| 引用本文: | 李恬鉴,柳英芝.一类生理信号的采集、建模和辨识[J].控制理论与应用,1992,9(1):55~62.[点击复制] |
| LI Tianjian and LIU Yingzhi.Sampling, Model Building and Identification of a Category of Physiological Signals[J].Control Theory and Technology,1992,9(1):55~62.[点击复制] |
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| 一类生理信号的采集、建模和辨识 |
| Sampling, Model Building and Identification of a Category of Physiological Signals |
| 摘要点击 714 全文点击 397 投稿时间：1988-12-30 修订日期：1990-07-06 |
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| DOI编号 |
| 1992,9(1):55-62 |
| 中文关键词 生理信号 时间序列分析 建模 参数辨识 |
| 英文关键词 physiological signal time series analysis model building parameter identification |
| 基金项目 |
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| 中文摘要 |
| 本文对生理信号的采集、建模和辨识作了较系统的探讨。在生理信号的采集方面，介绍了实时和离线信号的采集的设计思想和实现方案。在生理信号的数据建模方面，引入了ARMA 建模方案，着重研讨了模型的实现途径、参数辨识和平稳化方法，编制建模程序及实现框图。在心功能病类辨识方面，对典型心功能信号——ECG、CAG和ACG，根据类比原则，利用模型分析结果，对三类心血管病——高血压、冠心病和心肌炎作了聚类辨识，取得用参数域值辨识病理的结果。 |
| 英文摘要 |
| This paper intends to give a systematic investigation to the sampling, model building and identification of a category of physiological signals. As to model fitting of physiological signals, by applying the ARMA model scheme to the sampled cardiac function data series, we stressed on the realistic methodology, the parameter identification technique and stationarized method. By virture of typical cardiac function signals-ECG, ACG,CAG, combining with microscopic analysis results, we have made characteristic identification microscopically to the typical desease-hypertension, coronary heart desease and myocarditis, according to the parameter `s domain values of ARMA models. |
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