Assistive technologies using brain-computer interfaces: the problem of mental fatigue

Assistive technology has great potential for enhancing the capabilities of individuals with disabilities. In people with a severe neurological disability like chronic spinal cord injury (SCI) one strategy to overcome functional loss involves providing access to assistive technology that allows the severely disabled person to regain some level of control over their living environment. New types of assistive technologies include brain computer interface (BCI) based assistive technology systems. These are systems that interpret and translate voluntary changes in brain electrical activity to allow users to activate and control devices in their environment with their brain signals. However, BCI based assistive technologies require a great deal of attention and concentration from the user, especially if the user exerts control over extended periods of time. Any task that requires extended concentration and attention will undoubtedly result in elevated mental fatigue. Chronic mental fatigue is a common though negative symptom of many illnesses and disabilities. In this chapter we describe a device that utilizes changes in brain activity using EEG alpha waves (8-13Hz) as a switching mechanism for an environmental control system (ECS). The device functions by detecting changes in alpha activity during the opening and closing of the eyes. A rapid and substantial increase in alpha activity is observed when eyes are closed and there is a large attenuation of the 8-13Hz activity when the eyes are open. Switching occurs when alpha activity increases above a set threshold during eye closure. Although this hands-free ECS has been shown to be effective in severely disabled participants in their homes while operating a television set, little is known about the effects of mental fatigue on the operational capacity of this device when used by people with severe disabilities for long periods of time. Recent research on strategies for controlling the impact of fatigue will be presented and implications for BCI assistive technology discussed.