Sisti Jonathan A, Christophe Brandon, Seville Audrey Rakovich, Garton Andrew L A, Gupta Vivek P, Bandin Alexander J, Yu Qiping, Pullman Seth L
Columbia University College of Physicians and Surgeons, Columbia University, New York, NY, USA.
Department of Computer Science, Columbia College, USA.
J Neurosci Methods. 2017 Jan 1;275:50-54. doi: 10.1016/j.jneumeth.2016.11.004. Epub 2016 Nov 10.
Digital analysis of writing and drawing has become a valuable research and clinical tool for the study of upper limb motor dysfunction in patients with essential tremor, Parkinson's disease, dystonia, and related disorders. We developed a validated method of computerized spiral analysis of hand-drawn Archimedean spirals that provides insight into movement dynamics beyond subjective visual assessment using a Wacom graphics tablet. While the Wacom tablet method provides robust data, more widely available mobile technology platforms exist.
We introduce a novel adaptation of the Wacom-based method for the collection of hand-drawn kinematic data using an Apple iPad. This iPad-based system is stand-alone, easy-to-use, can capture drawing data with either a finger or capacitive stylus, is precise, and potentially ubiquitous.
The iPad-based system acquires position and time data that is fully compatible with our original spiral analysis program. All of the important indices including degree of severity, speed, presence of tremor, tremor amplitude, tremor frequency, variability of pressure, and tightness are calculated from the digital spiral data, which the application is able to transmit.
While the iPad method is limited by current touch screen technology, it does collect data with acceptable congruence compared to the current Wacom-based method while providing the advantages of accessibility and ease of use.
The iPad is capable of capturing precise digital spiral data for analysis of motor dysfunction while also providing a convenient, easy-to-use modality in clinics and potentially at home.
对书写和绘图进行数字分析已成为研究特发性震颤、帕金森病、肌张力障碍及相关疾病患者上肢运动功能障碍的重要研究和临床工具。我们开发了一种经过验证的计算机化螺旋分析方法，用于对手绘阿基米德螺旋线进行分析，该方法借助数位绘图板，能够深入了解运动动态，而不仅仅依赖主观视觉评估。虽然数位绘图板方法能提供可靠数据，但更广泛使用的移动技术平台也已存在。
我们引入了一种基于数位绘图板方法的新颖改进，利用苹果iPad收集手绘运动学数据。这种基于iPad的系统独立运行、易于使用，能用手指或电容式触控笔捕捉绘图数据，精确且可能无处不在。
基于iPad的系统获取的位置和时间数据与我们原来的螺旋分析程序完全兼容。所有重要指标，包括严重程度、速度、震颤的存在、震颤幅度、震颤频率、压力变化和紧密程度，都可从应用程序能够传输的数字螺旋数据中计算得出。
虽然iPad方法受当前触摸屏技术限制，但与当前基于数位绘图板的方法相比，它收集的数据具有可接受的一致性，同时具备可及性和易用性优势。
iPad能够捕捉精确的数字螺旋数据以分析运动功能障碍，同时在诊所乃至可能在家中提供一种方便、易用的方式。
