A human-machine interface based on single channel EOG and patchable sensor. (September 2016)

• Record Type: Journal Article
• Authors: Guo, Xuhong; Pei, Weihua; Wang, Yijun; Chen, Yuanfang; Zhang, He; Wu, Xian; Yang, Xiaowei; Chen, Hongda; Liu, Yuanyuan; Liu, Ruicong
• Is Part Of: Biomedical signal processing and control. Volume 30(2016)
• Page Start: 98
• Page End: 105
• Publication Date: 2016-09
• Subjects: Flexible patchable sensor -- Electrooculography -- Human-machine interface; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2016.06.018
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: A flexible dry electrode was manufactured to acquire the bioelectrical signals. A new control paradigm and an efficient classification algorithm were combined to implement the HMI system. An EOG-based HMI system was realized to recognize three kinds of eye movements with high accuracy and ITR. This study combined the advantages of dry electrode and single recording channel to reduce the system preparation time and improve user comfort. Abstract: Goal: This study demonstrates that single channel electrooculography (EOG) recorded by ultrathin and flexible electrodes can be practically used to control computer or machine, with the aid of proper recognition algorithms and efficient controlling methods. Methods: First, micro-fabrication process and transfer technology were used to develop a patchable sensor including three electrodes (a measurement electrode, a ground electrode, and a reference electrode). Each electrode was composed of golden ribbon in the form of a filamentary serpentine mesh to provide conformal contact of skin and stretchability. Second, EOG was recorded by the proposed sensor installed above the eyebrow. The peak and trough of eye movement signals were extracted as features to recognize three types of eye movements (blink, upward and downward) using a threshold-based recognition algorithm. Finally, a human-machine interface (HMI) system was realized by converting eye movements to computer commands including scroll up, scroll down, and close. To verify the effectiveness of the system, eight subjects were trained to use their eye movements to navigate a document on the screen. Results: The sensor was approximately triangular with a 5 cm side-length and a 70 um thickness. The electrode can be stretched to 10% longer without any damage. The weight of the sensor was 180 mg. The demonstration system was capable of making continuous controls with an average accuracy of 84%. Conclusion: Single channel EOG recorded with a patchable sensor is feasible for developing a wearable HMI system. The proposed system provides a comfortable user experience, a stable control method and a simple systematic framework for developing practical HMI systems.