Background

Patients with severe physical disabilities, such as people with quadriplegia, have considerable challenges in completing daily tasks without assistance. Tasks such as opening doors, turning on lights, and moving around the home become difficult for people with severe physical disabilities.

Recently, Human Machine Interface (HMI) systems have been proposed as a potential solution to allow these patients to more fully interact with their environment. These systems include brain-computer interfaces, electromyography switches, eye gaze trackers. However, these systems can be invasive an expensive, and are often complicated by low signal-to-noise ratios. A novel HMI system is needed that is non-invasive, cheap to produce, and easy to use.