Biomedical Signal Processing using Matlab and Open Source R Software – A Comparative Study on Running Times

In recent years, due to the enormous growth in computer power, memory, storage, and performance, even personal computers are being used to operate a broad range of complicated functions with extraordinary accuracy. Also, with the aid of supercomputers or high-end servers, the most wanted techniques such as machine learning, deep learning, advanced signal processing, and artificial intelligence can be executed quickly that too with higher accuracy. This article focuses mainly on computing the running times of platforms such as Matlab and R open-source software. For better comparison, functions such as dc-bias removal, a 1024-point fast Fourier transform, filtering using median, and moving average filters are considered. This study may become an excellent guide for beginners who are working with R open-source software. For many functions, the Matlab platform provides better performance (lower running times) than R software. The Matlab 9.4 tool and RStudio are used experimental simulations for specific tasks to compare the running times.