Soft dry electroophthalmogram electrodes for human machine interaction

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.