阻塞性睡眠呼吸暂停低通气综合征( OSAHS) 是心血管疾病的独立危险因素[1,2 ]。睡眠过程中反复发生氧饱和度降低和频繁觉醒是心血管损伤的病理生理基础。OSAHS 血管损害的早期改变可表现为血管僵硬度增加, 对亚临床血管病变患者开展早期动脉弹性功能检测及早进行干预, 可有效预防心血管疾病的发生。本文就常用的无创动脉硬化检测lt;br /gt;技术及其对OSAHS 心血管损伤的评估相关研究进展进行综述。
As one of the important indexes for the diagnosis and treatment of cardiovascular diseases, cardiac output can reflect the state of cardiovascular system timely, and can play a guiding role in the treatment of related diseases. In recent years detection technology of cardiac output has caused great attention, especially minimally invasive and non-invasive methods. In this paper, the principle of non-invasive detection methods and their recent developments are described, and various detection methods are also analyzed.
By studying the relationship between fingertip temperature changes and arterial function during vascular reactivity test, we established a new non-invasive method for detecting vascular function, in order to provide an assistance for early diagnosis and prevention of cardiovascular diseases. We customized three modules respectively for blood occlusion, measurement of finger temperature and blood oxygen acquisition, and then we established the hardware of data acquisition system. And the software was programmed with Labview. Healthy subjects [group A, n=24, (44.6±9.0) years] and subjects with cardiovascular diseases [group B, n=33, (57.2±9.9) years)] were chosen for the study. Subject's finger temperature, blood oxygen and occlusion pressure of block side during and after unilateral arm brachial artery occlusion were recorded, as well as some other regular physiological indexes. By time-domain analysis, we extracted 12 parameters from fingertip temperature signal, including the initial temperature (Ti), temperature rebound (TR), the time of the temperature recovering to initial status (RIt) and other parameters from the finger temperature signal. We in the experiment also measured other regular physiological body mass index (BMI), systolic blood pressure (SBP), diastiolic blood pressure (DBP) and so on. Results showed that 8 parameters difference between the two group of data were significant. based on the statistical results. A discriminant function of vascular function status was established afterwards. We found in the study that the changes of finger temperature during unilateral arms brachial artery occlusion and open were closely related to vascular function. We hope that the method presented in this article could lay a foundation of early detection of vascular function.
Artery stiffness is a main factor causing the various cardiovascular diseases in physiology and pathology. Therefore, the development of the non-invasive detection of arteriosclerosis is significant in preventing cardiovascular problems. In this study, the characterized parameters indicating the vascular stiffness were obtained by analyzing the electrocardiogram (ECG) and pulse wave signals, which can reflect the early change of vascular condition, and can predict the risk of cardiovascular diseases. Considering the coupling of ECG and pulse wave signals, and the association with atherosclerosis, we used the ECG signal characteristic parameters, including RR interval, QRS wave width and T wave amplitude, as well as the pulse wave signal characteristic parameters (the number of peaks, 20% main wave width, the main wave slope, pulse rate and the relative height of the three peaks), to evaluate the samples. We then built an assessment model of arteriosclerosis based on Adaptive Network-based Fuzzy Interference System (ANFIS) using the obtained forty sets samples data of ECG and pulse wave signals. The results showed that the model could noninvasively assess the arteriosclerosis by self-learning diagnosis based on expert experience, and the detection method could be further developed to a potential technique for evaluating the risk of cardiovascular diseases. The technique will facilitate the reduction of the morbidity and mortality of the cardiovascular diseases with the effective and prompt medical intervention.
By studying the relationship between fingertip temperature changes and arterial function during vascular reactivity test, we established a new non-invasive method for detecting vascular function, in order to provide an assistance for early diagnosis and prevention of cardiovascular diseases. We customized three modules respectively for blood occlusion, measurement of finger temperature and blood oxygen acquisition, and then we established the hardware of data acquisition system. And the software was programmed with Labview. Healthy subjects [group A, n=24, (44.6±9.0) years] and subjects with cardiovascular diseases [group B, n=33, (57.2±9.9) years)] were chosen for the study. Subject's finger temperature, blood oxygen and occlusion pressure of block side during and after unilateral arm brachial artery occlusion were recorded, as well as some other regular physiological indexes. By time-domain analysis, we extracted 12 parameters from fingertip temperature signal, including the initial temperature (Ti), temperature rebound (TR), the time of the temperature recovering to initial status (RIt) and other parameters from the finger temperature signal. We in the experiment also measured other regular physiological body mass index (BMI), systolic blood pressure (SBP), diastiolic blood pressure (DBP) and so on. Results showed that 8 parameters difference between the two group of data were significant. based on the statistical results. A discriminant function of vascular function status was established afterwards. We found in the study that the changes of finger temperature during unilateral arms brachial artery occlusion and open were closely related to vascular function. We hope that the method presented in this article could lay a foundation of early detection of vascular function.
Based on the noninvasive detection indeices and fuzzy mathematics method, this paper studied the noninvasive, convenient and economical cardiovascular health assessment system. The health evaluation index of cardiovascular function was built based on the internationally recognized risk factors of cardiovascular disease and the noninvasive detection index. The weight of 12 indexes was completed by the analytic hierarchy process, and the consistency test was passed. The membership function, evaluation matrix and evaluation model were built by fuzzy mathematics. The introducted methods enhanced the scientificity of the evaluation system. Through the Kappa consistency test, McNemer statistical results (P = 0.995 > 0.05) and Kappa values (Kappa = 0.616, P < 0.001) suggest that the comprehensive evaluation results of model in this paper are relatively consistent with the clinical, which is of certain scientific significance for the early detection of cardiovascular diseases.
The use of non-invasive blood glucose detection techniques can help diabetic patients to alleviate the pain of intrusive detection, reduce the cost of detection, and achieve real-time monitoring and effective control of blood glucose. Given the existing limitations of the minimally invasive or invasive blood glucose detection methods, such as low detection accuracy, high cost and complex operation, and the laser source's wavelength and cost, this paper, based on the non-invasive blood glucose detector developed by the research group, designs a non-invasive blood glucose detection method. It is founded on dual-wavelength near-infrared light diffuse reflection by using the 1 550 nm near-infrared light as measuring light to collect blood glucose information and the 1 310 nm near-infrared light as reference light to remove the effects of water molecules in the blood. Fourteen volunteers were recruited for in vivo experiments using the instrument to verify the effectiveness of the method. The results indicated that 90.27% of the measured values of non-invasive blood glucose were distributed in the region A of Clarke error grid and 9.73% in the region B of Clarke error grid, all meeting clinical requirements. It is also confirmed that the proposed non-invasive blood glucose detection method realizes relatively ideal measurement accuracy and stability.