Lee Seungho, Lee Sangkon
School of Future Technology, Korea University of Technology and Education, Choenan 31253, Republic of Korea.
School of Industrial Management, Korea University of Technology and Education, Choenan 31253, Republic of Korea.
Sensors (Basel). 2025 Jul 23;25(15):4555. doi: 10.3390/s25154555.
Lou Gehrig's disease, also known as ALS, is a progressive neurodegenerative condition that weakens muscles and can lead to paralysis as it progresses. For patients with severe paralysis, eye-tracking devices such as eye mouse enable communication. However, the equipment is expensive, and the calibration process is very difficult and frustrating for patients to use. To alleviate this problem, we propose a simple and efficient method to type texts intuitively with graphical guidance on the screen. Specifically, the method detects patients' eye blinks in video frames to navigate through three sequential steps, narrowing down the choices from 9 letters, to 3 letters, and finally to a single letter (from a 26-letter alphabet). In this way, a patient is able to rapidly type a letter of the alphabet by blinking a minimum of three times and a maximum of nine times. The proposed method integrates an API of large language model (LLM) to further accelerate text input and correct sentences in terms of typographical errors, spacing, and upper/lower case. Experiments on ten participants demonstrate that the proposed method significantly outperforms three state-of-the-art methods in both typing speed and typing accuracy, without requiring any calibration process.
肌萎缩侧索硬化症（ALS），也被称为卢伽雷氏病，是一种进行性神经退行性疾病，会使肌肉逐渐衰弱，并随着病情发展导致瘫痪。对于严重瘫痪的患者来说，诸如眼控鼠标之类的眼动追踪设备能够实现交流。然而，这类设备价格昂贵，而且校准过程对患者而言非常困难且令人沮丧。为缓解这一问题，我们提出一种简单高效的方法，可在屏幕图形引导下直观地输入文本。具体而言，该方法通过检测视频帧中患者的眨眼动作，分三个连续步骤进行操作，将选择范围从9个字母逐步缩小到3个字母，最后确定为单个字母（来自26个字母的字母表）。这样一来，患者最少眨眼三次、最多眨眼九次就能快速打出字母表中的一个字母。所提出的方法集成了大语言模型（LLM）的应用程序编程接口（API），以进一步加快文本输入速度，并在校对错误、间距以及大小写方面纠正句子。对10名参与者进行的实验表明，所提出的方法在打字速度和打字准确性方面均显著优于三种现有最先进的方法，且无需任何校准过程。
