Pulse waves contain rich physiological and pathological information of the human vascular system. The pulse wave diagnosis systems are very helpful for the clinical diagnosis and treatment of cardiovascular diseases. Accurate pulse waveform is necessary to evaluate the performances of the pulse wave equipment. However, it is difficult to obtain accurate pulse waveform due to several kinds of physiological and pathological conditions for testing and maintaining the pulse wave acquisition devices. A pulse wave generator was designed and implemented in the present study for this application. The blood flow in the vessel was simulated by modeling the cardiovascular system with windkessel model. Pulse waves can be generated based on the vascular systems with four kinds of resistance. Some functional models such as setting up noise types and signal noise ratio (SNR) values were also added in the designed generator. With the need of portability, high speed dynamic response, scalability and low power consumption for the system, field programmable gate array (FPGA) was chosen as hardware platform, and almost all the works, such as developing an algorithm for pulse waveform and interfacing with memory and liquid crystal display (LCD), were implemented under the flow of system on a programmable chip (SOPC) development. When users input in the key parameters through LCD and touch screen, the corresponding pulse wave will be displayed on the LCD and the desired pulse waveform can be accessed from the analog output channel as well. The structure of the designed pulse wave generator is simple and it can provide accurate solutions for studying and teaching pulse waves and the detection of the equipments for acquisition and diagnosis of pulse wave.
Objective To analyze different characteristics of extra-vascular lung water ( EVLW) in the patients with acute respiratory distress syndrome( ARDS) , and examine its prognostic value. Methods 23 patients with ARDS admitted between November 2010 and December 2011 were divided into a survival group( n=13) and a dead group( n =10) according to the outcome. The hemodynamic status including extravascular lung water index( EVLWI) was measured in 3 consecutive days, and the relationship between EVLWI and the prognosis of patients was analyzed. Results On the first day of diagnosis, the EVLWI was higher in both groups in comparison with normal value. It was ( 13. 9 ±3. 45) mL/kg in the survival group and ( 14. 87 ±5. 75) mL/kg in the dead group( P gt;0. 05) . However, on the second day, the EVLWI in the survival group dropped significantly after intensive intervention, but the patients in the dead group did not respond well to the treatment and the EVLWI declined slightly. The EVLWI of both groups began to diverge significantly fromeach other, showing average value of ( 11. 07 ±2. 51) mL/kg and ( 15.63 ±5. 05) mL/kg, respectively( P lt; 0. 05) . On the third day, this difference between two groups was still more remarkable, resulting in ( 10.32 ±1.57) mL/kg vs. ( 16. 6 ±4. 33) mL/kg( P lt; 0. 01) . Conclusions The changes of EVLWI can be used to evaluate the effectiveness of treatment and predict the prognosis of patients with ARDS. EVLWI would likely be an indicator to evaluate the pulmonary capillary leakage.
