Vianello Andrea, Chittaro Luca, Burigat Stefano, Budai Riccardo
Human-Computer Interaction Lab, Department of Mathematics, Computer Science, and Physics, University of Udine, Udine, Italy.
Human-Computer Interaction Lab, Department of Mathematics, Computer Science, and Physics, University of Udine, Udine, Italy.
Comput Methods Programs Biomed. 2017 May;143:35-47. doi: 10.1016/j.cmpb.2017.02.012. Epub 2017 Feb 22.
Human motor skills or impairments have been traditionally assessed by neurologists by means of paper-and-pencil tests or special hardware. More recently, technologies such as digitizing tablets and touchscreens have offered neurologists new assessment possibilities, but their use has been restricted to a specific medical condition, or to stylus-operated mobile devices. The objective of this paper is twofold. First, we propose a mobile app (MotorBrain) that offers six computerized versions of traditional motor tests, can be used directly by patients (with and without the supervision of a clinician), and aims at turning millions of smartphones and tablets available to the general public into data collection and assessment tools. Then, we carry out a study to determine whether the data collected by MotorBrain can be meaningful for describing aging in human motor performance.
A sample of healthy participants (N= 133) carried out the motor tests using MotorBrain on a smartphone. Participants were split into two groups (Young, Old) based on their age (less than or equal to 30 years, greater than or equal to 50 years, respectively). The data collected by the app characterizes accuracy, reaction times, and speed of movement. It was analyzed to investigate differences between the two groups.
The app does allow measuring differences in neuromotor performance. Data collected by the app allowed us to assess performance differences due to the aging of the neuromuscular system.
Data collected through MotorBrain is suitable to make meaningful distinctions among different kinds of performance, and allowed us to highlight performance differences associated to aging. MotorBrain supports the building of a large database of neuromotor data, which can be used for normative purposes in clinical use.
传统上，人类运动技能或损伤是由神经科医生通过纸笔测试或特殊硬件进行评估的。最近，诸如数字化平板电脑和触摸屏等技术为神经科医生提供了新的评估可能性，但它们的使用仅限于特定的医疗状况，或仅限于手写笔操作的移动设备。本文的目的有两个。首先，我们提出了一个移动应用程序（MotorBrain），它提供了六种传统运动测试的计算机化版本，可以由患者直接使用（有或没有临床医生的监督），旨在将数百万普通大众可用的智能手机和平板电脑转变为数据收集和评估工具。然后，我们进行了一项研究，以确定MotorBrain收集的数据是否能够有意义地描述人类运动表现中的衰老情况。
一组健康参与者（N = 133）使用智能手机上的MotorBrain进行运动测试。参与者根据年龄分为两组（年轻组、老年组）（分别为小于或等于30岁、大于或等于50岁）。该应用程序收集的数据表征了准确性、反应时间和运动速度。对其进行分析以研究两组之间的差异。
该应用程序确实能够测量神经运动表现的差异。该应用程序收集的数据使我们能够评估由于神经肌肉系统衰老导致的表现差异。
通过MotorBrain收集的数据适合在不同类型的表现之间做出有意义的区分，并使我们能够突出与衰老相关的表现差异。MotorBrain支持建立一个大型神经运动数据库，可用于临床的标准化目的。
