Functional Languages in Signal Processing Applied to Prosthetic Limb Control

This article describes how one can use functional languages to develop a dedicated system for controlling a prosthetic arm. It shows the prototype artificial limb along with the development of the various algorithms and software used to process electromyographic (EMG) signals, to be used as inputs for the control mechanism. Great emphasis is also laid on the parametric modelling used to extract the necessary features from the EMG signals. An iterative least mean square (LMS) algorithm has been used to improve the efficiency of traditional LMS algorithms, which greatly enhanced the performance of the system. The use of the functional paradigm lead to a fast developing stage and a very compact set of programs that will run as fast as (sometimes even faster than) traditional C/C++ programs.