Design And Application Of Multi-channel Sleep Monitoring System

With the quickening of the pace of life and the increasing of the life pressure,the sleep disorders are on the rise.The long-term sleep disorders can cause a lot of inconvenience and even cause illness,therefore,it is very important to carry out sleep monitoring effectively and to intervene in time.However,the existing sleep monitoring equipment is generally relatively large and expensive medical equipment,these machines only apply to large hospitals,and the data collected by these devices are closed not allow scientific research personnel to read and analyze them,this is bad for data sharing.Aiming at the above problems,this paper designs a multi-channel sleep monitoring system.The following is the main research work of this article.Firstly,combined with the acquisition demand and various technical indexes,the multi-channel sleep monitoring system is designed and constructed on the basis of in-depth theoretical research.The system includes the superior machine part and the inferior machine part.The inferior machine has designed a magnifying module,which can amplify the acquisition signal.The 16-bit acquisition card is selected as the acquisition device to collect the related physiological signals of sleep.The inferior machine connects with the superior machine through the USB interface to complete the transmission of data and commands.these datas received from the inferior machine are stored,displayed,played back,or filtered by the upper computer system.Secondly,the complete sleep related physiological signal experiment scheme and detailed experimental procedure are designed.Students aged between 20 and 28 years old were selected as subjects,and data collection was conducted on the subjects’ short-term sleep.The collected data is stored in the USB file and the system details the format of the USB file,it is convenient for researchers to read and analyze data.Finally,the data collected in the experiment were applied and analyzed,and the energy characteristics of eeg were extracted,and the entropy characteristics of the sleep related physiological signals were extracted.By using the support vector machine theory,the extracted characteristic parameters were trained and verified,and the sleep state of the subjects was judged.