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

研究人员提出了一种自校准集成方法，该方法在硬件、信号处理和用户界面层面上运行，以适应新的记录会话，同时用户负担最小，如下所述：1)硬件和电路层面的方法，其目的是通过注入已知幅度的参考信号来发现输入触点不匹配，并观察电路和电极的共模抑制比（CMMR）。当电极耦合恶化时，参考信号的伪影就会显现出来。2)采用信号处理校准技术解决脑电信号在不同时段之间的强烈差异。具体来说，研究小组提出了自适应训练算法，利用先前记录会话的相关信息来缩短甚至省略下一会话的校准时间。3)创建可定制的用户界面，以产生更友好的用户界面，减少用户负担。用户界面的适应性越强，使用越舒适，传输速率越高，实现用户意图的准确性也越高。研究人员计划开发一种廉价、易于佩戴、低功耗的脑机接口（BCI）系统，该系统使用干接点脑电图电极，可以通过蓝牙与计算机连接，适用于实时应用。脑电图系统已经存在了相当长的时间，它们的应用主要是在实验室里。然而，BCI应用程序可以潜在地包括我们日常生活中的任何现实世界交互。低调、廉价、手机大小、价格相当的脑机接口设备的推出，为我们的思想、表情和情感控制的新应用创造了机会。例如，随着慢性病发病率的上升，BCI自校准设备的主要医疗保健应用是可穿戴的家庭评估系统，通过长期脑电图记录和分析来量化脑缺陷症状的存在或治疗的有效性。BCI技术有很大的潜力成为用户与计算机交互的最常见的通信替代方案。例如，BCI设备能够在游戏行业中崭露头角。它使消费者能够通过消除传统的游戏、娱乐、导航和康复的操纵杆，体验一种全新的人机交互形式。

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.