Respiratory rate estimation from the oscillometric waveform obtained from a non-invasive cuff-based blood pressure...

Area of Science:

• Biomedical Engineering
• Physiological Signal Processing
• Digital Health

Background:

• Respiratory activity is detectable in various physiological signals like ECG and blood pressure.
• Current methods for respiratory rate (RR) estimation often rely on specialized equipment or other physiological signals.

Purpose of the Study:

• To demonstrate the presence of respiratory information in oscillometric signals from non-invasive blood pressure monitors.
• To develop and validate a novel method for estimating respiratory rate (RR) using these signals.
• To improve the reliability of RR estimation by addressing poor signal quality.

Main Methods:

• A novel method was developed to combine frequency and amplitude variations from oscillometric signals.
• Frequency analysis was employed to estimate RR and filter unreliable data.
• The method was validated using data from 40 subjects, comparing estimated RR against reference respiration waveforms.

Main Results:

• The proposed method achieved a mean absolute error of 2.69 breaths/min in RR estimation.
• Accuracy was comparable to existing methods using other physiological signals.
• The method successfully filtered unreliable estimations due to poor signal quality.

Conclusions:

• Oscillometric signals from non-invasive blood pressure monitors contain valuable information for respiratory rate estimation.
• The developed frequency analysis method provides accurate and reliable RR estimation.
• The implementation on an Android device facilitates its use in mHealth platforms.