Research And Development Of Remote Wireless Monitoring Terminal For Intraocular Pressure Fluctuations For Home Applications

At present,the existing continuous measurement tonometers are all contact tonometers,which can be divided into invasive and non-invasive continuous measurement tonometers according to whether they are in contact with the cornea.Invasive continuous measurement tonometer has the problems of surgical risk,irreversible trauma and long-term wear;non-invasive continuous measurement tonometer needs to be attached to the surface of the eyeball,which is greatly affected by corneal rigidity and thickness,and individual differences have a significant impact on accuracy.The existing portable tonometers are all offline single-shot intraocular pressure measurement devices,lacking easy operation and remote data automatic transmission functions.The research content of this paper is the research and development of an online continuous monitoring terminal for intraocular pressure based on the integrated cloud architecture.The purpose is to make home continuous monitoring of intraocular pressure and remote monitoring and diagnosis by ophthalmologists a reality.In view of the shortcomings of existing portable tonometers in terms of ease of operation and remote data transmission,the portable rebound tonometer is used as the basis of the intraocular pressure measurement unit to develop a remote wireless monitoring terminal for intraocular pressure fluctuations for home applications.The main contents of this paper are as follows:(1)Wearable continuous measurement terminal for intraocular pressure fluctuation.Taking a hand-held tonometer as the research object,it is realized that the tonometer can adapt to the individual differences of the patient's facial morphology and is compatible with the mainstream atypical rebound tonometer.By studying the integration of the sensing layer camera,algorithm program operating environment and PC display without destroying the body structure of the rebound tonometer,theterminal infrastructure design and program environment configuration are completed.(2)Image preprocessing of intraocular pressure data.Perform grayscale,Gaussian smoothing filter,median filter,binarization and image segmentation of the intraocular pressure data image read by the Raspberry Pi to obtain the measurement eye(left/right),the number of consecutive measurements and Three types of intraocular pressure data images(mean value).Finally,the sample set is prepared to prepare for the image classification algorithm of intraocular pressure data.(3)Design of image recognition algorithm for intraocular pressure data.First,the HOG feature algorithm is used to extract the gradient information of the three types of intraocular pressure data image sample sets,and then the SVM classification algorithm is used to fit the classifier models to the three types of intraocular pressure training data to obtain three classifier models.Finally,the feature value of each intraocular pressure data image is compared with the classifier,and the result of recognizing the tonometer image data is obtained,and the recognition result is transmitted to the cloud platform through network Socket programming.(4)Design and implementation of a remote monitoring platform for intraocular pressure fluctuations.The intraocular pressure data continuously monitored by the remote wireless terminal finally needs to be presented to the user.Realize remote monitoring and visual analysis of data by studying cloud and front-end technologies.The cloud includes device gateway and back-end application development.The front-end includes real-time IOP data reading,historical IOP data query,daily average value and monthly average value,etc.The remote monitoring terminal for intraocular pressure fluctuations developed in this paper is portable,accurate and real-time.