Objective To evaluate the feasibility of pulse transit time (PTT) arousals as an index of sleep fragmentation in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). Methods Individuals referred for evalua...Objective To evaluate the feasibility of pulse transit time (PTT) arousals as an index of sleep fragmentation in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). Methods Individuals referred for evaluation of possible OSAHS underwent overnight polysomnography (PSG). Three conventional indices of sleep fragmentation [electroencephalography (EEG) arousals, apnea/hypopnea index (AHI), oxygen desaturation index (ODI)], PTT arousals, and Epworth sleepiness scale (ESS) were compared. Results PTT arousals were positively correlated with EEG arousals (r= 0.746, P<0.001), AHI (r= 0.786, P<0.001), and ODI (r= 0.665, P<0.001), respectively. But, both PTT arousals and EEG arousals had no correlation with ESS (r= 0.432, P=0.201; r= 0.196, P=0.591, respectively). Conclusion PTT arousals are correlated well with other standard measures estimating severity of OSAHS and potentially a non-invasive marker with which to measure the sleep fragmentation in patients with OSAHS.展开更多
PuLse transit time(FIT)is used as a noninvasive and cull-less parameter to estimate blood pressure.In this paper,we develop an algorithm to obtain FTT rapidly,which is appropriate for micro-processor and could achieve...PuLse transit time(FIT)is used as a noninvasive and cull-less parameter to estimate blood pressure.In this paper,we develop an algorithm to obtain FTT rapidly,which is appropriate for micro-processor and could achieve good accuracy in PTT,even in noisy measurements.The algorithm is based on finite impulse response(FIR)filter to reduce the noise and an adaptive threshold to detect the significant points of ECG and PPG.Evaluation of this method is based on the signals from our PTr-based blood pressure devices.It is shown that the method works well for PPT calculation.展开更多
Pulse transit time (PTT) is used as a noninvasive and cuff-less parameter to estimate blood pressure. In this paper, we develop an algorithm to obtain PTT rapidly, which is appropriate for micro-processor and could ac...Pulse transit time (PTT) is used as a noninvasive and cuff-less parameter to estimate blood pressure. In this paper, we develop an algorithm to obtain PTT rapidly, which is appropriate for micro-processor and could achieve good accuracy in PTT, even in noisy measurements. The algorithm is based on finite impulse response (FIR) filter to reduce the noise and an adaptive threshold to detect the significant points of ECG and PPG. Evaluation of this method is based on the signals from our PTT-based blood pressure devices. It is shown that the method works well for PPT calculation.展开更多
Using a time-dependent multilevel approach, we demonstrate that lithium atoms can be transferred to states of lower principle quantum number by exposing them to a frequency chirped microwave pulse. The population tran...Using a time-dependent multilevel approach, we demonstrate that lithium atoms can be transferred to states of lower principle quantum number by exposing them to a frequency chirped microwave pulse. The population transfer from n = 79 to n = 70 states of lithium atoms with more than 80% efficiency is achieved by means of the sequential two-photon △n=-1 transitions. It is shown that the coherent control of the population transfer can be accomplished by the optimization of the chirping parameters and microwave field strength. The calculation results agree well with the experimental ones and novel explanations have been given to understand the experimental results.展开更多
Continuous non-invasive blood pressure (BP) measurement can be realized by using pulse transit time (PTT) based on electrocardiogram (ECG) and pulse wave signal. Modulated magnetic signature of blood (MMSB) is a promi...Continuous non-invasive blood pressure (BP) measurement can be realized by using pulse transit time (PTT) based on electrocardiogram (ECG) and pulse wave signal. Modulated magnetic signature of blood (MMSB) is a promising approach to obtain PTT. The origin of MMSB is critical to establish the relationship between MMSB and BP. In this paper, two possible origins of MMSB, blood disturbance mechanism and angular variation mechanism, are analyzed and verified through three control experi-ments under different conditions. The influence of blood velocity alteration and blood volume alteration on magnetic field is investigated though blood flow simulation sys-tem. It is found that MMSB comes mainly from the periodic blood flow while the per-turbation caused by angular variation between sensitive axis of the magnetic sensor and geomagnetic field can be neglected. As to blood disturbance mechanism, the change of blood volume plays a decisive role while the effect of blood velocity altera-tion is negligible.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
