[請益] 論文摘要潤飾
在肌電訊號的特徵值分析中，自主與非自主呼吸在三個頻段的頻譜功率皆呈現顯著差異(p<0.05)，
而過零率上則有明顯的自體差異。
在特徵值的應用上，是以半自動的方式做呼吸判斷，其正確率皆高於83%；
本研究以呼吸氣流溫度比對平台演算法對於呼吸肌電訊號處理在位置與呼吸數判斷的正
確性，分別為98.9%與95.4%。
此外本研究以MIT-BIH資料庫的多重睡眠電圖下巴肌電訊號驗證本研究的特徵值方法，
不但都能反應出受測者的呼吸動作(特別是在呼吸窒息的狀況)，在難以觀測的肌電訊號
中也能看出其呼吸動作的特徵值變化。
The characteristics of EMG signal between spontaneous and compulsive breathing
were analyzed, and the results of the each of three bands showed significant
differences (p<0.05) on power spectrum analyses.
However, there were only self-difference on zero-cross rate.
Additionally, the characteristic-methods were applied to detect the breath
semi-automatically in EMG, and the accuracies of characteristic-methods were
all above 83%; The respiratory-detection method performed on an
EMG-acquisition platform was estimated by comparing the position of
breathing peak and the count of respiration with the air temperature signal,
and the accuracies were 98.9% and 95.4% respectively.
Furthermore, the chin EMG signals from MIT-BIH Polysomnographic Database were
carried out by characteristics-method;
as a result, the responses of all characteristics of EMG were agreement with
not only the average signal (especially at the status of dyspnea)
but also the hard-to-detect signal.
這段文章我已經改了好多次，但始終寫不好希望大家能給我建議，或指出缺點，THX
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※ 編輯: spaceuit 來自: 140.135.100.111 (05/04 20:18)
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