首页> 中文期刊> 《北京生物医学工程》 >基于微机电系统加速度传感器的上肢运动功能评价系统

基于微机电系统加速度传感器的上肢运动功能评价系统

         

摘要

目的 设计一种基于微机电系统(micro-electro-mechical system,MEMS)加速度传感器的上肢运动功能评价系统,通过平滑度和加速度均方根指标精确客观地评价脑卒中患者上肢运动的功能障碍.方法 本系统主要包括ATmega128单片机的通信模块,可进行上下位机的数据传输,保存数据;ADXL345加速度传感器的数据采集模块,实时采集患者的上肢运动加速度,本系统造价低、便于携带、测试高效.选择6例脑卒中上肢偏瘫康复患者(病患组)和4例上肢健康者(健康组)进行初步测试.健康组进行零负荷定向够物运动和梯度负荷够物运动重复测试;病患组和健康组进行零负荷定向够物运动对比测试.结果 零负荷定向够物运动重复测试:健康组被试者间的平滑度(P>0.05)和加速度均方根(P>0.05)差异无统计学意义;零负荷定向够物运动的对比测试:患者与健康人员的平滑度指标差异具有统计学意义(P<0.05),加速度均方根指标差异无统计学意义(P>0.05);梯度负荷够物运动重复测试:平滑度随着负荷的增加而增长,且经一元线性回归分析,平滑度与负荷线性关系显著(P<0.001).结论 基于MEMS加速度传感器的上肢运动功能评价系统可通过平滑度定量评价脑卒中患者的上肢运动能力,并进一步得到平滑度和负荷之间呈线性关系,为后续评价脑卒中上肢偏瘫患者的康复状况,提供了新的思路.%Objective An evaluation system of upper limb movement function based on microelectro mechical system ( MEMS ) accelerometer sensor is designed to accurately and objectively evaluate the dysfunction of upper limb movement in stroke patients through the index of smoothness and root mean square of acceleration. Methods The system mainly included ATmega128 single-chip microcomputer communication module, this module could transmit data between the upper and lower computer and save the data. The system also included data acquisition module, this module could collect the patient's upper limb motion acceleration in real time by using ADXL345 acceleration sensor. The system was low cost, easy to carry and efficient in tests. Finally, six stroke patients with upper limb hemiplegia rehabilitation ( patient group) and four normal healthy adults ( healthy group ) were recruited. Healthy group performed directional motion with zero load and reduplicate tests of directional motion with gradient load. The data was contrasted between this two groups when patient group and the healthy group were tested of directional motion with zero load. Results Repeat tests of oriented motion with zero load: there were no significant differences among the smoothness ( P> 0.05) and the mean square root of acceleration ( P> 0.05) between numbers in the healthy group. Contrast test of oriented motion with zero load: there were significant differences among the smoothness ( P< 0. 05 ) and no significant differences among the mean square root of acceleration ( P> 0.05) between two groups. Repeat tests of directional motion with gradient load:smoothness increased as the load increased. And the smoothness ( P< 0.001) was significantly linear related to the load by the unitary linear regression analysis. Conclusions The evaluation system of upper limb movement function based on MEMS acceleration sensor can quantitatively evaluate the movement capacity of upper limb in stroke patients through the index of smoothness. Furthermore, the linear relationship between smoothness and load is obtained and provided a new way to evaluate the recovery of stroke patients with upper limb hemiplegia.

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