Haptic and Gesture-Based Assistive Technologies for People with Motor Disabilities

Abstract

The goal of this chapter is to explain how haptic and gesture-based assistive technologies work and how people with motor disabilities can interact with computers, cell phones, power wheelchairs, and so forth. The interaction is achieved through gestures and haptic feedback interfaces using bioelectrical signals such as in surface Electromyography. The chapter also provides a literature survey on ElectroMyoGraphic (EMG) devices and their use in the design of assistive technology, while it covers typical techniques used for pattern recognition and classification of EMG signals (including Independent Component Analysis, Artificial Neural Networks, Fuzzy, Support Vector Machines, Principle Component Analysis, the use of wavelet coefficients, and time versus frequency domain features) the main point driven by this literature survey is the frequent use of multiple sensors in the design and implementation of assistive technologies. This point is contrasted with the state-of-the-art, more specifically the authors’ current work, on the use of a single sensor as opposed to multiple sensors.