Giancardo L, Sánchez-Ferro A, Butterworth I, Mendoza C S, Hooker J M
Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139.
1] Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139 [2] Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129.
Sci Rep. 2015 Apr 16;5:9678. doi: 10.1038/srep09678.
Modern digital devices and appliances are capable of monitoring the timing of button presses, or finger interactions in general, with a sub-millisecond accuracy. However, the massive amount of high resolution temporal information that these devices could collect is currently being discarded. Multiple studies have shown that the act of pressing a button triggers well defined brain areas which are known to be affected by motor-compromised conditions. In this study, we demonstrate that the daily interaction with a computer keyboard can be employed as means to observe and potentially quantify psychomotor impairment. We induced a psychomotor impairment via a sleep inertia paradigm in 14 healthy subjects, which is detected by our classifier with an Area Under the ROC Curve (AUC) of 0.93/0.91. The detection relies on novel features derived from key-hold times acquired on standard computer keyboards during an uncontrolled typing task. These features correlate with the progression to psychomotor impairment (p < 0.001) regardless of the content and language of the text typed, and perform consistently with different keyboards. The ability to acquire longitudinal measurements of subtle motor changes from a digital device without altering its functionality may allow for early screening and follow-up of motor-compromised neurodegenerative conditions, psychological disorders or intoxication at a negligible cost in the general population.
现代数字设备和电器能够以亚毫秒级的精度监测按键的时间,或者一般来说手指的交互动作。然而,这些设备能够收集的大量高分辨率时间信息目前正被丢弃。多项研究表明,按下按钮的动作会触发明确的脑区,而这些脑区已知会受到运动功能受损状况的影响。在本研究中,我们证明与计算机键盘的日常交互可以用作观察并潜在量化精神运动障碍的手段。我们通过睡眠惯性范式在14名健康受试者中诱发了精神运动障碍,我们的分类器以0.93/0.91的ROC曲线下面积(AUC)检测到了这种障碍。该检测依赖于在无控制的打字任务期间从标准计算机键盘获取的按键保持时间衍生出的新特征。无论所输入文本的内容和语言如何,这些特征都与精神运动障碍的进展相关(p < 0.001),并且在不同键盘上表现一致。在不改变数字设备功能的情况下从其获取细微运动变化的纵向测量值的能力,可能允许以可忽略不计的成本对普通人群中的运动功能受损的神经退行性疾病、心理障碍或中毒进行早期筛查和随访。