CN102708721A - Analog medical care teaching system based on dynamic symptom reaction system - Google Patents
Analog medical care teaching system based on dynamic symptom reaction system Download PDFInfo
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- CN102708721A CN102708721A CN2012102017760A CN201210201776A CN102708721A CN 102708721 A CN102708721 A CN 102708721A CN 2012102017760 A CN2012102017760 A CN 2012102017760A CN 201210201776 A CN201210201776 A CN 201210201776A CN 102708721 A CN102708721 A CN 102708721A
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Abstract
The invention provides an analog medical care teaching system solution based on a dynamic symptom reaction system. The dynamic symptom reaction system based on a model recognition algorithm can actually simulate clinical reactions of a human body in different treatment operations under different vital sign environments for a case, a mode recognition flow of the dynamic symptom reaction system based on the mode recognition algorithm for one case consists of information acquiring, pre-processing, designing of a classifier, decision making and post-processing, the designing of the classifier is completed in case generation tool software of the system, a great amount of clinical physiological data samples are inputted for training, the principle of the disease characteristics can be generally determined through the samples, the specific parameters of the classifier can be determined, a dynamic symptom reaction human-computer interaction system realizes the information acquiring, pre-processing, decision making and post-processing of model recognition, treatment measures to be recognized are classified and decided, the dynamic symptom reaction human-computer interaction system drives an analog person to have dynamic reaction through an embedded-type control system, and an analog guarding instrument is connected with the analog person to display symptom physiological and disease information in real time.
Description
Technical field
Technical scheme of the present invention belongs to simulation medical educational technical field, is a kind of simulation medical care tutoring system solution, is used for the real standard of medical science simulation teching of medical education universities and colleges.
Background technology
The accuracy of identification that human body various environmental characteristics to external world change is not high; But can be more enough accurate inadequately; Also promptly fuzzy notion is made a response exactly, and dynamically illness reactive system technology is described this complicated system with pattern-recongnition method, sets up rational mathematical model and comes this blooming of researching human body physiological reaction; And can discern rapidly and accurately the treatment measure, satisfy need of teaching.
Summary of the invention
The objective of the invention is to be difficult to the physiology that simulates real clinical patient true to nature and the present situation of pathological data in order to solve present simulation medical care tutoring system on the market, its beneficial effect is to have significantly improved the medical education means.
Native system provides the simulation medical care tutoring system solution of a cover based on dynamic illness reactive system; Realized case under different vital sign environment based on the dynamic illness reactive system of algorithm for pattern recognition, real simulated goes out the clinical response of human body when different treatment operations.
Description of drawings
Fig. 1 is a systematic schematic diagram of the present invention.
Fig. 2 is a dynamic illness reactive system pattern-recognition process flow diagram of the present invention.
Embodiment
Dynamic illness reactive system based on algorithm for pattern recognition is as shown in Figure 2 for the pattern-recognition flow process of a case; By information obtain, pre-service, classifier design, decision-making and several parts of aftertreatment form; Classifier design is accomplished in the case Core Generator software of system; Import a large amount of clinical physiological data samples and train, can roughly confirm the regularity of pathological characters, confirm the concrete parameter of sorter by these samples; In Fig. 1 dynamically illness reaction man-machine interactive system implementation pattern identified information obtain, pre-service, decision-making and aftertreatment; Categorised decision is carried out in treatment measure to be identified, and dynamically illness reaction man-machine interactive system drives the anthropomorphic dummy through embedded control system and produces dynamic response, and the simulation monitor links to each other with the anthropomorphic dummy and shows illness physiology and pathological information in real time.
Claims (1)
1. as shown in Figure 2 for the pattern-recognition flow process of a case based on the dynamic illness reactive system of algorithm for pattern recognition; By information obtain, pre-service, classifier design, decision-making and several parts of aftertreatment form; Classifier design is accomplished in the case Core Generator software of system; Import a large amount of clinical physiological data samples and train, can roughly confirm the regularity of pathological characters, confirm the concrete parameter of sorter by these samples; In Fig. 1 dynamically illness reaction man-machine interactive system implementation pattern identified information obtain, pre-service, decision-making and aftertreatment; Categorised decision is carried out in treatment measure to be identified, and dynamically illness reaction man-machine interactive system drives the anthropomorphic dummy through embedded control system and produces dynamic response, and the simulation monitor links to each other with the anthropomorphic dummy and shows illness physiology and pathological information in real time.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN2012102017760A CN102708721A (en) | 2012-06-19 | 2012-06-19 | Analog medical care teaching system based on dynamic symptom reaction system |
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| CN2012102017760A CN102708721A (en) | 2012-06-19 | 2012-06-19 | Analog medical care teaching system based on dynamic symptom reaction system |
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| CN102708721A true CN102708721A (en) | 2012-10-03 |
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| CN2012102017760A Pending CN102708721A (en) | 2012-06-19 | 2012-06-19 | Analog medical care teaching system based on dynamic symptom reaction system |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103531069A (en) * | 2013-09-23 | 2014-01-22 | 上海市第十人民医院 | Learning practical training system based on simulation |
Citations (3)
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| US20060122954A1 (en) * | 2004-12-03 | 2006-06-08 | Podlasek Robert J | Medical simulator apparatus and method |
| CN101231676A (en) * | 2007-01-25 | 2008-07-30 | 希森美康株式会社 | Medical analog system and control system thereof |
| CN201336099Y (en) * | 2009-01-23 | 2009-10-28 | 北京医模科技有限公司 | Simulated first aid training device |
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2012
- 2012-06-19 CN CN2012102017760A patent/CN102708721A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US20060122954A1 (en) * | 2004-12-03 | 2006-06-08 | Podlasek Robert J | Medical simulator apparatus and method |
| CN101231676A (en) * | 2007-01-25 | 2008-07-30 | 希森美康株式会社 | Medical analog system and control system thereof |
| CN201336099Y (en) * | 2009-01-23 | 2009-10-28 | 北京医模科技有限公司 | Simulated first aid training device |
Non-Patent Citations (4)
| Title |
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| 刘为萍等: "运用ECS模拟人实施PBL教学的体会", 《广西医科大学学报》 * |
| 张永兵等: "基于人工神经网络的自适应疾病诊断模型研究", 《医疗设备信息》 * |
| 李惠萍等: "生理驱动模拟人在药理学教学中的研究与实践", 《医学模拟教学》 * |
| 沈花玉: "《神经网络在医学诊断中的应用研究》", 《中国优秀硕士论文全文数据库 信息科技辑 2009年》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103531069A (en) * | 2013-09-23 | 2014-01-22 | 上海市第十人民医院 | Learning practical training system based on simulation |
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Application publication date: 20121003 |