A Novel Approach of ECG Signal Enhancement Using Adaptive Filter Based on Whale Optimization Algorithm

An Electro cardiogram is commonly used in biomedical signal processing. It is used to monitor minor electrical changes in the human body. The electrical changes originate due to the function of heart. The anomalies of heart are found by ECG. In this work the Whale optimization algorithm is used to de-noising the ECG signal. The Whale optimization algorithm is used with Adaptive filter which filter the corrupted ECG signal. The performance of the ANC will be improved by calculating the optimum weight value. The WOA technique gives the best result on the different fidelity parameter compare to PSO, MPSO and ABC. The WOA technique gives the significant improvement in accuracy. It gives a good SNR, MSE, ME result compare to PSO, MPSO and ABC. The WOA gives 80% improvement in SNR 88% in MSE and 89% in ME as compared to PSO. So, by using WOA we get a desired ECG component. The WOA reduces the noise in ECG signal and improves the quality of signal.

Evaluation of Electromyogram Signals in the Control of Prosthetic Limb: A Review

: Electromyogram (EMG) signals are produced by the human body and are used in prosthetic design due to its significant functionality with human biomechanics. Engineers are capable of developing a variety of prosthetic limbs with the advancement of technology in the domain of biomedical signal processing, as limb amputees can restore their lives with the help of prosthetic limbs. This current review paper looks at the signals that are used to monitor the device, explaining the various steps and techniques involved (such as data acquisition, feature vector conversion after noise, and redundant data removal) and reviewing previously developed electromyogram-based prosthetic controls. Furthermore, this research also focuses on a variety of electromyogram controlled applications.