Development of a real-time breathing-rate monitor using difference operation method and adaptive windowing on dry-electrode ECG signal

Estimation of breathing rate (BR) along with electrocardiogram signal plays an important role in patient health monitoring. Continuous monitoring of BR is often required during diagnosis of many diseases. Traditional methods like nasal air flow equipments employ cumbersome methods of BR monitoring which is not suitable for continuous monitoring. Therefore, a non-invasive method of estimation is required. This paper proposes a non-invasive way of BR estimation using dry-electrode ECG from the palm of a person. The paper uses Respiratory Peak Arrhythmia and Respiratory Sinus Arrhythmia based ECG derived respiratory rate estimation technique. We have developed an algorithm for real-time BR estimation which can be run on embedded platform having limited computation capability. The whole algorithm was first tested on MIT-BIH polysomnographic database and then later extended to obtained signal from developed analog circuitry and the embedded platform. Nasal airflow sensor is used for calculating reference BR. The developed setup was tested on volunteers and the obtained results show accuracy to be in between 2 breaths per minutes.