I-Corps: Self Calibration Techniques for Robust Brain Computer Interface

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

Researchers propose a self-calibrating integrated approach that operates at the hardware, signal processing and user interface levels to adapt to the new recording session with the least burden on the user as outlined here: 1) The hardware and circuit level approach, where the aim is to find input contact mismatch by injecting a reference signal of known amplitude and observe the common-mode rejection ration (CMMR) of the circuits and electrodes. Artifacts of this reference signal manifest themselves when the electrode coupling is worsening. 2) Employing the signal processing calibration techniques to resolve the strong variation in electroencephalography (EEG) signals from one session to another. Specifically, the research team proposes adaptive training algorithms to utilize relevant information from prior recording sessions to shorten or even omit the calibration time for the next session. 3) Creating customizable user interface in order to produce a more user friendly interface that create less burden on the user. More adaptive user interfaces will lead to more comfortable use, higher transfer rate and better accuracy in realization of the user intents. Researchers plan to develop an inexpensive, easy-to-wear, and low power brain computer interface (BCI) system that uses dry-contact EEG electrodes and can be connected to the computer via Bluetooth and is suitable for real-time applications. EEG systems have been around for a relatively long time and their applications have been mostly inside the laboratories. However, BCI applications can potentially include any real-world interaction in our daily life. The introduction of low profile, and inexpensive BCI devices with the size of a cellphone and comparable prices create opportunities for new applications controlled with our thoughts, expressions and emotions. For instance, with the rising incidence of chronic diseases, a major health care application for BCI self-calibrating devices is wearable in-home assessment systems to quantify the existence of symptoms or effectiveness of treatments for brain deficiencies through long term EEG recording and analysis. BCI technology has great potentials to become the most common communication alternative for users interacting with computers. For instance, BCI devices are capable of emerging in the gaming industry. It enables the consumers to experience an entirely new form of human-machine interaction by eliminating the conventional joysticks for gaming, entertainment, navigation and rehabilitation.