**2. EEG emulated switch**

An EEG switch is a control circuit which produces a digital switch output driven by an EEG pattern. After the BCI challenge stated by Vidal [2], the first EEG switch was explicitly described in 1988 [9–12]. It is shown in **Figure 1** [11–12].

**Figure 1** shows the screen of the 1988 brain-machine interface program [9–12]. The lower part of the screen shows the EEG signal recorded in a particular BMI session. Inside that session a user may generate alpha wave bursts by some relaxation technique, for example closing/opening the eyes. The robot movement takes place in real time while intentionally generating/blocking the alpha rhythm. In offline analysis mode, the program has a feature of zooming a part of the signal, defined by a line below the signal, as shown in **Figure 1**. The zoomed segment of the signal is shown in the center of the screen. The upper part of the screen shows the result of pattern recognition method in real time, which recognizes when the EEG signal contains increased amplitude of the alpha rhythm. That produces a switch pattern, actually an EEG emulated Schmitt trigger (e.g., [25]). The recognition software implements a machine learning algorithm in which the learning phase is collecting two distributions, one for amplitude and one for frequency. If both amplitudes and periods between two adjacent extreme points of an EEG signal increase, it is recognized as increased alpha rhythm, and it turns on the switch.

**Figure 1.** *EEG emulated digital switch.*

**Figure 2.** *The 1988 experimental setup for an EEG control of a robot.*

If both amplitudes and periods decrease, it turns off the switch. A statistical machine learning method was used. Details are given in a recent review [26].

A human user, in a BCI based on an EEG emulated switch presented in **Figure 1**, requires a period of training in order to perform the task. The 1988 experiments show that the training requires about 20 minutes.

Let us note that the concept of a "mind switch" was introduced in [14]. Before that, the term "switching devices" [27] was used in relation to the independence of disabled persons. The term "brain-controlled switch" was used in [16]. We use the term EEG emulated switch as part of our work on EEG emulated control circuits.

The BMI task when the EEG emulated switch was used in 1988, was control of a mobile robot moving along a closed line drawn on the floor. Robot movement happens when the user increases the alpha rhythm by closing the eyes. The robot stops when the user opens the eyes and observes how far the robot is from the goal point, a "station" where the robot should stop. At what point to stop was decided by the user based on a visual feedback. The BMI setup is shown in **Figure 2**.

**Figure 2** is a translation of the original 1988 block diagram of a BCI [9–12]. It was the first block diagram of a BCI in the literature. It shows a human user, an EEG amplifier, a computer (PC/XT), an A/D converter, a software for recognition of an alpha rhythm, a D/A converter, an energy amplifier, a robot, and an optical sensor for following the trajectory drawn on the floor. The robot used was a Ellehobby Movit Line Tracer II.

A differential biosignal amplifier was used to record the signal from the Pz site (international 10/20 system), with referential electrode on right mastoid, and ground electrode placed at the forehead. The signal was received in an IBM PC/XT (640 KB, 8 MHz) computer by an A/D converter at 300 Hz sampling rate. The software which recognized the alpha wave was written in Pascal. During the alpha wave presence, the system outputted a logic pulse at 5 volts through a D/A converter. The output signal was amplified on a transistor amplifier which drove the robot motor.
