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Objective To explore the application of three parameter identification methods (impedance modulus curve method, impedance component method, and genetic algorithm) in solving parameter identification problem of the 11-element lumped parameter model in the circle of Willis. Methods Using the flow and pressure waveforms of the internal carotid arteries and vertebral arteries on both sides as inlet conditions, parameter values of the model under normal and bilateral vertebral artery stenosis conditions were calculated. The recognition algorithm was verified by using Simulink models, and finally the stability of the recognition algorithm was verified by adding a certain noise to the flow. Results Under normal circumstances, the proximal resistances obtained by the impedance modulus curve method were larger, and the resistances of the anterior communicating artery obtained by the impedance component method were larger. The genetic algorithm could obtain relatively reasonable model parameter values. In the case of vertebral artery stenosis on both sides, the impedance modulus curve method could obviously get the results of the increasement in proximal resistances of the posterior circulation, but the results obtained by the impedance component method and the genetic algorithm mainly lied in that the distal resistance had a larger increase. Conclusions There are still differences between the pressure data calculated by the parameters identified by the above three methods and the actual data, which are considered as modeling errors, source data errors and calculation errors. The impedance modulus curve method has a certain effect in distinguishing changes of the proximal and distal resistances, but there exist large errors in identification of some parameters. The impedance component method can identify the parameters, but this method is unstable with large calculation errors. Genetic algorithm can obtain a better approximate solution, but it has certain problems in distinguishing vertebral artery stenosis. The combination of impedance modulus curve method and genetic algorithm may play a better role in future application of this model for disease diagnosis.
ABSTRACT
The measurement of heart rate variability (HRV) has the advantages of noninvasiveness and simple operation and is widely used in clinical trials and scientific research for assessing reactions of the autonomic nervous system. More and more studies on acupuncture also take HRV as an important index. In addition to the definition, origin, analytical methods, and significance of time domain and frequency domain parameters of HRV, we reviewed the situations of application of HRV to acupuncture research in recent years, analyzed the influence of acupuncture and sham acupuncture, different acupuncture methods, and different acupoints on HRV, and confirmed the role of HRV in reflecting the effect of acupuncture on the vagal and sympathetic systems. However, various interference factors for HRV measurement and diverse methods for data analysis may lead to great differences in the experimental results of HRV and the interpretation of parameters. Therefore, careful analysis is needed in future studies on acupuncture with HRV as an observation index.
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This study was aimed to explore the feasibility of identification of traditional Chinese medicine (TCM) constitution based on photoplethysmography (PPG) frequency domain analysis,and to establish an automatic identification system (AIS) of TCM constitution with simple operation and good generalization.The Classification and Determination of Constitution in TCM was used to evaluate the subjects' constitutional state.Pulse wave sensor was used to collect the pulse wave signal.Spectral characteristics were analyzed by power spectrum analysis.Eight classification algorithms of data mining were used to establish the model of qi-insufficiency constitution.The results showed that the pulse wave harmonic peak was that qi-insufficiency constitution was higher than health group;the model was optimal when random forest algorithm was used;and the accuracy of 10-CV test was 80.4％.Sensitivity reached 73.2％.Specificity and receiver operator characteristic were all above 0.8.The model has certain reliability.It was concluded that it was feasible to identify qiinsufficiency constitution by means of frequency domain analysis of PPG.It provides preliminary work for the construction of AIS of TCM constitution as well as a simple and quick assistant tool for the constitution identification of subhealth group in family health care.
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This paper presents a novel algorithm of fault location for transmission line. Solving the network spectrum equations for different frequencies the fault can be located accurately by this algorithm with one terminal data of voltage and current, and the identified parameters, such as fault distance, fault resistance, and opposite terminal system resistance and inductance. The algorithm eliminates the influence of the opposite system impedance on the fault location accuracy, which causes the main error in traditional fault location methods using one terminal data. A method of calculating spectrum from sampled data is also proposed. EMTP simulations show the validity and higher accuracy of the fault location algorithm compared to the existing ones based on one terminal data.
ABSTRACT
This paper presents a novel algorithm of fault location for transmission line. Solving the network spectrum equations for different frequencies the fault can be located accurately by this algorithm with one terminal data of voltage and current, and the identified parameters, such as fault distance, fault resistance, and opposite terminal system resistance and inductance. The algorithm eliminates the influence of the opposite system impedance on the fault location accuracy, which causes the main error in traditional fault location methods using one terminal data. A method of calculating spectrum from sampled data is also proposed. EMTP simulations show the validity and higher accuracy of the fault location algorithm compared to the existing ones based on one terminal data.
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Objective:To study the relationship between different pulse forces and cyclical power(CP)of radial artery motion.Methods:39 patients’and 20 healthy persons’ ECG and pressure sphygmograms were collected synchronously with NX-1 sphygmograph.On the basis of automatic detecting R waves of ECG and FFT analysis of pressure sphygmograms with SPTool of MATLAB 7.0.1,change in frequency domain of radial artery motion with different forces was observed and CP was worked out.Results: There is signifi cant deviation between CP of pulse tracings with different forces(pulse tracings with powerful force〉pulse tracings with normal force〉pulse tracings with weak force).Conclusion: CP of radial artery motion can be used to discriminate pulse force.
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In this paper,heart rate (HR) and heart rate variability (HRV) are extracted from ECG,and the five indexes in both time and frequency domains are analyzed.The result shows that the standard deviation (SDNN) of R-R intervals,the value of total power (TP),the power value of low frequency (LF) of HRV and the value of LF/HF increase obviously,while the power value of high frequency (HF) decreases markedly after fatigue.The physical fatigue level is classified according to the rate of increase and decrease of the indexes above.It is suggested that these five ECG indexes be used to reflect and evaluate the degree of physical fatigue quantitatively.
ABSTRACT
OBJECTIVES: Power spectrum analysis decomposes the heart rate signal into its frequency components and facilitates separation of sympathetic (low frequency) and parasympathetic (high frequency) activity. In congestive heart failure, augmented sympathetic tone and decreased parasympathetic tone were found. Autonomic nervous system was normalized 6 months after myocardial infarction. So we compared the autonomic nervous system activity by the heart rate variability in congestive heart failure and old myocardial infarction. METHODS: The protocol involved 20 healthy subjects (Group 1), 5 congestive heart failure patients not caused by myocardial infarction (Group 2), 4 congestive heart failure patients due to myocardial infarction and 11 old myocardial infarction patients without heart failure. We took 24 hour Holter monitoring by Del Mar Avionic tape recorder. All Holter tapes were analyzed with use of Model 563 Stratascan Holter Analysis System. We computed power spectra on each 256 sec segment of each hour during 24 hour recording. So, RR interval, SD of RR interval by time domain, and LF, HF, LF/HF ratio, Total PSD by frequency domain were measured. RESULTS: In congestive heart failure, nocturnal HF peak and diurnal variation of LF/HF ratio was decreased relative to healthy subjects. Nocturnal HF peak in old myocardial infarction was not visualized. All of LF, HF and Total PSD in congestive heart failure and old myocardial infarction patients relative to healthy subjects. CONCLUSION: On heart rate variability analysis using by 24 hour Holter monitoring, abnormal autonomic nervous activity was demonstrated in congestive heart failure and old myocardial infarction patients relative to healthy subjects.