整合峰度與特徵演算模型之即時心電訊號呼吸分析

Abstract

Cardiovascular diseases are the most popular causes of death in the world recently. It is well know that doing the cardiac rehabilitation program treatment has positive effects on disease symptoms, quality of life, cardiopulmonary capability and reduction of mortality for the heart disease patients, such as cardiovascular patients, postoperative patients of cardiac surgery, heart failure patients and even the patients who received heart transplant. Presently the home-based rehabilitation is regard as a important approach. It needs ECG and respiratory signal to estimate the intensity and safety. Especially, heart rate and respiratory rate are the most basic monitoring information. ECG measuring has researched for a long time in many kind of algorithm or device. However, respiratory information is difficult to acquire. Most of devices are not appropriate to home-based rehabilitation exercise. Those are interfered easily or not comfortable equipment. In this study, develop an algorithm that transforming the ECG signal to respiratory signal. And only ECG holter can acquire ECG signal and respiration condition. Moreover, let the algorithm apply to mobile device. In the past research, the algorithm either is too complex, low accuracy or unsuitable at vast range of respiratory rate. The algorithm has clinical testing in Mackay Memorial Hospital. Clinical test of 15 subjects affording Bruce Task (treadmill), correlation between this system and commercial product (Custo-Med) is up to 82% in respiratory rate as 98% in heart rate. Combining with smart phone, patients exercise with more comprehensive, efficiency, and safety rehabilitation system.

Cardiovascular diseases are the most popular causes of death in the world recently. It is well know that doing the cardiac rehabilitation program treatment has positive effects on disease symptoms, quality of life, cardiopulmonary capability and reduction of mortality for the heart disease patients, such as cardiovascular patients, postoperative patients of cardiac surgery, heart failure patients and even the patients who received heart transplant. Presently the home-based rehabilitation is regard as a important approach. It needs ECG and respiratory signal to estimate the intensity and safety. Especially, heart rate and respiratory rate are the most basic monitoring information. ECG measuring has researched for a long time in many kind of algorithm or device. However, respiratory information is difficult to acquire. Most of devices are not appropriate to home-based rehabilitation exercise. Those are interfered easily or not comfortable equipment. In this study, develop an algorithm that transforming the ECG signal to respiratory signal. And only ECG holter can acquire ECG signal and respiration condition. Moreover, let the algorithm apply to mobile device. In the past research, the algorithm either is too complex, low accuracy or unsuitable at vast range of respiratory rate. The algorithm has clinical testing in Mackay Memorial Hospital. Clinical test of 15 subjects affording Bruce Task (treadmill), correlation between this system and commercial product (Custo-Med) is up to 82% in respiratory rate as 98% in heart rate. Combining with smart phone, patients exercise with more comprehensive, efficiency, and safety rehabilitation system.