The electrical impedance method of peripheral vein detection is a novel approach, which offers the advantages of not being expensive and the capability of minimizing and reducing the difficulty of achieving intravenous access in many patients, especially pediatric and obese patients. The electrical impedance method of peripheral vein detection is based on the measurement of electrical impedance using the 4-electrode technique by applying a known alternating current of frequency 100 kHz and constant amplitude to a set of current electrodes and measuring the resulting surface potential at two separate electrodes. This paper presents the results of investigations to estimate the efficiency of this method.
Reda Abdelbaset, Mohamed El Dosoky and Mohamed T. El-Wakad
-processing. Second stage is the processing stage as shown in Fig.1 . In addition to the postprocessing stage in which the results are extracted and analyzed.
Block Diagram of the COMSOL model.
The pre-processing stage
As shown in Fig.1 , the pre-processing stage contains: firstly, the selection of space dimensions, however, 2D space dimension is preferred to simplify the model in order to reduce the running time and increase the efficiency of the model. Secondly, the selection of physics, the electric current module is preferred to simulate the applied
extensively applied time–frequency technique [ 8 , 9 , 10 , 11 ]. The wavelet transform gives a high resolution in the frequency and time domains.
High dimensionality of the feature space makes an increase in computational time and a decrease in classifycation accuracy. To build robust learning models, a subset of the relevant features should be determined. The main objectives of feature selection are making a faster and more efficient learning procedure, ameliorating the efficiency of classification and making a better understanding of the underlying process that
Elnaz Alizadeh-Haghighi, Samad Jafarmadar and Shahram Khalilarya
. Holland J. H Adaptation in Natural and Artifical Systems University of Michigan Press Michigan 1975
19 Goldberg, D. E. Genetic algorithm in search, optimization and machine learning. Reading MA Addison Wesley. 1989. Goldberg D. E Genetic algorithm in search, optimization and machine learning Reading MA Addison Wesley 1989
20 Safak, H, Sahin, M, Gulveren, B, Tomak, M. Efficiency of genetic algorithm and determination of ground state energy of impurity in a spherical quantum dot. Int. J. Mod. Phys. C, 2003; 14: 775-784. https://doi.org/10.1142/S
Mohammad Karimi Moridani, Fatemeh Choopani and Mandana Kia
patient. J Med Eng Technol.2016;40(3):87-98. https://doi.org/10.3109/03091902.2016.1139201 27028609 10.3109/03091902.2016.1139201 Moridani MK Setarehdan SK Nasrabadi AM Hajinasrollah E Non-linear feature extraction from HRV signal for mortalityprediction of ICU cardiovascular patient J Med Eng Technol 2016 40 3 87 98 https://doi.org/10.3109/03091902.2016.1139201
25 Moridani MK, Kia M, Choopani F. Development of computer-aided system to evaluate the lung efficiency using electricalimpedance tomography. 3 rd International Conference onElectrical
Kathrin Badstübner, Marco Stubbe, Thomas Kröger, Eilhard Mix and Jan Gimsa
, particularly in the advanced stages of the disease, who are refractory to conventional therapy [ 2 , 3 ]. However, the clinical DBS therapies may have not reached optimal efficiency. For example, the best target regions are not clear and the basic mechanisms of action remain poorly understood [ 4 ]. This situation results in a striking contrast between the boom of the clinical applications and a relatively poor knowledge in basic research. One reason for this contrast is the insufficient availability of chronic stimulation devices for small laboratory animals. In practice
258 voltages were taken for each image. The last part of the experiment involved simulation of the image using different algorithms like perturbations and sLORETA. The final image was simulated using the shrinking sLORETA-FOCUSS. The results of the experiment are shown in Fig. 9 illustrate the effects of different algorithms. It can be seen that the shrinking sLORETA-FOCUSS method produced images with good spatial resolution and the shrinking strategy increased computation efficiency greatly. Indeed, the only shortfall of this algorithm appears to be that it has
, the limited amount of energy of excitation signal spreads between multiple signal components with different frequencies during a short timeframe. Therefore, the power of corresponding individual components, equal to the square of their root-mean-square (RMS) values, decreases. The task to use the limited energy resources of signals most effectively and flexibly becomes necessary.
Concurrently, such an important criterion of the efficiency of impedance measurements – the signal-to-noise ratio (SNR) of measured signal – is proportional to the power of every
Mohsen Habib Nezhad, Khazaimatol S. Subari and Mehran Yahyavi
Generally EEG signal application is divided into three major groups: medical purposes [ 2 ]; biometric purposes [ 3 , 20 ]; and entertainment purposes [ 2 , 20 ].
In wireless EEG systems, the efficiency of using brainwaves for a specific purpose is strictly dependent on the performance of the wireless system. Undoubtedly, wireless communication gives us more capabilities to utilize EEG signals. However, a corresponding increase in the barriers for transmitting EEG occurs. In the next part, we will briefly discuss existing problems in
This paper presents a new system for measuring water conductivity as a function of electrophysical property (admittance). The system is cheap and its manufacturing is easy. In addition, it does not require any sort of electrolysis and calibration. The system consists of four electrodes made of silver (Ag 92.5 g to Cu 7.5 g) fixed in a plastic tube filled by water which allows the use of two and four electrode setups. The admittance (reciprocal of impedance) was measured for different water sources (distilled, rainfall, mineral, river and tap water) using different frequencies between 50 Hz and 100 kHz. These measurements were taken twice, first with four electrodes and then with two electrodes of two modes (inner and outer electrodes). The results showed good correlation between the measured admittance and the conductivity of all the water sources and the best correlation was found at low frequencies between 50 Hz and 20 kHz. The highest efficiency can be achieved by using the four electrode system which allows circumventing the effect of the electrode impedance. This result makes the system efficient compared to traditional conductivity meters which usually require high frequencies for good operation.