標題: 胸腹部運動下瞬時相位差之分析-以腹式呼吸為例
Instantaneous phase difference analysis between thoracic and abdominal movement in abdominal breathing
作者: 陳雅蓁
蕭子健
Chen, Ya-Chen
Hsiao, Tzu-Chien
資訊科學與工程研究所
關鍵字: 瞬時相位差;胸腹部運動;腹式呼吸;Instantaneous phase difference;Thoracoabdominal movement;Abdominal breathing
公開日期: 2017
摘要: 文獻指出:胸部與腹部運動之同步關係可以用來診斷呼吸系統疾病!臨床研究慣用Lissajous figure計算相位差來評估胸部與腹部運動 (Thoracoabdominal movement, 簡稱TAM) 之同步關係。然而,這種方法的時間解析度低,而且當呼吸訊號不屬於正弦波形 (sinusoidal wave) 時,其相位差之計算易出現錯誤。近期的文獻提出以帶通濾波器計算相位關係的方法,以提高相位差分析的時間解析度,然而,帶通濾波器有相位延遲的效應,需要結合校正方法才能有效地應用於呼吸運動之相位差分析。本研究提出一高時間解析度的瞬時相位差 (Instantaneous phase difference, 簡稱IPD) 分析流程,即結合互補式經驗模態結構法,來評估TAM之同步關係。為了驗證IPD分析流程的效益,本研究進行正弦波與非正弦波形訊號模擬實驗,以及人體胸式呼吸 (Thoracic breathing, 簡稱TB) 與腹式呼吸 (Abdominal breathing, 簡稱AB) 運動實驗,過程中所萃取之IPD結果將與臨床常用的Lissajous figure 相位分析(Improved version of Lissajous figure analysis, 簡稱loop analysis)以及工程領域提出的自動化相位計算方法(Automatic phase estimation procedure, 簡稱 APEP)進行比較。模擬訊號實驗將有標準答案 (Gold standard) 可以比對,結果顯示IPD的計算結果與標準答案較為一致,從IPD的標準差小於loop analysis及APEP 兩種方法可以觀察到IPD有比較穩定的計算結果;另一方面,人體呼吸訊號實驗分析結果顯示,AB之IPD大於TB之IPD (AB vs. TB:23 ± 6.28° vs. 19 ± 4.91°, p < .001),此結果與loop analysis (AB vs. TB:32 ± 16.94° vs. 19 ± 8.97°, p < .001) 及APEP (AB vs. TB:51 ± 35.20° vs. 34 ± 21.88°, p < .01) 結果相同,並且與臨床慣用的loop analysis呈現高度正相關 (TB時相關係數為0.88,AB時相關係數為0.91)。 根據模擬訊號實驗與人體訊號實驗結果顯示,IPD能有效的分析呼吸胸部與腹部運動之相位差,其結果與臨床慣用的方法相近 (相較於APEP),並且有五大特色:(1) 提高時間解析度、(2)沒有相位延遲的問題、(3)能有效地分析非正弦波形的模擬呼吸訊號、(4)解析流程中不需要事先知道呼吸運動的頻率、(5)分析結果不需要進行校正。本研究有效結合資訊工程領域的演算法 (即IPD分析流程) 與人體實驗,探討瞬時相位差,近而分析呼吸運動之同步關係,研究呼吸模式的生理機制,未來將有助於發展瞬時呼吸速率及呼吸運動對自主神經系統的調控機轉,相關成果將有助於結合資訊工程與生醫應用的知識,達到跨領域研究與生醫工程技術之發展。
Thoracoabdominal asynchrony is often adopted to discriminate respiratory diseases in clinics. Conventionally, Lissajous figure analysis is the most frequently used estimation of the phase difference in thoracoabdominal asynchrony in clinic. However, the temporal resolution of the produced results is low and the estimation error increases when the signals are not sinusoidal. Other previous studies have reported time-domain procedures with the use of band-pass filters for phase-angle estimation. Nevertheless, the band-pass filters need calibration for phase delay elimination. To improve the estimation, this study proposes a novel method that is based on complementary ensemble empirical mode decomposition for estimating the instantaneous phase difference (IPD) relation between measured thoracic wall movement and abdominal wall movement. To validate the proposed method, experiments on simulated time series (i.e., sinusoidal signal and non-sinusoidal signal) with gold standard and human subject respiratory data with two breathing types (i.e., thoracic breathing, TB and abdominal breathing, AB) were conducted. Improved version of Lissajous figure analysis (called as loop analysis) and automatic phase estimation procedure (APEP) were compared. The simulation results show that the results of the proposed method (IPD) were very close to the gold standard compared with the results of loop analysis and APEP. For the human subject respiratory data, the results of the proposed method are in line with those in the literature, and the correlation analysis result reveals that they were positively correlated with the results generated by the two conventional methods (correlation coefficient between IPD and loop analysis is r = 0.88 under TB and r = 0.91 under AB; correlation coefficient between IPD and APEP is r = 0.46 under TB and r = 0.84 under AB). Furthermore, the standard deviation of the proposed method was also the smallest. And the results from IPD are similar to the method which is the most frequently used in clinic (loop analysis). To summarize, this study proposes a novel method for estimating IPD. According to the findings from both the simulation and human subject data, our approach was demonstrated to be effective. The method offers the following advantages: 1) improves the temporal resolution, 2) does not introduce a phase delay, 3) works with non-sinusoidal signals, 4) provides quantitative phase estimates without estimating the embedded frequency of the breathing signals, and 5) works without calibrated measurements. This study integrates the technologies from computer science (i.e., a novel procedure of IPD) with human subject experiment. The findings of current study are expected to evaluate the thoracoabdominal asynchrony for investigating respiratory mechanism and to apply the results in clinic. The development of the instantaneous respiratory pattern could be helpful for investigating instantaneous respiratory rate variability and exploring how the breathing modulates autonomic nervous system. The current study is expected to support the technology of multidisciplinary research, which may be applied to various applications in biomedical engineering in near future.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070086012
http://hdl.handle.net/11536/140779
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