The Embeded Design Of A Deepth Of Anesthesia Monitor System

Monitoring of the depth of anesthesia (DoA) is of great importance in guiding theapplication of anesthetics, avoiding sugery risks and reducing patients’pains. TraditionalDoA monitoring are generally based on patient’s reactions and physiological parameterssuch as heartrate variation and spontaneous skin myoelectricity. The judgement of DoAhighly relies on the experience of the anesthetist, and lacks a defined quantative measure.Great attention has been paid to DoA monitoring via electroencephalogram (EEG) analy-sis recently. A few products have emerged on the market. However, most products calcu-late their paramaters based on linear theory, therefore have deficits in analyzing non-linearEEG signals. The high price also restricts their application in China. Therefore, deveploingnew DoA monitoring algorithms and devices has a great significance.A DoA monitor based on digital signal processor (DSP) is proposed in this disserta-tion. are discused. The source, characteristics and removal of artifacts within EEG are de-scribed, and de-noise solutions suitable for DoA monitoring and DSP realization are pro-posed. Some available EEG analysis methods are presented, and the DoA monitoring al-gorithm based on Permutation Entropy (PE) is described in detail, including the principleof PE, the pharmacokinetics/pharmacodynamics (PK/PD) analysis and statistical analysis.The comparision of PE with other indexes proved its advantage. Moreover, a DoA moni-toring algorithm based on the multiscale sample entropy is proposed. PK/PD analysisshows its validity in reflecting EEG changes with anesthetic concentration. The method isproved better than a few DoA paramaters. Paticularly, it reveals the multiscale characteris-tic of EEG signal to some extend.The complete design of an EEG acquistition system is explained in this dissertation,including the front amplifier, channel muxing, acquistition logic, data processing, datatransmission and the data receive and display on the host system. Then the implement ofthe key algorithms on the DSP platform are explained. Main code for data acquistition,USB communication, digital filters and PE calculation are explained. Issues on program-ming and algorithm optimization are discussed.