基于手功能评估系统的“腕背伸”动作定量评估

目前临床上采用基于传统量表评估和手工测量作为针对脑卒中偏瘫患者手功能康复的主要评估方法,这种方法存在误差大、依赖人力效率低下、评估结果不连续等缺陷,难以满足病人康复治疗需求.提出了一种基于多维视觉手功能康复评估系统的手功能代表性康复动作“腕背伸”的定量评估方法,采用最新的光学动作捕捉设备与计算机视觉技术对“腕背伸”动作参数进行捕捉,通过多维度精准视觉采集与智能分析,得到患者患病手与健康手运动数据并进行处理分析,给出康复评估结果.详细介绍了该系统的软硬件结构、数据采集过程、评估结果分析等,并将评估结果与传统量表结果、手工测量结果进行对比分析,实验结果满足临床所需精度要求且可以更加精准、灵活的反映病人康复情况,对传统评估方式进行补充,弥补了评估不连续性、非精准性的缺点.

Quantitative evaluation method of wrist extension based on hand function evaluation system

At present,assessment based on traditional scale and manual measure are the main methods for evaluation of hand function for stroke patient.However,due to the disadvantages of large errors,poor efficiency and discontinuous evaluation results,it's difficult for these methods to meet rehabilitation needs.This paper presents a quantitative evaluation method of wrist extension based on multidimensional vision evaluation system,the system captures action parameter using optical motion capture device and computer vision technology,it can get the motion data of patient's both hands through multidimensional vision acquisition and intelligent analysis and presents the analysis result.This paper introduces hardware and software structure of the system,data acquisition process and analysis of evaluation result in detail and the result is compared with the result of traditional scale and manual measurement.In this paper,we use the'wrist back'as an example for experiment,the result can meet the requirements of clinical accuracy and can be more accurate and flexible.This method also can make up for the shortcomings of discontinuity and non precision.