计算机应用与软件Issue(8)：166-169,4.DOI:10.3969/j.issn.1000-386x.2015.08.039
基于机器视觉的抓握状态模型及其适用性
GRASP STATE MODEL AND ITS APPLICABILITY BASED ON COMPUTER VISION
摘要
Abstract
For digitising the hand movement of patients with hand function dysfunctions during rehabilitation, we presented that to recognise the hand state with a grasp state model, and analysed the applicability and robustness of the model by experiments.First, we presented the hand grasp state model, including the grasping objects, the types of hand grasp and the determination process of hand grasping state.Subsequently, we tracked using Leap Motion the hand movements of five testees when they grasping the ARAT objects, and analysed the applicability of the grasp state model.Finally, we analysed the effect of grasping objects size, hand differences and grasping angels on the stability of the model with the parameters of dispersion of the model in experiment.Experimental results showed that the average relative standard deviation of model parameters in experiment was 0.637, and the grasp state model has good applicability and robustness.Using computer vision-based grasp state model to reorganise the hand state basically meets the requirements of high track accuracy and rapid processing speed.关键词
Leap Motion/红外跟踪/抓握和捏握/抓握状态模型Key words
Leap Motion/Infrared tracking/Grasp and grip/Grasp state model分类
信息技术与安全科学引用本文复制引用
林燕姿,赵翠莲,范志坚,罗林辉..基于机器视觉的抓握状态模型及其适用性[J].计算机应用与软件,2015,(8):166-169,4.基金项目
上海市科委重点科技攻关项目（子课题号13DZ1941607）。 （）
