摘 要

步态分析（gait analysis）是对步行的规律以生物学和运动学的方法对相关的步态参数进行采集和分析的检查方法，揭示了步态异常的关键环节及影响因素。在指导康复，临床诊断，疗效评估及机理研究等医学领域有着重要意义和价值，步态参数通常包括：步态周期，运动学参数，动力学参数，肌电活动参数和能量代谢参数等。在实际的应用过程中常使用观察法和测量法，观察法对于结果的分析没有具体数据及参数的支撑，只能定性地判断，测量法在没有专业仪器的情况下只能采用人工测量的方式进行，效率低下，人为影响因素较多。而专业设备通常有着价格昂贵，体积庞大，便携性差的特点。在我国缺少相关的价格低廉，便携性较好的步态分析设备。

本文利用基于数据采集卡，STM32单片机及相关传感器构成的硬件采集模块，基于LabVIEW的数据采集及分析模块相结合构成了基于LabVIEW的多元人体数据采集系统。

硬件采集模块分别利用数据采集卡和STM32单片机的硬件优势，结合传感器的实际情况完成了对肌电信号，加速度陀螺仪信号和心率血氧信号的采集。利用数据采集卡完成对表面肌电信号的模拟信号采集，能够得到原始的肌电信号方便后期对波形的分析和处理。对于加速度陀螺仪信号及心率和血氧数据的采集则采用STM32和对应的传感器来完成，加速度和陀螺仪数据及心率和血氧数据均为数字信号，便于对数据的分析处理，通信方便，减轻了LabVIEW对数据处理的负担，降低程序的复杂程度。基于LabVIEW的数据采集系统实现了对信号的实时采集。利用STM32单片机基于C 编程实现对加速度陀螺仪数据及心率血氧的初步滤波计算。基于LabVIEW的数据采集及分析系统实现对心电信号的滤波和分析，对加速度陀螺仪信号和心率血氧信号进行分析计算得到步态周期及运动学参数，肌电活动参数和能量参数。最后通过测量法得到实际的参数和系统采集数据进行对比。

关键词：步态分析；LabVIEW；多元人体数据采集；STM32

Abstract

Gait analysis is an inspection method that collects and analyzes related gait parameters based on biological and kinematic methods for the rules of walking, revealing the key links and influencing factors of abnormal gait. It has important significance and value in guiding rehabilitation, clinical diagnosis, curative effect evaluation and mechanism research. Gait parameters usually include: gait cycle, kinematic parameters, dynamic parameters, electromyographic activity parameters and energy metabolism parameters. Observation and measurement methods are often used in the actual application process. The observation method has no specific data and parameter support for the analysis of the results and can only be judged qualitatively. The measurement method can only be carried out by manual measurement without professional instruments. , Low efficiency and many human factors. Professional equipment is usually expensive, bulky, and poorly portable. In my country, there is a lack of relevant gait analysis equipment with low price and good portability.

This article uses a hardware acquisition module based on a data acquisition card, STM32 single-chip microcomputer and related sensors, and a combination of LabVIEW-based data acquisition and analysis modules to form a LabVIEW-based multiple human data acquisition system.

The hardware acquisition module uses the hardware advantages of the data acquisition card and the STM32 single-chip microcomputer to complete the acquisition of myoelectric signals, acceleration gyroscope signals and heart rate blood oxygen signals in combination with the actual conditions of the sensors. The data acquisition card is used to complete the analog signal acquisition of the surface EMG signal, and the original EMG signal can be obtained to facilitate the later analysis and processing of the waveform. For acceleration gyroscope signal and heart rate and blood oxygen data collection, STM32 and corresponding sensors are used to complete. Acceleration and gyroscope data, heart rate and blood oxygen data are all digital signals, which is convenient for data analysis and processing, and communication is convenient. This reduces the burden of LabVIEW on data processing and reduces the complexity of the program. The LabVIEW-based data acquisition system realizes real-time acquisition of signals. Using STM32 single-chip microcomputer based on C programming to realize the preliminary filtering calculation of acceleration gyroscope data and heart rate blood oxygen. The data acquisition and analysis system based on LabVIEW realizes the filtering and analysis of the ECG signal. The acceleration gyroscope signal and the heart rate blood oxygen signal are analyzed and calculated to obtain the gait cycle and kinematic parameters, electromyographic activity parameters and energy parameters. Finally, the actual parameters obtained by the measurement method are compared with the data collected by the system.

Key Words：Gait analysis；LabVIEW；Multiple human body data collection；STM3

目录

第1章 绪论 1

1.1背景及意义 1

1.2相关人体生理信号简述 1

1.2.1心率信号 1

1.2.2血氧饱和度（SpO2）信号 2

1.2.3表面肌电信号（sEMG） 2

1.3论文结构 3

第二章 开发平台及总体设计方案 4

2.1开发平台介绍 4

2.2整体系统方案 5

2.2.1硬件采集模块 5

2.2.2基于C 的数据采集分析模块 7

2.2.3基于LabVIEW的数据采集分析模块 7

2.3本章小结 8

第三章 硬件采集模块 9

3.1硬件概述 9

3.2心率血氧信号采集模块 10

3.3加速度陀螺仪传感器 11

3.4肌电信号采集模块 12

第四章 数据采集分析模块 14

4.1基于C的数据采集分析模块 14

4.1.1IIC通信模式简述 14

4.1.2信号采集及初步处理 16

4.2基于LabVIEW的数据采集分析系统 17

4.2.1表面肌电信号采集分析模块 18

4.2.2加速度陀螺仪信号及心率血氧信号采集分析 20

第五章 总结与展望 22

参考文献 23

致谢 24

1. 绪论

1.1背景及意义

随着我国康复事业的发展，未来强调患者个体化需求的精准诊断治疗体系会不断完善。^[1] 步态分析是康复评定中评价在有限范围内获得独立生活能力的一项基本内容。采用目测分析或专门设备定量评测。分析神经系统或运动系统疾病影响行走能力的患者的步态及变化。 步态分析可提供患者使用下肢矫形器和步行辅助的依据。作为患者耐力或步速等训练的客观指标；分析影响步态的关节、肌肉等改变，以及运动动力学的变化，从而制定对应的康复训练计划，使病人最大限度获得独立生活能力，并可作为某些下肢矫形手术后的定量比较指标^[2] 。

观察法只能定性地判断，而测量法较为原始多为人工测量，缺少相关的专业仪器，数据获取较为麻烦。专业的步态分析实验室则采用步态分析仪进行专业地测试，数据获取具有精度高，数据全面的特点，但是其便携性较差，成本高昂。国内外就相关的方面进行了深入的研究，为更加方面快捷，精确地获取在相关参数，提出了很多新测量方法和算法，