OMG: Introducing Optical Myography as a New Human Machine Interface for Hand Amputees

Abstract

Given the recent progress in the development of computer vision, it is nowadays possible to optically track features of the human body with unprecedented precision. We take this as a starting point to build a novel human-machine interface for the disabled. In this particular work we explore the possibility of visually inspecting the human forearm to detect what fingers are moving, and to what extent. In particular, in a psychophysical experiment with ten intact subjects, we tracked the deformations of the surface of the forearm to try and reconstruct intended finger motions. Ridge Regression was used for the reconstruction. The results are highly promising, leading to an average error in the range of 0.13 to 0.2 (normalized root mean square error). If further successfully tested in the large, this approach could represent a fully fledged alternative / replacement to similar traditional interfaces such as, e.g., surface electromyography.