Design Of A Real-time Acquisition System For Surgery Physiological Monitoring Signals And Analysis Of The Depth Of Anesthesia

In order to conduct clinical research deeply, many medical research institutions are required to collect a large amounts of operation data to establish the operation medical case database, which requires efficient data collection methods. These physiological signals include heart rate, Bispectral index(BIS), Electrocardiogram(EEG), electroencephalogram(ECG), respiratory rate, oxygen concentration, temperature, skin conductivity, etc. These reflect the main characteristics of the patient’s physical activity. During the surgery, the patient is under anesthesia, and the monitoring physiological signals could reflect the patient’s response to operation, record and restore the whole physiological state in the surgery, which are essential information doctors take as reference to undertake the surgery. Currently, most surgery data collection depends on manual methods to compete it. This approach wastes a lot of manpower and time. At the same time, the anesthesia monitors on the market is expensive and assessment of depth of anesthesia(DOA)algorithm is secret for the public, which improves the cost of surgical instruments and medical burden on patients.For the issues, the main work is shown as follows.(1) For problems of manual collection methods, we propose a real-time acquisition program, established a WLAN-based wireless network to achieve the goal of data wireless transmission. A MySQL-based database system was designed for storing surgery physiological data, which can be accessed through a web browser.(2) In the practical hospital environment, test for the real-time physiological signal acquisition system has been undertaken using Wifi Analyzer and IPerf tools, which shows that the wireless signal strength, data transmission speed and accuracy have reached the application requirements.(3) An DOA assessment algorithm based on permutation entropy(PE)was proposed, which has high noise immunity, low time complexity and quick computing speed. Utilizing this algorithm, 20 cases of surgical anesthesia physiological data has been assessed and evaluated. Results proved that the effectiveness and superiority of the algorithm compared with the BIS, expert assessment of conscious level.This thesis presents an automatical physiological signals monitoring system, which can conduct data recording,transmission, storage, management and the establishment of a database. And also some analysis based on the data is undertaken to assess the depth of anesthesia(DOA),which reflects the DOA of patients correctly.