Development of smart cure and urgent medical aid system for tracking of chronic pulmonary patients with mobile communication technology

Chronic lung disease care system that is developed in J2ME provides real-time tracking of diagnostic asthma and COPD patients in the home environment with intelligent and wireless facilities. The properties of the developed system, the performance analysis and the practice results on real patients are presented in this study. The patient's pulmonary function test values are measured with spirometry, the oxygen concentration (SPO2) and pulse rate are measured with pulse oximetry in the system. Then, the data are transferred to the smart phone through bluetooth virtual serial port protocol. The data are classified with two five-input-hidden layer feed-forward multi-layer back propagation neural network (MLP). Input attributes of MLP that works on smart phone are FEV1, FVC, FEV1/FVC, FEF25-75, PEF. Output classification results are normal, obstructive or restrictive. The classification results and the measured values are shown in the smart phone screen. General packet radio service, wireless LAN, or third generation based wireless networks are used to send the pulmonary function test results to remote database through XML based web service. If the measurement results contain an emergency condition, a recommendation-based SMS message is sent to the patient and also an information-based SMS message is sent to the doctor. In addition, all patient data and flow-volume and volume-time graph can be visualized via normal and mobile web pages that are securely entered. Furthermore, if necessary, the doctor can send e-mail to the patient. In this doctorate study, the test results of 486 patients, obtained from Atatürk Chest Diseases and Thoracic Surgery Training and Research Hospital in Ankara/Turkey, are used as training and test set in algorithm. Algorithm has 98,7% accuracy, 97,83% specificity, 97,63% sensitivity, and 0,946 correlation values. When this study is compared with previous studies, it is observed that there are an improvement in differentiation between asthma and COPD and the facilitation of the tracking of chronic pulmonary patients with smart and mobile system