IEEE Trans Neural Syst Rehabil Eng. 2024;32:2983-2992. doi: 10.1109/TNSRE.2024.3443073. Epub 2024 Aug 20.
Individuals with high-level spinal cord injuries often face significant challenges in performing essential daily tasks due to their motor impairments. Consequently, the development of reliable, hands-free human-computer interfaces (HCI) for assistive devices is vital for enhancing their quality of life. However, existing methods, including eye-tracking and facial electromyogram (FEMG) control, have demonstrated limitations in stability and efficiency. To address these shortcomings, this paper presents an innovative hybrid control system that seamlessly integrates gaze and FEMG signals. When deployed as a hybrid HCI, this system has been successfully used to assist individuals with high-level spinal cord injuries in performing activities of daily living (ADLs), including tasks like eating, pouring water, and pick-and-place. Importantly, our experimental results confirm that our hybrid control method expedites the performance in pick-place tasks, achieving an average completion time of 34.3 s, which denotes a 28.8% and 21.8% improvement over pure gaze-based control and pure FEMG-based control, respectively. With practice, participants experienced up to a 44% efficiency improvement using the hybrid control method. This state-of-the-art system offers a highly precise and reliable intention interface, suitable for daily use by individuals with high-level spinal cord injuries, ultimately enhancing their quality of life and independence.
患有高水平脊髓损伤的个体由于运动障碍，常常在执行基本日常任务方面面临重大挑战。因此，开发可靠的、免手操作的人机界面（HCI）对于辅助设备对于提高他们的生活质量至关重要。然而，现有的方法，包括眼动追踪和面部肌电图（FEMG）控制，在稳定性和效率方面表现出了局限性。为了解决这些缺点，本文提出了一种新颖的混合控制系统，无缝集成了注视和 FEMG 信号。当作为混合 HCI 部署时，该系统已成功用于协助患有高水平脊髓损伤的个体进行日常生活活动（ADL），包括进食、倒水和取放等任务。重要的是，我们的实验结果证实，我们的混合控制方法加快了取放任务的完成速度，平均完成时间为 34.3 秒，分别比纯基于注视的控制和纯基于 FEMG 的控制提高了 28.8%和 21.8%。经过练习，参与者使用混合控制方法的效率最高可提高 44%。这个最先进的系统提供了一个高度精确和可靠的意图接口，适合患有高水平脊髓损伤的个体日常使用，最终提高他们的生活质量和独立性。
