- 學位論文
分析靜態有氧運動對心率變異度之影響
Analysis of Heart Rate Variability in Static Aerobic Exercise
摘要
長時間記錄心臟電生理訊號有助於檢測異常訊號偵測心臟異常生理現象，可用於分析心率變異度所反映之心臟適應變化能力，以及瞭解自主神經系統對心臟活動的調控作用，如、有效的有氧運動可增進自主神經活性，反映在心率變異度頻譜圖可發現數個波鋒，其中高頻部分波峰代表了呼吸影響副交感神經對於心跳之節律調控，故可透過追蹤心率變異度頻譜圖，觀察受測者進行有氧運動之呼吸方式是否對自主神經系統調控作用產生改變，檢驗藉由控制呼吸對心跳速率所造成之影響。 本研究將前端所截取之心電訊號資料利用藍芽模組傳送至電腦端，以Borland C++ Builder視窗化軟體顯示及將資料儲存為.txt文字檔，分析系統使用MATLAB 7.0.1做訊號分析，經過數位訊號處理及快速傅立葉轉換得到心率變異度頻譜圖。高頻追蹤將訊號以時間分割為11段訊號，分別對每段訊號做快速傅立葉轉換，取得在不同時間間期之功率頻譜圖，追蹤每個時段頻譜圖的高頻峰值頻率，並以量化分析計算落在mean±SD範圍內之高頻頻率位置數量，分析受測者維持在穩定狀態下之時間長度。 利用心電訊號分析系統，分析(1)有靜態有氧運動(禪坐)經驗受測者清醒狀態(2)一般正常受測者清醒狀態(3)一般正常受測者睡眠狀態所測得之訊號，比較三個類別受測者的高頻峰值頻率位置，及高頻峰值追蹤維持在mean±SD內之時間長度。其中第一類別和第三類別受測者在心率變異度頻譜圖之表現為高頻峰值位置相對集中，且高頻峰值追蹤在各時段之表現較為穩定，反映在生理狀態顯示呼吸頻率較為穩定、心率隨之下降，心率變異度高頻部分的峰值明顯，應證副交感神經活性較強之表現；相較之下第二類別受測者高頻峰值頻率位置集中程度較低，高頻峰值追蹤與前者之穩定性相比為較低。 有經常性有氧運動習慣的人，因呼吸性竇性心律不整（RSA）助於代償呼吸所造成之心律調節及血壓變動，RSA主要反映副交感神經調控作用，相對反應在心率變異度功率頻譜圖上代表副交感神經作用的高頻部分較為明顯，故可利用高頻追蹤在mean±SD範圍內量化數據判別受測者是否進行有效靜態有氧運動，以及維持在靜態有氧運動狀態之時間長短，未來若能將壓力因素一併考量分析，對於心率變異度訊號解讀生理調控機制將更為精確。
並列摘要
Heart rate variability (HRV) during exercise may be affected by the breathing frequency. If effective aerobic exercise improves autonomic nervous activity, we can use HRV spectrum to analyze the regulated of autonomic nervous system (ANS) to cardiovascular activity. There will be features shown on the HRV spectrum, and the high-frequency (HF, 0.15-0.4Hz in HRV spectrum) represent the regulation of heart rhythms by the parasympathetic nerve. Long-term ECG signals are proposed to reveal parasympathetic influences on HRV. And they also can be used to detect accidentally abnormal signals of cardiac dysfunction. Using the HRV spectrums to track HF peak frequency, quantitative analyses were used to calculate the quantity of HF peak frequency between mean±SD. We can use this quantization parameter to determine whether the subjects stay in stable state. Reflecting the capacity of cardiac variation adaptation in the physiological function. In this study, we analyze three types of subjects: (1) awakening subjects with static aerobic exercise experience; (2) normal awakening subjects; and (3) normal sleeping subject. Type 3 subjects have rhythm breathing, compared with type 1 and type 2 subjects, we found that only type 1 related. In terms of physiological conditions, their breathing frequency are more stable, results in the reduction of heart rate, and the HF peak in HRV spectrum were more obvious, which means the parasympathetic activity were increased. The breathing frequency of subjects with static aerobic exercise experience can improve respiratory sinus arrhythmia (RSA), cause both heart rate and blood pressure return to regular state. RSA reflects the regulation of parasympathetic, expressing the HF part on HRV spectrum. Using HF tracking quantitative value, we can estimate if the subject is doing effective aerobic exercise. If we put pressure factors into consideration in the future, this ECG signals analysis will be more accurate and precise.