Golparvar Ata Jedari, Yapici Murat Kaya
Faculty of Engineering and Natural Sciences, Sabanci University, TR-34956 Istanbul, Turkey.
Sabanci University SUNUM Nanotechnology Research Center, TR-34956 Istanbul, Turkey.
Beilstein J Nanotechnol. 2021 Feb 11;12:180-189. doi: 10.3762/bjnano.12.14. eCollection 2021.
The study of eye movements and the measurement of the resulting biopotential, referred to as electrooculography (EOG), may find increasing use in applications within the domain of activity recognition, context awareness, mobile human-computer and human-machine interaction (HCI/HMI), and personal medical devices; provided that, seamless sensing of eye activity and processing thereof is achieved by a truly wearable, low-cost, and accessible technology. The present study demonstrates an alternative to the bulky and expensive camera-based eye tracking systems and reports the development of a graphene textile-based personal assistive device for the first time. This self-contained wearable prototype comprises a headband with soft graphene textile electrodes that overcome the limitations of conventional "wet" electrodes, along with miniaturized, portable readout electronics with real-time signal processing capability that can stream data to a remote device over Bluetooth. The potential of graphene textiles in wearable eye tracking and eye-operated remote object interaction is demonstrated by controlling a mouse cursor on screen for typing with a virtual keyboard and enabling navigation of a four-wheeled robot in a maze, all utilizing five different eye motions initiated with a single channel EOG acquisition. Typing speeds of up to six characters per minute without prediction algorithms and guidance of the robot in a maze with four 180° turns were successfully achieved with perfect pattern detection accuracies of 100% and 98%, respectively.
眼动研究以及对由此产生的生物电位的测量,即眼电图(EOG),在活动识别、情境感知、移动人机和人机交互(HCI/HMI)以及个人医疗设备等领域的应用中可能会得到越来越广泛的应用;前提是通过真正可穿戴、低成本且易于使用的技术实现对眼睛活动的无缝感知及其处理。本研究展示了一种替代笨重且昂贵的基于摄像头的眼动追踪系统的方法,并首次报道了一种基于石墨烯织物的个人辅助设备的开发。这个独立的可穿戴原型包括一个带有柔软石墨烯织物电极的头带,该电极克服了传统“湿”电极的局限性,以及具有实时信号处理能力的小型化、便携式读出电子设备,该设备可以通过蓝牙将数据传输到远程设备。通过利用单通道EOG采集引发的五种不同眼动,在屏幕上控制鼠标光标以使用虚拟键盘打字,并在迷宫中引导四轮机器人导航,展示了石墨烯织物在可穿戴眼动追踪和眼控远程对象交互方面的潜力。在没有预测算法的情况下,打字速度达到每分钟六个字符,并且在有四个180°转弯的迷宫中引导机器人时,模式检测准确率分别成功达到了100%和98%。