Study And Design Of Asynchronous Cache Handling Mechanism Based On Wireless Real-time EEG Monitoring System

With the development of society,people pay more attention to the research of brain science.EEG monitoring technology,with the advantages of non-invasive,low-cost and high time resolution,has become a significant tool for the diagnosis and treatment of brain diseases by acquisition and analysis of EEG signals.Particularly,real-time EEG monitoring technology plays a crucial role in the locating and diagnosis of paroxysmal brain disease.Meanwhile,realtime EEG monitoring can support the treatment and prognosis with physical stimulation.Therefore,real-time EEG monitoring technology is very valuable.Although the traditional cable transmission mode restricts the flexibility and practicability of EEG monitoring,the introduction of wireless communication technology has brought great convenience.Research on wireless real-time EEG monitoring system has become a hotspot.As a delay-sensitized application,real-time EEG monitoring system's real-time performance is critical.This paper focuses on the real-time performance of the wireless EEG monitoring.After analyzing the system data cache strategy and wireless communication mechanism,it presents an efficient asynchronous cache handling mechanism(ACHM),which can achieve real-time EEG signal while provide a feasible way to realize medical electrical stimulation demand.The main contents of this paper are exhibited as follows:(1)Ease the fluctuation problem of wireless data flow: study and analyze the data caching mechanism.According to the system requirements and the fluctuation of wireless data stream,the ring-memory is introduced to read/write asynchronously.With optimized parameters,the management and operation of the ring-memory can be simplify and further improve the working efficiency.The ring-memory ensures efficient read/write,which can obtain continuous data.(2)Solve the conflict problem of upload requests from multi-terminal: study medium access control principle of wireless LAN.Combined with the real-time and high throughput requirements of real-time EEG monitoring,analysis DCF and PCF mechanism on MAC layer and use the optimized PCF as the data transmission control strategy.In the consideration of operation of multi-terminal,the optimized PCF introduces priority polling and dynamically retry-limit adjustment,which ensures orderly transmission with multi-terminal,effectively reduction of wireless data delay and the improvement of wireless network throughput.Finally,the data transmission performance of ACHM is simulated with NS2,then the system function and performance are tested in a hardware platform.The results show that the upload and download function runs well,which means ACHM is able to support EEG acquisition and stimulation function for a real-time EEG monitoring.In addition,ACHM can get continuous data in the collecting process.In the data transmission process,it decreases the data delay by at least 5% and 1% respectively compared with DCF and PCF.Furthermore,ACHM has a higher rate of throughput,and with the increase of network traffic load,it performs relatively better.This design achieves the expected goal and laid the foundation for the followup study of the EEG signals.