透過您的圖書館登入
IP:13.59.122.162
  • 學位論文

以心肺情況變動對ECG和PPG衍生參數的相干性評估研究

Evaluation of Coherence Between ECG and PPG Derived Parameters in Various Cardiopulmonary Situations

指導教授 : 林康平
若您是本文的作者,可授權文章由華藝線上圖書館中協助推廣。

摘要


心率變異度(Heart rate variability )稱為HRV ,廣泛應用於臨床情境,可作為自主神經系統活性的評估指標。心率變異度參數最標準的來源是取得生物心電訊號即心電圖 (Electrocardiography, ECG)波峰與波峰之區間序列,經由時域分析以及頻域轉換,取得心率變異度時頻域參數。 光體積描記圖(Photoplethysmography),稱為 PPG,其生物光學訊號擷取的方式比生物電訊號擷取方式簡便,故穿戴設備生物訊號擷取技術的發展多以光體積描記圖為主流。光體積描記圖常用於測量脈搏率,而以光體積描記圖的量測訊號進行心率變異度分析,稱作脈率變異度(Pulse rate variability, PRV)。於論文研究上已有為數不少的論文在研究討論脈率變異度是否可作為心率變異度的替代。 心肺耦合在描述呼吸生理會影響心臟血管的表現,而此心肺之間的訊息傳導則是透過自律神經之傳導,因此心率變異度多用來作為評估心肺耦合表現之工具。 本論文研究探討清醒狀態下,受測者為健康族群以及睡眠狀態下,受測者為健康族群、具備呼吸中止事件族群以及呼吸中止事件族群配戴陽壓呼吸器,評估心肺耦合的生理活動下心率變異度以及脈率變異度是否具備一致性。 多數論文以心率變異度研究呼吸性竇性心率不整,較少以脈率變異度進行研究評估,且多在探導量測時姿勢對脈率變異度之影響。本論文除了評估心率變異度與脈率變異度於呼吸性竇性心率不整(Respiratory Sinus Arrhythmia, RSA)期間參數的一致性,同時也設計完整之呼吸控制模式進行研究,從研究成果可得到呼吸頻率影響心率變異度的程度最大,其次是呼吸深淺,最後是自然呼吸。 於睡眠過程中,具備睡眠呼吸中止事件的患者,當呼吸中止事件發生時如同呼吸遭受控制,故本論文以此為研究思考,企圖研究睡眠過程之心肺耦合狀態,以健康受測者為對照組,比對呼吸中止事件受測者之心率變異度及脈率變異度參數表現,除了分析心率變異度及脈率變異度參數是否具備一致性,同時分析呼吸中止事件受測者配戴陽壓呼吸器,是否可讓參數接近正常人之表現。

並列摘要


Heart rate variability is called HRV, which is widely used in clinical situations and can be used as an evaluation index for the activity of the autonomic nervous system. The most standard source of HRV parameters is to obtain biological Electrocardiography (ECG) signals and capture peaks and peaks interval sequence of ECG, then obtain the time-frequency domain parameters of HRV through time-domain analysis and frequency-domain conversion. Photoplethysmography is called PPG, has a simpler method of capturing bio-optical signals than bio-electrical signals. Therefore, the development of bio-signal capturing technology for wearable devices is mostly based on PPG. The PPG is often used to measure the pulse rate, and the measurement signal of the PPG is used to analyze the HRV, which is called pulse rate variability (PRV). There have been quite a few papers in research papers discussing whether PRV can be used as a substitute for HRV. Cardiopulmonary coupling is describing that respiratory physiology affects the performance of the heartbeat and blood vessels, and the signal transmission between the heart and lungs is conducted through the autonomic nerve. Therefore, the HRV is mostly used as a tool to evaluate the performance of the cardiopulmonary coupling. This paper investigates that in the awake state, the subjects are in the healthy group and in the sleeping state, the subjects are in the healthy group, the group with the sleep apnea syndrome, and the sleep apnea syndrome group wearing a continuous positive airway pressure(CPAP) machine, and assessing the physical activity of the cardiopulmonary coupling whether the HRV and PRV are consistent. Most papers use HRV to study respiratory sinus arrhythmia, and rarely use PRV for research and evaluation, and most of them explore the influence of posture on PRV during measurement. In this paper, apart from evaluating the consistency of the parameters of HRV and PRV during respiratory sinus arrhythmia (RSA), it also designs a complete respiration control model for research. From the research results, it can be obtained that the respiratory rate affects the HRV and PRV the most, followed by the depth of breathing, and finally the natural breathing. During sleep, patients with sleep apnea events are as if breathing is controlled when the apnea event occurs. Therefore, this paper uses this as research thinking to study the cardiopulmonary coupling state during sleep. Healthy subjects are used as the control group, compare the performance of the HRV and PRV parameters of the subjects of the sleep apnea, in addition to analyzing whether the HRV and the PRV parameters are consistent, and analyze the sleep apnea subjects wearing CPAP machine, whether the parameters can be close to the performance of healthy subjects. Keywords: Electrocardiography(ECG), Photoplethysmography (PPG), Heart rate variability(HRV), Pulse rate variability(PRV), Respiratory sinus arrhythmia (RSA), Sleep Apnea, Continuous positive airway pressure (CPAP)

參考文獻


[1] Acharya, U. R., Joseph, K. P., Kannathal, N., Lim, C. M., Suri, J. S. (2006). Heart rate variability: a review. Medical Biological Engineering Computing, 44(12), 1031–1051.
[2] Tripathi, K. K. (2004). Respiration and heart rate variability: A review with special reference to its application in aerospace medicine.
[3] Indian Journal of Aerospace Medicine, 48(12), 64-75. Nemati, S., Malhotra, A. (2010). Clifford GD “Data fusion for improved respiration rate estimation”. EURASIP Journal on Advances in Signal Processing, 2010(1), 1.
[4] Bailon, R., Sornmo, L. (2006). Laguna P “A robust method for ECG-based estimation of the respiratory frequency during stress testing”. IEEE Transactions on Biomedical Engineering, 53(7), 1273–1285.
[5] Tamura, T., Maeda, Y., Sekine, M., Yoshida, M. (2014). Wearable photoplethysmographic sensors-past and present. Electronics, 3(2), 282–302.

延伸閱讀