# Fuzzy Tracking and Control Algorithm for an SSVEP-Based BCI System
## 1 Introduction  
Amyotrophic lateral sclerosis (ALS) attacks the motor neurons. Numerous ALS patients around the world report that ALS seriously reduces the quality of their lives. ALS critically reduces their motor abilities; they experience difficulties in performing daily activities, such as participating in entertainment activities. Therefore, in recent years, an extensive range of high technology assistive devices have been developed to fulfill the needs of these individuals. These assistive devices can help these patients perform daily activities such as eating, communicating, and moving from place to place. Although assistance in performing daily activities is essential, the psychological effects of nonessential patient activities such as entertainment should also be considered. Therefore, the development of a brain-computer interface (BCI) application for entertainment is worthwhile for subjects with ALS. A BCI is used to give commands to a computer or other device through electroencephalography (EEG) measurements taken from sensors on a human scalp. A BCI is not necessary for the implementation of any sensor into the brain, so it can easily be applied to subjects with motor neuron disease [1]. This technology can effectively and easily help subjects with ALS to communicate with the outside world [2]. A BCI can be developed using P300 waves, motor imagery, event-related potential, visual evoked potential, and steady-state visual evoked potential (SSVEP) [3; 4; 5; 6; 7; 8; 9]. A P300-based BCI is operated by asking the user to select a row and a column from a command matrix [4]. BCI applicationscan integrate several methods, such as P300 and SSVEP [5; 6]. A suitable BCI for subjects with ALS may enable those subjects to operate various devices, including entertainment devices. SSVEP technology has been utilized in BCI applications by using visual stimuli to induce human brain waves and trigger brain potentials [3]. Several boxes with different flickering frequencies can be used as stimuli for SSVEP applications [7]. Other researchers have used several boxes that flickered at the same frequency but with different phases as stimuli for an SSVEP application [8]. The light source that was used as a stimulus also varied. Some research has used liquid-crystal display (LCD) monitors as stimuli, and other research has used LEDs as stimuli. A SSVEP-based BCI is one of the easiest interfaces to implement for subjects with ALS. Several studies have been proposed to develop BCI applications for entertainment. A BCI application was designed to help people with severe disabilities play tennis games on a computer [10]. The use of consumer-grade equipment rather than research lab-grade equipment for BCI gaming applications can improve public awareness of BCI technology. SSVEP technology can be adopted to provide excellent control when applied in a tactical video game [11]. Another SSVEP-based BCI application was used to control an avatar in a maze game. Four commands triggered by responses to stimuli, namely up, down, left, and right, controlled the movement of an avatar in a maze [12]. Phase-tagging SSVEP has been implemented to control spacecraft movement to avoid obstacles. Two stimuli with 180\({}^{\circ}\) phase differences and frequencies in the 3-5 Hz range were used to produce inputs for controlling left or right movements [13]. In general, most fuzzy recognition algorithms contain three processes: fuzzification, inference rules, and defuzzification. In fuzzy recognition algorithms, fuzzy sets and fuzzy logic are used for heuristic quantification of the meanings of linguistic variables, linguistic values, and linguistic rules that are specified by experts. The concept of a fuzzy set can be introduced by first defining a \"membership function.\" Fuzzy sets are used to quantify the information in the rule-base, and the inference mechanism operates on fuzzy sets to produce fuzzy sets; hence, the fuzzification process converts numeric inputs into fuzzy sets.