摘要:目的: 评价机械通气对胸腔内脉搏氧饱和度的影响。 方法 :以食道、气管和降主动脉作为胸腔内脉搏氧饱和度的监测位点,将改制后的氧饱和度探头分别固定于上述部位,并连接于同一监护仪上。纯氧通气,待上述氧饱和度容积波波形和读数稳定,停止机械通气30s。以录像的方式记录机械通气停止前后30 s内食道、气管和降主动脉SpO2容积波和读数的变化。同时记录舌SpO2。 结果 :机械通气时,食道、气管和降主动脉三个监测位点均可获得异常高大的SpO2容积波;停止通气时,异常高大的氧饱和度波形消失。食道、气管和降主动脉脉搏容积波变异率分别为112%,74%,302%。降主动脉脉搏容积波的变异率明显高于食道和气管( 〖WTBX〗P ＜005)。机械通气停止前后30s内食道、气管和降主动脉的SpO2读数变化无显著差异(〖WTBX〗P ＞005)。 结论 :机械通气对胸腔内食道、气管和降主动脉氧饱和度读数无影响,主要影响是脉搏容积波。且各位点间脉搏氧容积波受呼吸的影响不同。Abstract: Objective: To investigate the impact of mechanical ventilation on pulse oximetry in thoracic cavity. Methods : After dogs anesthesia induction and thoracotomy, pulse oximeters were simultaneously placed at esophagus, trachea, and descending aorta, and connected with the same monitor for SpO2 monitoring. During ventilation with 100% oxygen, the mechanical ventilator was temporarily switched off for 30 seconds after high quality PPG waveforms and SpO2 readings were obtained. SpO2 signals and readings from esophagus (SeO2), trachea (StraO2), descending aorta (SDAO2) shown on the monitoring screen were recorded by the SONY video before and after stopventilation. And StonO2 were also recorded. Results : Abnormally largeamplitude PPG waves were found in normal waves at monitoring sites of esophagus, trachea, and descending aorta in all animals during ventilation; however, they disappeared without ventilator. The variation rate in ventilationinduced PPG amplitude were 112%, 74%, 302% at esophagus, trachea and descending aorta respectively. The PPG amplitude variation rate from SDAO2 was higher than that from SeO2 and StraO2 (〖WTBX〗P ＜005). However, the SpO2 readings obtained from pulse oximetries in all sites were no significantly statistical difference within 30s before and after temporarily stopventilation (〖WTBX〗P ＞005). Conclusion : Abnormally amplitude PPG waveforms from oximetry probe placed at esophagus, trachea, and descending aorta were induced by ventilation. The Variation rate in ventilationinduced PPG amplitude was various at different monitoring sites. The SpO2 readings from esophagus, trachea, and descending aorta were not significantly contaminated by ventilation.
The performance of a pulse oximeter based on photoelectric detection is greatly affected by motion noise (MA) in the photoplethysmographic (PPG) signal. This paper presents an algorithm for detecting motion oxygen saturation, which reconstructs a motion noise reference signal using ensemble of complete adaptive noise and empirical mode decomposition combined with multi-scale permutation entropy, and eliminates MA in the PPG signal using a convex combination least mean square adaptive filters to calculate dynamic oxygen saturation. The test results show that, under simulated walking and jogging conditions, the mean absolute error (MAE) of oxygen saturation estimated by the proposed algorithm and the reference oxygen saturation are 0.05 and 0.07, respectively, with means absolute percentage error (MAPE) of 0.05% and 0.07%, respectively. The overall Pearson correlation coefficient reaches 0.971 2. The proposed scheme effectively reduces motion artifacts in the corrupted PPG signal and is expected to be applied in portable photoelectric pulse oximeters to improve the accuracy of dynamic oxygen saturation measurement.
Objective To explore the hemodynamic monitoring value of pulse-indicated continuous cardiac output( PiCCO) during lung transplantation. Methods Twenty patients with end-stage lung disease undergone lung transplantation were enrolled. Hemodynamic states were monitored by PiCCO and Swan-Ganz standard thermodilution pulmonary artery catheter( PAC) simultaneously at six stages throughout the study. Changes in the variables were calculated by subtracting the first fromthe second measurement( Δ1 ) and so on ( Δ1 to Δ5 ) . Results The linear correlation between intra-thoracic blood volume index( ITBVI) and stroke volume index( SVIpa) was significant ( r = 0. 654, P lt; 0. 05) , whereas pulmonary artery wedge pressure ( PAWP) poorly correlated with SVIpa( P gt; 0. 05) . Changes in ITBVI correlated with changes in SVIpa ( Δ1 , r =0. 621; Δ2 , r = 0. 784; Δ3 , r = 0. 713; Δ4 , r = 0. 740; Δ5 , r = 0. 747; all P lt; 0. 05) , whereas PAWP failed. The mean bias between CIart and CIpa was ( 0. 09 ±0. 5) L·min-1 ·m-2 ; the limit of agreement was ( - 0. 89 ～1. 07) L·min-1 ·m-2 . Conclusions There is good correlation between the two methods of PiCCO and PAC for reflecting the change of heart preload. PiCCO is reliable in hemodynamic monitoring in patients undergone lung transplantation.
