One-Sensor P300 EEG and Blink EOG from OpenBCI Cyton Board

Resumen

Two different systems have been developed in this study. An  EEG control system based on P300 EP and an EOG system based on eye blinks. Both developed systems, the objects that the user can interact with are presented on a laptop screen using a GUI. This stimulation program was designed and developed in Python employing the PsychoPy package. The GUI, composed by a 3×3 matrix containing nine images describing the objects and control functions to be executed by users. The first two rows correspond to home devices, such as TVs, digital house locks or electric lights, which have a state that can be switched (e.g., on/off or up/down) by selecting it with the HMI. The last row has three possible phone calls: the emergency call (i.e., an SOS number) and two favourite contacts in their phone-book. Two stimulation paradigms were assessed for the experiments. For the first paradigm, each element of the matrix is intensified one by one. This intensification is randomly performed, but all the elements are intensified the same number of times. Therefore, they will have the same probability of being intensified, that is, 𝑝=1/9. Moreover, an element cannot be intensified two consecutive times..For the second paradigm, instead of element by element, each row and column of the matrix is intensified. This is also done randomly, and they are intensified the same number of times. Therefore, the probability of one element being intensified at any given time is 𝑝=2/6=1/3.   EEG and EOG data have been recorded using the OpenBCI Cyton Board with a sampling frequency of 250Hz. For EEG recordings, since the objective is to detect the P300 potential, the electrode for the input channel was located in the Cz position. Conversely, for EOG recordings, the electrode was placed at Fp2 in order to detect activity related to eye blinks. Both recording modes shared reference and ground electrodes, placed at the right mastoid (RM) and the left earlobe (A1), respectively.  The participant group in our experiments included a total of nine volunteers who agreed to collaborate in this research. The participants indicated that they did not have hearing or visual impairments. Informed consents were obtained from all the participants in order to employ their data in our study. The experiments were carried out in a sound-attenuated room where the participants were invited to sit in a comfortable chair while focusing their attention on a 15.6-inch laptop screen where stimuli were presented.  Recording sessions for each participant were divided into four independent experiments, one per each stimulation paradigm and recording mode that is: for the 1-by-1 paradigm with EEG signals, for the row/column paradigm with EEG signals, for the 1-by-1 paradigm with EOG signals and for the row/column paradigm with EOG data. Eight runs were recorded for each experiment. Each subject recording is stored in one separate folder, named s[number_subject], e.g., for subject 1: folder s1. Inside each subject folder we will find 32 folders corresponding with each experiment. The structure of the name is the following: subject_controlSignal_paradigm_date, eg, s1P3001by1-12-11-2020_12-57-15. Inside each experiment folder we will find 3 files.  ExInfo : Contains data related to the subject, channel, paradigm and also the target element of that experiment. Raw-STIMS: Contains the stimuli presentation for that experiment. It is important to note that each specific stimuli is represented by a code. In the 1-by-1 paradigm these codes range from 101 to 109 and represent each of the elements of the 3x3 matrix, from the upper left corner to the bottom right corner. In the row-column paradigm these codes range from 101 to 106. Codes 101-103 represents the rows of the matrix from top to bottom. Codes 104-106 represent the columns of the matrix from left to right. Raw-EEG: Contains the EEG data recorded from the Cyton board.  For more details about the recordings and the data plase see the related paper of this study and also the associated code: Sensors | Free Full-Text | Proposals and Comparisons from One-Sensor EEG and EOG Human-Machine Interfaces (mdpi.com) franciscolaport/Proposals-and-Comparisons-from-One-Sensor-EEG-and-EOG-Human-Machine-Interfaces (github.com)