文摘Objective To evaluate the feasibility of pulse transit time (PTT) arousals as an index of sleep fragmentation in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). Methods Individuals referred for evaluation of possible OSAHS underwent overnight polysomnography (PSG). Three conventional indices of sleep fragmentation [electroencephalography (EEG) arousals, apnea/hypopnea index (AHI), oxygen desaturation index (ODI)], PTT arousals, and Epworth sleepiness scale (ESS) were compared. Results PTT arousals were positively correlated with EEG arousals (r= 0.746, P<0.001), AHI (r= 0.786, P<0.001), and ODI (r= 0.665, P<0.001), respectively. But, both PTT arousals and EEG arousals had no correlation with ESS (r= 0.432, P=0.201; r= 0.196, P=0.591, respectively). Conclusion PTT arousals are correlated well with other standard measures estimating severity of OSAHS and potentially a non-invasive marker with which to measure the sleep fragmentation in patients with OSAHS.
文摘PuLse transit time(FIT)is used as a noninvasive and cull-less parameter to estimate blood pressure.In this paper,we develop an algorithm to obtain FTT rapidly,which is appropriate for micro-processor and could achieve good accuracy in PTT,even in noisy measurements.The algorithm is based on finite impulse response(FIR)filter to reduce the noise and an adaptive threshold to detect the significant points of ECG and PPG.Evaluation of this method is based on the signals from our PTr-based blood pressure devices.It is shown that the method works well for PPT calculation.
文摘Pulse transit time (PTT) is used as a noninvasive and cuff-less parameter to estimate blood pressure. In this paper, we develop an algorithm to obtain PTT rapidly, which is appropriate for micro-processor and could achieve good accuracy in PTT, even in noisy measurements. The algorithm is based on finite impulse response (FIR) filter to reduce the noise and an adaptive threshold to detect the significant points of ECG and PPG. Evaluation of this method is based on the signals from our PTT-based blood pressure devices. It is shown that the method works well for PPT calculation.
基金Project supported by the National Natural Science Foundation of China (Grant No 10774039)
文摘Using a time-dependent multilevel approach, we demonstrate that lithium atoms can be transferred to states of lower principle quantum number by exposing them to a frequency chirped microwave pulse. The population transfer from n = 79 to n = 70 states of lithium atoms with more than 80% efficiency is achieved by means of the sequential two-photon △n=-1 transitions. It is shown that the coherent control of the population transfer can be accomplished by the optimization of the chirping parameters and microwave field strength. The calculation results agree well with the experimental ones and novel explanations have been given to understand the experimental results.
文摘Continuous non-invasive blood pressure (BP) measurement can be realized by using pulse transit time (PTT) based on electrocardiogram (ECG) and pulse wave signal. Modulated magnetic signature of blood (MMSB) is a promising approach to obtain PTT. The origin of MMSB is critical to establish the relationship between MMSB and BP. In this paper, two possible origins of MMSB, blood disturbance mechanism and angular variation mechanism, are analyzed and verified through three control experi-ments under different conditions. The influence of blood velocity alteration and blood volume alteration on magnetic field is investigated though blood flow simulation sys-tem. It is found that MMSB comes mainly from the periodic blood flow while the per-turbation caused by angular variation between sensitive axis of the magnetic sensor and geomagnetic field can be neglected. As to blood disturbance mechanism, the change of blood volume plays a decisive role while the effect of blood velocity altera-tion is negligible.
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Supported by Advanced Space Medico-Engineering Research Project of China(SJ200903,SJ201006)State Key Laboratory of Space Medicine Fundamentals and Application(SMFA09A16)
