Research And Development On Smart Garments For Medical Monitoring

With the development of science and technology and improvement of living condition, people's requirements on garments are more and more, wishing that garments have more functions besides heat preservation and beautiful appearance. It is people's objective that smart garments are integrated with electrical devices and have the ability of detections and reactions at the same time. Especially, we can implement effective real-time health monitoring using close-fitting garments with embedded biomedical sensors to detect biomedical signals. Therefore, people are more and more interested in research on smart garments for purpose of medical monitoring. However, currently research on this field still needs further steps. So, research on system architecture and implementation solutions of smart garments is very necessary.Firstly, we analyze research actuality of wearable computation and design architecture for smart garments facing medical monitoring following analysis on the research objective and system requirement. Based on that, we discuss two feasible solutions for its hardware implementation and their own advantages and disadvantages. In addition, in order to achieve connections between smart garments and medical centers or the Internet, we design a wearable network framework based on ZigBee and Bluetooth devices embedded in smart garments.Secondly, because biomedical signals are easily noised and biomedical sensors are embedded in garments, we probe into the requirements of ECG amplifier in smart garments. According to these requirements, we design an ECG amplifier and filtering circuit to sample and offer ECG data for further study.Thirdly, we study on how to use wavelet technology to decompose and reconstruct ECG data in order to denoise it.And then, based on ECG features, we suggest an easy way to extract ECG characteristic parameters, which can be used to evaluate the health status of the heart. We can reduce the storage cost by converting lots of ECG data to a few parameters. And we also research on non-linear analysis method such as correlation dimension for classification of normal and abnormal ECG without extracting its characteristic parameters.Finally, on the basis of ECG preprocess and parameters extraction, we research on how to integrate cardiopathy knowledge and cardiologists' experience to expert system embedded in garments to implement cardiopathy online detection and real-time warning. We suggest a solution based on fuzzy technology. It could be a reference for further study on diseases expert systems in garments for medical monitoring.The achievements in the thesis will be the basis for wearable medical monitoring devices development.