Respiration Rate Diagnosis Using Single Lead ECG in Real Time

Abstract

Respiration rate is the respiratory signal or the respiratory knowledge. Numeral methods can be applied to derive a respiratory signal from the ECG. The efficacy of this monitoring can be improved by deriving respiration, which previously has been based on overnight polysomnography studies where patients are stationary or the use of multi lead ECG systems. In this paper, ECG features of Heart rate variability (HRV) and ECG-derived respiration (EDR) including ECG filtering methods are examined. This ECG features are compared with the simultaneously recorded respiratory signal, it is estimate from RR-interval, R-wave time duration and R-wave amplitude. These values are evaluated using discrete wavelet transform. Based on the respiratory signal, time domain measures are Mean RR, SDRR, Maxrate, Minrate, RMSDD, SDEDR, Mean EDR, p NN 50, NN 50 are calculated, that reflect the Respiration rate variability (RV). Those Respiration variability measures have been established their use, by the ability to distinguish between periods of rest and during respiratory rate testing time. Moreover, these RV measures are able to differentiate between the first resting period and the periods following the respiration rate.