Current soft surface electrodes have attracted more and more attentions owing to their potential applications in biological signal monitoring, human-machine interaction (HMI) and Internet of Things (IoT). The paper presents that soft dry electrode based on polydimethylsiloxane-carbon black (PDMS-CB) conductive polymer is designed and fabricated to continuous, long-term, stable electroophthalmogram (EOG) signal recordings for HMI applications. The features corresponding to the different eye motions are extracted from the EOG data via the soft dry electrodes. Linear discriminant analysis (LDA) recognition algorithms are proposed to recognize eye motion behaviors for controlling the motion of the mobile robots. Experiment results have been demonstrated that LDA recognition algorithm achieves a relatively high recognition accuracy of 90.63% for recognizing four eye movements (‘Up’, ‘Down’, ‘Right’, and ‘Left’). The control commands are generated with different eye motions and transmitted to the mobile robot through WiFi communication unit, which the mobile robot is successfully controlled. The soft dry electrodes have the potential in a comfortable, simple, wearable and wireless control of rehabilitation devices.

中文翻译：

---

用于人机交互的柔软干燥眼电图电极。

当前的软表面电极由于其在生物信号监控，人机交互（HMI）和物联网（IoT）中的潜在应用而受到越来越多的关注。本文介绍了基于聚二甲基硅氧烷-炭黑（PDMS-CB）导电聚合物的软干电极的设计和制造，可用于HMI应用的连续，长期，稳定的眼电图（EOG）信号记录。经由软干电极从EOG数据中提取与不同眼动相对应的特征。提出了线性判别分析（LDA）识别算法来识别眼睛运动行为，以控制移动机器人的运动。实验结果表明，LDA识别算法可达到90的较高识别精度。63％用于识别四个眼动（“上”，“下”，“右”和“左”）。通过不同的眼睛动作生成控制命令，并通过WiFi通信单元将控制命令传输到移动机器人，从而成功控制了移动机器人。柔软的干电极具有舒适，简单，可穿戴和无线控制康复设备的潜力。