人体静电电位信号数据对齐方法研究

Research on data alignment methods based on human electrostatic potential signals

针对多传感器检测系统相关试验中存在的多个传感器在数据采集过程中数据读取时间不同步以及采样频率不统一,导致数据对齐存在偏差,无法进行精确解算的问题,以人体静电电位信号采集试验的数据对齐操作为例,通过函数计算、波形分析、特征点提取等方法对3组不同传感器数据进行滤波清洗和对齐处理。结果表明,上述方法能够得到有效数据的起始点和终止点,解决数据采集过程中读取不同步的问题,提高了多传感器数据的对齐精度,为试验后续信号的识别提供更加准确的数据支持。所设计的数据对齐方法可应用于静电检测、运动健康、行为识别等具有多个传感器的数据采集系统中,为系统数据的对齐处理提供了有效的理论参考与方法依据。

In experiment of multi-sensor detection system,there are often problems of multiple sensors with unsynchronized data reading times and non-uniform sampling frequency in the process of data collection,which lead to the biased data alignment and the inability of accurate solution.Taking the data alignment operation for a human electrostatic potential signal acquisition experiment as an example,the filter,cleaning and alignment processing of three different sets of sensor data were carried out by using function calculation,waveform analysis and feature point extraction.The results show that the above method can obtain the starting and ending points of valid data and solve the problem of unsynchronized reading during data acquisition.At the same time,the above method improves the alignment accuracy of multi-sensor data and provides more accurate data support for the subsequent identification of signals in the experiment.The data alignment method designed in this paper can be applied to data acquisition systems with multiple sensors,such as electrostatic detection,sports and health,and behavior identification.The method provides a good theoretical reference and methodological basis for the alignment processing of system data.