Akram Faraz, Han Seung Moo, Kim Tae-Seong
Department of Biomedical Engineering, Kyung Hee University, Yongin-si, Republic of Korea.
Department of Biomedical Engineering, Kyung Hee University, Yongin-si, Republic of Korea.
Comput Biol Med. 2015 Jan;56:30-6. doi: 10.1016/j.compbiomed.2014.10.021. Epub 2014 Nov 4.
A typical P300-based spelling brain computer interface (BCI) system types a single character with a character presentation paradigm and a P300 classification system. Lately, a few attempts have been made to type a whole word with the help of a smart dictionary that suggests some candidate words with the input of a few initial characters.
In this paper, we propose a novel paradigm utilizing initial character typing with word suggestions and a novel P300 classifier to increase word typing speed and accuracy. The novel paradigm involves modifying the Text on 9 keys (T9) interface, which is similar to the keypad of a mobile phone used for text messaging. Users can type the initial characters using a 3×3 matrix interface and an integrated custom-built dictionary that suggests candidate words as the user types the initials. Then the user can select one of the given suggestions to complete word typing. We have adopted a random forest classifier, which significantly improves P300 classification accuracy by combining multiple decision trees.
We conducted experiments with 10 subjects using the proposed BCI system. Our proposed paradigms significantly reduced word typing time and made word typing more convenient by outputting complete words with only a few initial character inputs. The conventional spelling system required an average time of 3.47 min per word while typing 10 random words, whereas our proposed system took an average time of 1.67 min per word, a 51.87% improvement, for the same words under the same conditions.
典型的基于P300的拼写脑机接口（BCI）系统通过字符呈现范式和P300分类系统来输入单个字符。最近，人们尝试借助智能词典，在输入几个初始字符的情况下，输入整个单词，智能词典会根据这些初始字符给出一些候选单词。
在本文中，我们提出了一种新颖的范式，即利用带单词建议的初始字符输入以及一种新颖的P300分类器，以提高单词输入速度和准确性。这种新颖的范式涉及对9键文本（T9）界面进行修改，该界面类似于用于短信输入的手机键盘。用户可以使用3×3矩阵界面和集成的定制词典输入初始字符，该词典会在用户输入初始字符时给出候选单词。然后，用户可以从给定的建议中选择一个来完成单词输入。我们采用了随机森林分类器，通过组合多个决策树显著提高了P300分类的准确性。
我们使用所提出的BCI系统对10名受试者进行了实验。我们提出的范式显著减少了单词输入时间，并且通过仅输入几个初始字符就能输出完整单词，使单词输入更加便捷。在输入10个随机单词时，传统拼写系统平均每个单词需要3.47分钟，而在相同条件下，我们提出的系统平均每个单词只需1.67分钟，提高了51.87%。
