A Study And Implementation Of The Medical Cloud Device Interface Based On Wireless Sensor Networks

With the development of the medical treatment,more and more disabled people hope to improve their live through intelligent medical equipments.Assistive instruments and artificial limbs became the hot topic among countries.This kind of medical equipment is developed based on artificial limbs class medical device interface and wireless transmission systems.It is of great significance to the development of the intelligence medical device.This research aims to design a cloud of medical equipment based on the combination of wireless sensor network technology and wireless sensor network interface.In other words,it aims to classify and identify the PC to the methods of electrical signals and then control the prosthetic class medical equipment effectively through the use of wireless interface to sends a large number of real-time data.The major contents are as followed:(1)By learning the features and the producing principle of multi-channel to design the collection scheme of electrical electrode on the electromyographic signal data: by using the electromyographic signal data source around the muscle surface of human arm as the signal source to set the proper record the movements and the experimental group.(2)By combining the current research status of acquisition equipment multi-channel semg and electromyographic signal interference sources: give a detailed design and optimization measures of preamplifier circuit,low pass filter circuit,trap circuit power frequency,and verify the effect through the analog circuit experiment.(3)By learning the characteristics and technological structure of wireless sensor networks and comparing several kinds of wireless sensor networks to ensure the technology solutions of wireless data transmission and network: elect CC2530 hardware module by Zigbee agreement to build a wireless transmission system,and designed the software development process,through the wireless digital transmission test results.(4)Through the research on the related theories about the signal process,design the classifier: design the classifier with the adaptive ability of self based on the contrast analysis of commonly used linear discriminant LDA nonlinear quadratic discriminantclassifier and QDA classifier carries.At the same time,put forward a cloud storage solution of electrical data,which is a lightweight cloud storage platform based on Hadoop.