一种基于主成分分析法的多维表面肌电信号假手控制方法

• Format: Patent
• Language: Chinese
• Published: 25.12.2020
• Subjects: CALCULATING; CHAMBERS PROVIDED WITH MANIPULATION DEVICES; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HAND TOOLS; HANDLING RECORD CARRIERS; MANIPULATORS; PERFORMING OPERATIONS; PHYSICS; PORTABLE POWER-DRIVEN TOOLS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; TRANSPORTING

本发明公开了一种基于主成分分析法的多维表面肌电信号假手控制方法，包括如下步骤：首先将设有24通道阵列肌电传感器的臂环佩戴至受试者前臂，将五个手指关节姿态传感器分别佩戴在受试者拇指的远节指骨和其余手指的中节指骨处；受试者进行五指独立弯曲伸展训练，同时采集肌电传感阵列数据与手指关节姿态传感器数据；使用主成分分析方法对肌电传感数据进行解耦，组成手指运动训练集；训练完毕后将佩戴在手指上的传感器移除；采取神经网络方法对上述手指运动训练集进行数据拟合，构建手指连续运动预测模型；使用手指连续运动模型预测当前手指的弯曲角度。本发明能够克服离散动作模态分类的非连贯性，最终达到对假手更加平滑流畅的控制。 The present invention discloses a multi-dimensional surface electromyogram signal prosthetic hand control method based on principal component analysis. The method comprises the following steps. Wear an armlet provided with a 24-channel array electromyography sensor to a front arm of a subject, and respectively wear five finger joint attitude sensors at a distal phalanx of a thumb and at middle phalanxes of remaining fingers of the subject. Perform independent bending and stretching training on the five fingers of the subject, and meanwhile, collect data of an array electromyography sensor and data of the finger joint attitude sensors. Decouple the data of the array electromyography sensor by principal component analysi