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METHOD AND APPARATUS FOR WIRELESS SENSOR NETWORK BASED INTELLIGENT FRAMEWORK FOR MOBILE REAL TIME HEALTH CARE SYSTEM.
METHOD AND APPARATUS FOR WIRELESS SENSOR NETWORK BASED INTELLIGENT FRAMEWORK FOR MOBILE REAL TIME HEALTH CARE SYSTEM.
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机译：基于无线传感器网络的移动实时健康护理系统智能框架的方法和装置。
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摘要
Health monitoring is repeatedly mentioned as one of the main application areas of Wireless Sensor Networks. Mobile Health Care is the application of mobile computing technologies for improving communication amongst patients, physicians, and other health care workers. As mobile devices have become an inseparable part of our life it can integrate health care more seamlessly to our everyday life. Sensor nodes, capable of sensing, processing, and communicating one or more vital signs, can be easily integrated into wireless personal or body area networks for mobile " health monitoring. Here, we introduce a real time mobile health monitoring framework that describes how these sensed vital signs can be analyzed with the help of data mining techniques to predict the health status of the monitored people. The framework is innovative in the sense that it applies dynamic data mining concept for inspecting the recent trends of the body signals in addition to learning patient"s historical behaviour with the help of classical data mining techniques. The invention is described by way of example with reference to the following drawings FIG. 1 of sheet 1 is schematic view of generalized real time data mining framework Where 1 denotes streamed labeled data,2 denotes real time data, 3 denotes interpreted knowledge, 4 denotes evaluated knowledge, 5 denotes workflow, 6 denotes knowledge, 7 denotes feedback, 8 denotes modeling, 9 denotes labeled data, 10 denotes streamed labeled data, 11 denotes dynamic labeled data, 12 denotes dynamic classification/predictions, 13 denotes knowledge interpretation and visualization, 14 denotes dynamic model updation/training, 15 denotes knowledge base, 16 denotes model evaluation, 17 denotes data patterns, 18 denotes dynamic rules/patterns, 19 denotes unevaluated knowledge, 20 denotes dynamic environment modeling periodic/aperiodic data (labeled/unlabelled), 21 denotes user feedback, 22 denotes adjustment of environmental parameters. Figure 2 of sheet 2 denotes the framework of Wireless Sensor Network based intelligent framework for mobile real-time health care system (WIMRHC) Where 1 denotes historical data, 2 denotes intelligent health care computing, 3 denotes preprocessing, 4 denotes feature extraction, 5 denotes data stream mining algorithm, 6 denotes historical rule base, 7 denotes static data mining module, 8 denotes smart phone computing, 9 denotes risk component analysis, 10 denotes risk evaluation, 11 denotes real time classification module, 12 denotes dynamic rule base, 13 denotes dynamic stream mining algorithm, 14 denotes feature extraction, 15 denotes preprocessing, 16 denotes dynamic data mining module, 17 denotes real time sensor data, 18 denotes risk alert.
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