilbert transform is used to generate an amplitude-invariant phase signal in-line with the respiratory rate. The respiratory rate can then be estimated, first, by using a simple peak detection, and second, by differentiation.

Results: By analysis of a sleep laboratory data set consisting of nine records of healthy individuals lasting more than 63 h and including more than 59,000 breaths, a mean absolute error of as low as 0.7 BPM for both methods was achieved.

Conclusion: The results encourage further assessment for hospitalised patients and for home-care applications especially with patients suffering from diseases of the respiratory system like COPD or sleep apnoea.

Keywords: Ballistocardiography; Instantaneous breathing frequency; Respiration.

MeSH terms

  • Algorithms
  • Ballistocardiography* / methods
  • Heart Rate
  • Humans
  • Respiration
  • Respiratory Rate
  • Signal Processing, Computer-Assisted
  • Sleep Apnea Syndromes* / diagnosis