In order to solve the saturation distortion phenomenon of R component in fingertip video image, this paper proposes an iterative threshold segmentation algorithm, which adaptively generates the region to be detected for the R component, and extracts the human pulse signal by calculating the gray mean value of the region to be detected. The original pulse signal has baseline drift and high frequency noise. Combining with the characteristics of pulse signal, a zero phase digital filter is designed to filter out noise interference. Fingertip video images are collected on different smartphones, and the region to be detected is extracted by the algorithm proposed in this paper. Considering that the fingertip’s pressure will be different during each measurement, this paper makes a comparative analysis of pulse signals extracted under different pressures. In order to verify the accuracy of the algorithm proposed in this paper in heart rate detection, a comparative experiment of heart rate detection was conducted. The results show that the algorithm proposed in this paper can accurately extract human heart rate information and has certain portability, which provides certain theoretical help for further development of physiological monitoring application on smartphone platform.
As one of the standard electrophysiological signals in the human body, the photoplethysmography contains detailed information about the blood microcirculation and has been commonly used in various medical scenarios, where the accurate detection of the pulse waveform and quantification of its morphological characteristics are essential steps. In this paper, a modular pulse wave preprocessing and analysis system is developed based on the principles of design patterns. The system designs each part of the preprocessing and analysis process as independent functional modules to be compatible and reusable. In addition, the detection process of the pulse waveform is improved, and a new waveform detection algorithm composed of screening-checking-deciding is proposed. It is verified that the algorithm has a practical design for each module, high accuracy of waveform recognition and high anti-interference capability. The modular pulse wave preprocessing and analysis software system developed in this paper can meet the individual preprocessing requirements for various pulse wave application studies under different platforms. The proposed novel algorithm with high accuracy also provides a new idea for the pulse wave analysis process.
Photoplethysmography (PPG) is often affected by interference, which could lead to incorrect judgment of physiological information. Therefore, performing a quality assessment before extracting physiological information is crucial. This paper proposed a new PPG signal quality assessment by fusing multi-class features with multi-scale series information to address the problems of traditional machine learning methods with low accuracy and deep learning methods requiring a large number of samples for training. The multi-class features were extracted to reduce the dependence on the number of samples, and the multi-scale series information was extracted by a multi-scale convolutional neural network and bidirectional long short-term memory to improve the accuracy. The proposed method obtained the highest accuracy of 94.21%. It showed the best performance in all sensitivity, specificity, precision, and F1-score metrics, compared with 6 quality assessment methods on 14 700 samples from 7 experiments. This paper provides a new method for quality assessment in small samples of PPG signals and quality information mining, which is expected to be used for accurate extraction and monitoring of clinical and daily PPG physiological information.
The pulse amplitude of fingertip volume could be improved by selecting the vascular dense area and applying appropriate pressure above it. In view of this phenomenon, this paper used Comsol Multiphysics 5.6 (Comsol, Sweden), the finite element analysis software of multi-physical field coupling simulation, to establish the vascular tissue model of a single small artery in fingertips for simulation. Three dimensional Navier-Stokes equations were solved by finite element method, the velocity field and pressure distribution of blood were calculated, and the deformation of blood vessels and surrounding tissues was analyzed. Based on Lambert Beer's Law, the influence of the longitudinal compression displacement of the lateral light surface region and the tissue model on the light intensity signal is investigated. The results show that the light intensity signal amplitude could be increased and its peak value could be reduced by selecting the area with dense blood vessels. Applying deep pressure to the tissue increased the amplitude and peak of the signal. It is expected that the simulation results combined with the previous experimental experience could provide a feasible scheme for improving the quality of finger volume pulse signal.