基于眼电的阅读状态检测研究

Detection of reading status based on EOG

目的阅读是一种重要的认知过程,可通过眼动检测实现观测。基于眼电的阅读检测算法可应用于不同的阅读行为和注意力水平的自动检测。方法通过提取阅读时水平眼电信号的特征以有效识别阅读活动。首先使用数学形态学对原始水平眼电信号进行平滑处理,去除眨眼和肌电等干扰。平滑后的眼电信号进行差分处理,然后提取出阅读时的水平眼电信号的特征,进行识别分类,从而判断出受试的阅读情况,并与实际的阅读状态进行比较。结果对阅读状态和非阅读状态时间段的分析结果显示,数学形态学和阈值法相结合的方法对眨眼和肌电等噪声的抗干扰能力较强,可有效识别出阅读活动,平均检测率为75%。结论数学形态学和特征提取相结合的方法能较好地提取出眼球的活动信息,应用于日常的阅读活动识别中。

Objective Reading behavior which is an important cognitiye process can be realized by detecting the eye movements. This paper presents a detection algorithm which can identify reading activities effectively through the feature extraction of horizontal EOG. The detection algorithm can detect different reading behaviors and attention levels automatically. Methods First,the EMG and blink interference are removed from the horizontal EOG by mathematical morphology. Next, the features of the smoothed horizontal EOG are extracted by difference arithmetic. At last,the reading activities can be detected by the classification result of the features which are compared with actual reading activities. Results The analysis results of reading state and non-reading state in different periods show that the combination method of mathematical morphology with threshold value method has a strong anti-interference ability to the noise of blink and EMG. In this paper, a detection rate of 75% is achieved. Conclusions The combination method of mathematical morphology with feature extraction is effective for identifying the reading behaviors. This method can be applied to the recognition of daily reading activity.