Human–Machine Interfaces for Motor Rehabilitation

Neurological disorders affect a large part of the population, causing cognitive and motor impairments. To that end, non-pharmacological interventions targeting support and restoration of the disrupted functions have been a major issue in modern society. New technologies enable effective communication between the affected individual and an external system, establishing the concept of a human–machine interface (HMI). This chapter seeks to describe the principles of modern noninvasive HMI systems and to present current trends regarding the methods used to capture physiological and non-physiological motor-related data in order to control external devices within a rehabilitation framework. Furthermore, in regard to classification and parameter complexity, computational intelligence tools, machine learning approaches and simulation testing are presented. The relevant applications are discussed within a taxonomy based on the nature of the motor-related source data, while methodological aspects and future challenges concerning the design of HMI systems for rehabilitation purposes are also included.