连续血糖监测在糖尿病管理中具有重要的意义.目前糖尿病患者主要通过指尖采血或植入式微创传感器监测血糖,但上述方法存在疼痛、成本昂贵、易感染等问题,因此,无创监测是实现连续血糖监测的理想技术.本文利用心电(ECG)信号,提出了一种...连续血糖监测在糖尿病管理中具有重要的意义.目前糖尿病患者主要通过指尖采血或植入式微创传感器监测血糖,但上述方法存在疼痛、成本昂贵、易感染等问题,因此,无创监测是实现连续血糖监测的理想技术.本文利用心电(ECG)信号,提出了一种血糖水平无创监测的方法:通过获取12名志愿者共60 d 756160个ECG周期信号,利用递归滤波器实现ECG信号的滤波,并采用卷积神经网络和长短期记忆网络相结合(CNN-LSTM)的方法,实现了血糖水平的十分类监测,并通过实验探索了个体建模和群体建模2种建模方式的差异.结果表明,在个体建模和群体建模的条件下,血糖监测精确率分别约达到80%和88%.其中群体建模10分类的F1值可达到0.95、0.88、0.91、0.85、0.92、0.88、0.86、0.86、0.87和0.86.研究表明,本文提出的基于ECG的无创血糖监测方法为实现血糖水平的实时、精准监测提供了一种有力的理论支撑与技术指导.展开更多
Adequate oxygen in red blood cells carrying through the body to the heart and brain is important to maintain life.For those patients requiring blood,blood transfusion is a common procedure in which donated blood or bl...Adequate oxygen in red blood cells carrying through the body to the heart and brain is important to maintain life.For those patients requiring blood,blood transfusion is a common procedure in which donated blood or blood components are given through an intravenous line.However,detecting the need for blood transfusion is time-consuming and sometimes not easily diagnosed,such as internal bleeding.This study considered physiological signals such as electrocardiogram(ECG),photoplethysmogram(PPG),blood pressure,oxygen saturation(SpO2),and respiration,and proposed the machine learning model to detect the need for blood transfusion accurately.For the model,this study extracted 14 features from the physiological signals and used an ensemble approach combining extreme gradient boosting and random forest.The model was evaluated by a stratified five-fold crossvalidation:the detection accuracy and area under the receiver operating characteristics were 92.7%and 0.977,respectively.展开更多
In order to analyze the experimental cardiovascular signal with high accuracy, a system, integrating real-time monitoring and off-line further analysis, was developed and verified. The design, data processing and anal...In order to analyze the experimental cardiovascular signal with high accuracy, a system, integrating real-time monitoring and off-line further analysis, was developed and verified. The design, data processing and analysis methods as well as testing results are described. With 5 sampling frequency choices and 8 channel data acquisition, the system achieved high performances in beat-to-beat monitoring, signal processing and analysis. Tests were carried out to validate its performance in real-time monitoring, effectiveness of digital filters, QRS and blood pressure detection reliability, and RR-interval timing accuracy. The QRS detection rate was at least 99.46% for the records with few noises from MIT-BIH arrhythmia database using the algorithm for real-time monitoring, and no less than 96.43% for the records with some noises. In the condition that noise amplitude levels were less than 80%,the standard deviations for RR-interval timing were less than 1 ms with a generated ECG corrupted with various noises from MIT-BIH Noise Stress Test Database. Besides, the system is open for function expansion to meet further study-specific needs.展开更多
AIM: To investigate autonomic nervous function in patients with a diagnosis of gastroesophageal reflux disease(GERD).METHODS: The investigation was performed on 29patients(14 men), aged 18-80 years(51.14 ± 18.34)...AIM: To investigate autonomic nervous function in patients with a diagnosis of gastroesophageal reflux disease(GERD).METHODS: The investigation was performed on 29patients(14 men), aged 18-80 years(51.14 ± 18.34),who were referred to our Neurocardiology Laboratory at the Clinical and Hospital Center "Bezanijska Kosa"with a diagnosis of GERD. One hundred sixteen healthy volunteers matched in age and sex with the examinees served as the control group. The study protocol included the evaluation of autonomic function and hemodynamic status, short-term heart rate variability(HRV) analysis, 24 h ambulatory ECG monitoring with long-term HRV analysis and 24 h ambulatory blood pressure monitoring.RESULTS: Pathologic results of cardiovascular reflex test were more common among patients with reflux compared to the control group. Severe autonomic dysfunction was detected in 44.4% of patients and in7.9% of controls(P < 0.001). Parameters of short-term analysis of RR variability, which are the indicators ofvagal activity, had lower values in patients with GERD than in the control group. Long-term HRV analysis of time-domain parameters indicated lower values in patients with reflux disease when compared to the control group. Power spectral analysis of long-term HRV revealed lower low- and high-frequency values.Detailed 24 h ambulatory blood pressure analysis showed significantly higher values of systolic blood pressure and pulse pressure in the reflux group than in the control group.CONCLUSION: Patients with GERD have distortion of sympathetic and parasympathetic components of the autonomic nervous system, but impaired parasympathetic function appears more congruent to GERD.展开更多
文摘连续血糖监测在糖尿病管理中具有重要的意义.目前糖尿病患者主要通过指尖采血或植入式微创传感器监测血糖,但上述方法存在疼痛、成本昂贵、易感染等问题,因此,无创监测是实现连续血糖监测的理想技术.本文利用心电(ECG)信号,提出了一种血糖水平无创监测的方法:通过获取12名志愿者共60 d 756160个ECG周期信号,利用递归滤波器实现ECG信号的滤波,并采用卷积神经网络和长短期记忆网络相结合(CNN-LSTM)的方法,实现了血糖水平的十分类监测,并通过实验探索了个体建模和群体建模2种建模方式的差异.结果表明,在个体建模和群体建模的条件下,血糖监测精确率分别约达到80%和88%.其中群体建模10分类的F1值可达到0.95、0.88、0.91、0.85、0.92、0.88、0.86、0.86、0.87和0.86.研究表明,本文提出的基于ECG的无创血糖监测方法为实现血糖水平的实时、精准监测提供了一种有力的理论支撑与技术指导.
