In present-day scenario, major efforts have been put into the development of human prosthetic models from electromyographic (EMG) signals to achieve more natural control for re-habitation of humans. Myoelectric control of prosthetic arms provides light for providing naturalistic movements. The objective of this article is to reconstruct the input myoelectric signal by removing the noise, mitigating the electrical and mechanical disturbances present in the EMG signal. To meet the above objective, a novel algorithm called Anudruti algorithm is proposed which makes use of Fourier transform spectral analysis and Kalman filter. The proposed algorithm smoothens the input signal to the prosthetic model, thereby enhancing the performance of the system even with worst input conditions. The algorithm is mathematically modeled, and the simulated results are obtained in support of the model. The Anudurti algorithm is put under various test conditions from best to worst, and the results are found to be more promising than the conventional system. The test results show that the system achieves its maximum efficiency of 94% and to a minimum of 73%. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.