標題: 植基於HHT之腹式呼吸學習系統研發
Research and Development of Abdominal Breathing Learning System – HHT Evaluation Method
作者: 徐如欣
Hsu, Ju-Hsin
蕭子健
Hsiao, Tzu-Chien
生醫工程研究所
關鍵字: 希爾伯特黃轉換;腹式呼吸;訊號處理;Hilbert-Hung Transform;Abdominal breathing;Signal processing
公開日期: 2012
摘要: 常見的呼吸方式為胸式呼吸與腹式呼吸或者混合型態的呼吸。以解剖生理學和肌肉運動學的角度,胸式呼吸的機制已被明確的定義,而腹式呼吸的定義尚不明確,也導致腹式呼吸的效益無法有效評估。本研究的主要目的,為腹式呼吸的動作表現給予量化,並建立效益評估之標準。本研究中的實驗通過佛教慈濟綜合醫院研究倫理委員會的審查,有35位受試者參與本研究。實驗流程分為胸式呼吸與腹式呼吸,並分別進行自然呼吸與固定呼吸速率的步驟;固定呼吸速率設定為每分鐘呼吸12次的一般呼吸,以及每分鐘呼吸6次的慢呼吸。在進行腹式呼吸實驗步驟前,會先指導受試者使用腹式呼吸。實驗中使用四組壓電材料感測呼吸帶,分別繫於腋下下方、劍突、肚臍上方與肚臍下方,擷取呼吸時胸腹部移動的訊號,再以系集經驗模態分解法 (Ensemble Empirical Mode Decomposition)解構訊號,得到內在模式函數 (Intrinsic mode functions),計算相對應的瞬時頻率與能量。並萃取出主成分,再進一步計算內在模式函數與主成分的相關係數。 結果顯示,有23名受試者的腹式呼吸特徵較明顯,部分受測者在腹式呼吸實驗過程中使用混合型態的呼吸模式。不論是固定呼吸速率或非固定呼吸速率的情況下,能量可做為評估腹式呼吸效益的依據,且可在30秒內評估完成。在固定呼吸速率時,主成分瞬時頻率的均值和所設定的呼吸頻率接近;在非固定呼吸速率時,也仍可由主成分的瞬時頻率計算出呼吸速率。綜合本研究的結果,希爾伯特-黃 (Hilbert-Huang Transform) 可分析呼吸移動訊號,且內在模式函數的能量可作為呼吸動作的量化結果,依此量化結果可分辨胸式呼吸與腹式呼吸,並可做為評估腹式呼吸的標準。
In general, thoracic breathing (TB), abdominal breathing (AB) and mixing TB and AB are conventional breathing modes. The mechanism of TB is clearly defined in anatomy and muscle kinematics, but the trait of AB is vague. The main purpose of this study is to quantify the mechanism of AB and to provide an effectiveness evaluation criterion for AB. Thirty-five volunteers joined the experiment of this study which was approved by the Institution Review Board of Buddhist Tzu Chi General Hospital Research Ethics Committee. Four piezoelectric belt sensors were used to acquire spontaneously displace of breathing movement, which were attached to the subject’s chest below axilla, xiphoid, above navel, and below navel respectively. In the experiment TB and AB procedures were included, and each procedure contains spontaneous breathing, and paced breathing procedures which were set to 12 cycles per minute and 6 cycles per minute. Ensemble Empirical Mode Decomposition (EEMD) decomposed signals into intrinsic mode functions (IMFs), and then instantaneous frequency of each IMF was obtained by Hilbert Transform and differential. R-value, power, and average frequency of IMFs were calculated, and main component of the signal was extracted. The results indicate that 23 subjects appeared obvious AB characteristics, and some subjects used mixing TB and AB in AB procedure. Power proportion can evaluate AB effectiveness no matter paced breathing or spontaneous breathing, and even can evaluate in 30 seconds. In paced breathing, the average frequency approaches the set breathing frequency. Hilbert-Huang Transform (HHT) can analyze breathing movement signal, and the power proportion of IMF can quantify the mechanism of breathing. The quantification can distinguish between TB and AB and evaluate AB effectiveness.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT079930501
http://hdl.handle.net/11536/49989
顯示於類別:畢業論文