基于Leap Motion的病患手评估算法研究

Research on Affected Hand Evaluation Algorithm Based on Leap Motion

手功能评估的传统方法还是基于医生和专家的主观判断,这样的方法不仅仅缺乏标准性,同时还会因为个别医生或者专家的评估标准不同,获得错误的评估结果。随着人工智能的发展,硬件的革新换代,各种算法的提出,使得利用计算机技术对手进行科学的自动的评估成为了可能。论文搭建了手功能自动评估系统,利用Leap Motion提取手各个部位在空间中的位置和方向,提出评价两手之间手势差异程度的方法,从而实现数据化后的患侧手和健康手的比较,获得患侧手手功能丧失程度。通过该项研究,可以科学地评估患侧手的病患程度,帮助医生做进一步的诊断和治疗,有助于病人尽快恢复病患手的功能。

The traditional methods to evaluate affected hands are manually done by doctors or researchers,which the manual methods lack standard for hand evaluation,and easily get error results.With the rapid developments of artificial intelligence,machines and algorithms,it is possible to evaluate affected hands with computer techniques.In this paper,automatic evaluation system is crented for hands.With Leap Motion sensors,the information including fingertips positions and directions can be obtained.Then,a method is proposed for comparing the affected hand and the normal hand to calculate and evaluate the degree of the affected hand.This system can help the doctors to perform further diagnosis and treatment for the affected hands.Furthermore,it can help patients recover the function of affected hand as soon as possible.