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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/65845


    Title: 智慧型呼吸器之抽痰警報設計;Intelligent Ventilator with Sputum Suction Alarm Design
    Authors: 李建賢;Lee,Jian-shian
    Contributors: 電機工程學系
    Keywords: 智慧型警報;智慧型呼吸器;呼吸器抽痰警報;Intelligent alarm;intelligent ventilator;Ventilator sputum alarm
    Date: 2014-08-29
    Issue Date: 2014-10-15 17:11:46 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 呼吸器是加護病房中輔助病人進行人工呼吸,支持生命很重要的生醫儀器。呼吸器除提供人工呼吸外,會有警報的設計,目的為能及時提醒醫療人員,病人在使用呼吸器時處於異常狀態,其中最常見的氣道高壓警報,代表的是呼吸器通氣時,病人氣道有受阻的問題,但是可能的原因很多,加上每日病人臨床的問題也繁多,需要更有效率地精準地判斷與處置。當呼吸器發出高壓警報時,第一種可能原因為病人咳嗽、痰液增加之動態阻塞。第二種原因是病人的呼吸道產生靜態阻塞,如支氣管收縮所引起;或病人肺功能的改變而引起的高壓警報。而之前發展的呼吸器高壓警報提醒系統,是以呼吸道檢測機制來分辨呼吸器病人之高壓警報時,呼吸道阻塞的分類。為了能再精準地提醒醫護人員,病人是否需要抽痰的警報,因此,我們的研究目的是以量化「呼吸流量」上之震盪狀況來發展呼吸器高壓警報之智慧型輔助系統。本論文將痰液阻塞時「呼吸流量」波形中特有的「鋸齒狀」波形(在此稱為震盪現象),加以量化。量化的步驟為先將「呼吸流量」中含「鋸齒狀」的部分切出,然後再將其部分利用曲線擬合的方式找出平滑線,最後計算「鋸齒狀」波形與平滑線的差異作為量化值。在實驗結果部分,當病人出現痰液阻塞時「呼吸流量」波形中的震盪現象就會比較明顯,所量化出的震盪值就會較高;反之震盪值就會較小。因此本文藉由這量化值,使得呼吸器的高壓警報系統可以準確地給予醫療人員其病人需要抽痰的警示,以發展出智慧型呼吸器警報系統。;With the modern technology, people can still alive by the assistance of biomedical instrument even when they are seriously injured. Now, many types of ventilators have alarm systems in order to send alert signal to health care personnel when patients are in emergency condition. But the traditional ventilators alarm systems often give false alarm because the criterion was often only relying on one parameter. And health care personnel often can not recognize what the exactly conditions is in the beginning. So they must rely on a wealth of clinical experience to make right judgments after going to patients’ ward. According to that, we design an intelligent alarm system that will help health care personnel work more efficiently. In this study, we design a sputum alarm system to send alert signals when patients’ airway were obstructed by sputum. Until now, health care personnel have to go to patient’s ward to check what patient’s condition is after hearing high pressure alarm. And once they hear something like grunt sounds, they will implement sputum suction process. Thus, we can add that way to our alarm system. The grunt sounds will reflect on flow parameter in the ventilator. If there are some grunt sounds from the patient’s airway, flow wave will reveal some vibrations known as saw tooth pattern. In this study, we quantify the vibrations of the flow wave, and let this value as a criterion that our system can give the exact condition when patient’s was during airway sputum obstruction period. When the value we quantified was high, our system will send airway sputum obstruction alarm. In contrast, when the value was low, our system will send airway static obstruction alarm.
    Appears in Collections:[電機工程研究所] 博碩士論文

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