• CHERUKUMILLI PAVAN KUMAR
• DR .M.SAILAJA

A crucial physiological characteristic that is frequently assessed in a variety of therapeutic contexts is breathing rate (BR). It is still frequently measured manually, though. In this study, a novel methodology is put forth for estimating the BR from a blood pressure (BP), photoplethysmogram (PPG), or electrocardiogram (ECG) signal. The framework takes advantage of both time and frequency domain data to extract respiratory signals using Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) techniques. With the use of a Robust Kalman Filter (RKF) that incorporates a Signal Quality Index (SQI), our technique was able to operate adequately even during periods when the signals were noticeably distorted. The output signals are integrated via state vector fusion, and then the BR is calculated. The MIT-BIH Polysomnographic and BIDMC datasets were used to evaluate the framework on two publically accessible clinical databases. The mean absolute percentage error (MAPE) was used to evaluate performance. The outcomes showed great accuracy, with MAPEs on the two databases for ECG signals of 4% and 4%, 7% for PPG signals, and 5.4% for BP signals. The outcomes also showed a remarkable robustness to noise at 0 dB. Consequently, this system might be useful for BR monitoring in environments with excessive noise.

Breathing rate (BR), Electrocardiogram (ECG), Photoplethysmogram (PPG), blood pressure (BP), Robust Kalman Filter (RKF), respiratory rate, respiratory signals, empirical mode decomposition (EMD), discrete wavelet transform (DWT), Signal Quality Index (SQI),power spectral density (PSD).

"A MODIFIED FRAMEWORK TO ESTIMATE BREATHING RATE FROM ELECTROCARDIOGRAM, PHOTOPLETHYSMOGRAM, AND BLOOD PRESSURE SIGNALS BY USING ROBUST KALMAN FILTER .", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.b804-b813, November-2023, Available :http://www.jetir.org/papers/JETIR2311198.pdf

"A MODIFIED FRAMEWORK TO ESTIMATE BREATHING RATE FROM ELECTROCARDIOGRAM, PHOTOPLETHYSMOGRAM, AND BLOOD PRESSURE SIGNALS BY USING ROBUST KALMAN FILTER .", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppb804-b813, November-2023, Available at : http://www.jetir.org/papers/JETIR2311198.pdf