Classification of hand preshaping in persons with stroke using Linear Discriminant Analysis
Classification of hand preshaping in persons with stroke using Linear Discriminant Analysis
复制标题
使用线性判别分析对中风患者手部预整形进行分类
DOI：
--
复制
发表时间：
2012
期刊：
影响因子：
--
通讯作者：
S. Adamovich
中科院分区：
文献类型：
--
作者：
Saumya Puthenveettil;G. Fluet;Q. Qiu;S. Adamovich
目的：本研究描述了分析手的预成形使用线性判别分析（LDA）预测手的形成过程中达到和掌握任务的偏瘫手，一系列的上肢运动干预治疗。本研究的目的是使用手姿势分类作为评估上肢康复治疗（如虚拟现实（VR）治疗和传统物理治疗）有效性的额外工具。分别对训练前后的偏瘫手和健手进行了分类误差分析。方法：8名脑卒中患者参加为期两周的上肢运动训练。四名受试者接受了交互式VR电脑游戏的训练，四名受试者接受了强度相似的临床物理治疗程序的训练。在训练之前和训练之后，使用CyberGlove®在运动学伸手抓握测试期间测量受试者的手指关节角度，并且使用trackSTAR™系统测量臂关节角度。结果如下：受试者的未受损的手preshape到目标对象具有更高的准确性比偏瘫的手表示较低的分类错误。改善偏瘫手的预成形精度和时间，以达到最小误差。结论：手预塑形的分类可以提供对由机器人促进的虚拟模拟训练课程或传统物理治疗引起的运动性能的改善的洞察。
Objective: This study describes the analysis of hand preshaping using Linear Discriminant Analysis (LDA) to predict hand formation during reaching and grasping tasks of the hemiparetic hand, following a series of upper extremity motor intervention treatments. The purpose of this study is to use classification of hand posture as an additional tool for evaluating the effectiveness of therapies for upper extremity rehabilitation such as virtual reality (VR) therapy and conventional physical therapy. Classification error for discriminating between two objects during hand preshaping is obtained for the hemiparetic and unimpaired hands pre and post training. Methods: Eight subjects post stroke participated in a two-week training session consisting of upper extremity motor training. Four subjects trained with interactive VR computer games and four subjects trained with clinical physical therapy procedures of similar intensity. Subjects' finger joint angles were measured during a kinematic reach to grasp test using CyberGlove® and arm joint angles were measured using the trackSTAR™ system prior to training and after training. Results: The unimpaired hand of subjects preshape into the target object with greater accuracy than the hemiparetic hand as indicated by lower classification errors. Hemiparetic hand improved in preshaping accuracy and time to reach minimum error. Conclusion: Classification of hand preshaping may provide insight into improvements in motor performance elicited by robotically facilitated virtually simulated training sessions or conventional physical therapy.