基金This work was supported by the Korea Medical Device Development Fund from the Korean government(the Ministry of Science and ICTMinistry of Trade,Indus-try and Energy+2 种基金Ministry of Health and Welfareand Ministry of Food and Drug Safety)(KMDF_PR_20200901_0095)the Soonchunhyang University Research Fund.
文摘Adequate oxygen in red blood cells carrying through the body to the heart and brain is important to maintain life.For those patients requiring blood,blood transfusion is a common procedure in which donated blood or blood components are given through an intravenous line.However,detecting the need for blood transfusion is time-consuming and sometimes not easily diagnosed,such as internal bleeding.This study considered physiological signals such as electrocardiogram(ECG),photoplethysmogram(PPG),blood pressure,oxygen saturation(SpO2),and respiration,and proposed the machine learning model to detect the need for blood transfusion accurately.For the model,this study extracted 14 features from the physiological signals and used an ensemble approach combining extreme gradient boosting and random forest.The model was evaluated by a stratified five-fold crossvalidation:the detection accuracy and area under the receiver operating characteristics were 92.7%and 0.977,respectively.
基金This work is supported by Beijing Natural Science Foundation (3052015)
文摘In order to analyze the experimental cardiovascular signal with high accuracy, a system, integrating real-time monitoring and off-line further analysis, was developed and verified. The design, data processing and analysis methods as well as testing results are described. With 5 sampling frequency choices and 8 channel data acquisition, the system achieved high performances in beat-to-beat monitoring, signal processing and analysis. Tests were carried out to validate its performance in real-time monitoring, effectiveness of digital filters, QRS and blood pressure detection reliability, and RR-interval timing accuracy. The QRS detection rate was at least 99.46% for the records with few noises from MIT-BIH arrhythmia database using the algorithm for real-time monitoring, and no less than 96.43% for the records with some noises. In the condition that noise amplitude levels were less than 80%,the standard deviations for RR-interval timing were less than 1 ms with a generated ECG corrupted with various noises from MIT-BIH Noise Stress Test Database. Besides, the system is open for function expansion to meet further study-specific needs.
文摘AIM: To investigate autonomic nervous function in patients with a diagnosis of gastroesophageal reflux disease(GERD).METHODS: The investigation was performed on 29patients(14 men), aged 18-80 years(51.14 ± 18.34),who were referred to our Neurocardiology Laboratory at the Clinical and Hospital Center "Bezanijska Kosa"with a diagnosis of GERD. One hundred sixteen healthy volunteers matched in age and sex with the examinees served as the control group. The study protocol included the evaluation of autonomic function and hemodynamic status, short-term heart rate variability(HRV) analysis, 24 h ambulatory ECG monitoring with long-term HRV analysis and 24 h ambulatory blood pressure monitoring.RESULTS: Pathologic results of cardiovascular reflex test were more common among patients with reflux compared to the control group. Severe autonomic dysfunction was detected in 44.4% of patients and in7.9% of controls(P < 0.001). Parameters of short-term analysis of RR variability, which are the indicators ofvagal activity, had lower values in patients with GERD than in the control group. Long-term HRV analysis of time-domain parameters indicated lower values in patients with reflux disease when compared to the control group. Power spectral analysis of long-term HRV revealed lower low- and high-frequency values.Detailed 24 h ambulatory blood pressure analysis showed significantly higher values of systolic blood pressure and pulse pressure in the reflux group than in the control group.CONCLUSION: Patients with GERD have distortion of sympathetic and parasympathetic components of the autonomic nervous system, but impaired parasympathetic function appears more congruent to GERD.
