Design And Implementation Of Data Processing And Analysis Of Rehabilitation Equipment Based On Big Data

With the development of portable rehabilitation equipment and the enhancement of user health awareness,rehabilitation medical data has shown explosive growth.Traditional medical informatization construction can no longer bear the storage and analysis of massive data.Hadoop,as the technical foundation of big data,provides distributed storage and computing capabilities.Building a new generation of medical big data platform based on Hadoop will effectively alleviate the storage and analysis of massive data.Aiming at the massive data storage and analysis challenges,with the medical data collected by the rehabilitation equipment developed in the laboratory as the background,the actual business needs of the rehabilitation equipment(gesture games,balance scales,and walkers)were first analyzed,and then refined into functional requirements Then,it analyzes the use cases of the main functional modules,and finally designs and implements a medical big data platform based on the Hadoop architecture.The platform contains four modules of data acquisition,storage,analysis and visualization,data acquisition module sqoop,Flume tool,data storage module using HDFS,proposed a small file consolidation scheme based on Sequence File technology.Effectively solves the problem of inefficient retrieval caused by the direct storage of medical small pictures.On the one hand,the data analysis module uses Hive to build a data warehouse,uses the dimensional modeling method to carry out statistical analysis of indicators,and on the other hand,uses the correlation algorithm Apriori,through which to excavate the correlation between diseases,and more comprehensively helps doctors understand the type of disease in patients.In order to solve the problem of low computing performance caused by the native Apriori algorithm,the algorithm is changed to a distributed algorithm based on Map Reduce.Experiments show that the time required to calculate the astanda’s Apriori algorithm is 18 to 20 times that of distributed form,which effectively proves the efficiency of the distributed algorithm.The data visualization system uses the SSM framework as the background,and the front end uses the ECharts component to present indicator statistics to the user in the form of a dynamic chart.The medical big data platform based on Hadoop,with its high availability,high reliability,and flexible expansion,effectively guarantees the storage and calculation of massive data.By performing a functional test and a performance test on the system,the system can provide stable services to the outside world and achieve the expected design goals.