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Estimation of the respiratory rate from ballistocardiograms using the Hilbert transform
Onno Linschmann1, Steffen Leonhardt2, Antti Vehkaoja3
1Medical Information Technology, Helmholtz Institute, RWTH Aachen University, Aachen, Germany. linschmann@hia.rwth-aachen.de.
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.
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