Monitoring of Respiration activity is very important in diagnosis, therapeutics, during surgical procedures, Stress testing, monitoring sleeping disorders and cardiac & pulmonary related disorders. The joint study of respiratory and cardiac activity suggests indirect methods to derive the respiratory signal by electrocardiogram (ECG) processing. Extraction of respiratory activity from electrocardiogram (ECG) signal will eliminate the use of an additional hardware used to record respiration. The

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... present study proposes various algorithms to estimate respiratory rate and Heart rate from ECG signal during incremental stage of exercise. For that, instrument like Treadmill test (TMT) with Bruce protocol is preferable. In this paper, five methods have been implemented, which are: (1) Discrete wavelet transform (DWT) method (2) Filtering concept method (3) R peak amplitude variation method (4) Homomorphic filter and (5) Neural network method. Comparison of result found that all methods have acceptable accuracy but EDR using neural network method gives highest accuracy compared to other methods.