Holland Bloorview Kids Rehabilitation Hospital, Bloorview Research Institute, Toronto, Ontario, Canada.
Neurosci Lett. 2012 Oct 24;528(2):99-103. doi: 10.1016/j.neulet.2012.09.030. Epub 2012 Sep 21.
In this study, we conducted an offline analysis of transcranial Doppler (TCD) ultrasound recordings to investigate potential methods for increasing data transmission rate in a TCD-based brain-computer interface. Cerebral blood flow velocity was recorded within the left and right middle cerebral arteries while nine able-bodied participants alternated between rest and two different mental activities (word generation and mental rotation). We differentiated these three states using a three-class linear discriminant analysis classifier while the duration of each state was varied between 5 and 30s. Maximum classification accuracies exceeded 70%, and data transmission rate was maximized at 1.2 bits per minute, representing a four-fold increase in data transmission rate over previous two-class analysis of TCD recordings.
在这项研究中，我们对经颅多普勒 (TCD) 超声记录进行了离线分析，以研究在基于 TCD 的脑机接口中提高数据传输率的潜在方法。在 9 名健康参与者在休息和两种不同的心理活动（词语生成和心理旋转）之间交替时，我们记录了左、右大脑中动脉的血流速度。我们使用三分类线性判别分析分类器对这三种状态进行了区分，同时每个状态的持续时间在 5 到 30 秒之间变化。最大分类准确率超过 70%，数据传输率最高可达 1.2 位/分钟，与之前对 TCD 记录的两分类分析相比，数据传输率提高了四倍。
