Signal Acquisition Method Research Articles

Fast Acquisition of GPS Signal Using FFT Decomposition

Acquisition in Global Positioning System (GPS) is primary and important step to measure the code phase of Pseudo Random Noise (PRN) code and Doppler shift in carrier frequency of received GPS signal. The performance of a GPS receiver system depends on the fast and accurate measure of the code phase and Doppler shift in the recived signal. A new GPS signal acquisition method based on decomposition of FFT is proposed to improve the acquisition performance. Conventional GPS receivers use Fast Fourier Transform (FFT) to carry out correlation in the acquisition process. However, this paper proposes a new method that reduces the complexity of FFT computation. The proposed algorithm is implemented, validated and compared the performance with conventional serial search and radix2 FFT search algorithms using Intermediate Frequency (IF) GPS signal. Acquisition algorithms are implemented on 1.25MHz signal data of one millisecond period, sampled at 5MHz. For the sampled data, the proposed algorithm uses 5000 samples insted of number of samples raised to nearest power of 2 i.e. 8192 samples as in the case of radix2 FFT search method to compute FFT. Performance of the algorithms are compared based on computational time and correlation peak magnitude.

A Fast Algorithm of Compressed Sensing for 2D Signals

ABSTRACTCompressed sensing (CS) is a new signal acquisition method that can do sampling and compression of signals simultaneously. In order to reduce the signal reconstruction time of CS algorithms and lower the growth rate of the reconstruction time when increasing the size of signals, this paper proposes the algorithm of block whole orthogonal matching pursuit (BWOMP), which is a fast CS algorithm based on the method of orthogonal matching pursuit (OMP) for two-dimension (2D) signals. BWOMP defines a measurement parameter named whole-correlation. At each iteration, instead of computing the correlation between each atom and 1D residuals, the whole-correlation is computed as the correlation between the atom and the 2D residuals. After that, an approximation of the 2D signal is generated directly by BWOMP. By reducing the number of the iterations, this method can significantly lower the computational complexity. On the other hand, BWOMP introduces the concept of block compressed sensing (BCS), and redesigns the block size and the observation matrix. BCS reduces the consumption of computational resources (i.e. memory and CPU cycles) by reducing the size of variables (especially the matrixes). The experimental comparisons show that, in comparison with OMP, BWOMP can save at least 80% reconstruction time, which makes the increasing rate of reconstruction time linear. The results indicate that the proposed algorithm may have great performance advantage for complex cases.

Neck Cardiography and Fractal Analysis of its Wavelet Transform Modified Signal

Electrocardiography (ECG) deals with recording of the electrical activity of heart muscles. Usual method of ECG recording is done using 12-Lead system. The paper deals with a new method of recording the electrical activity of heart from the neck region (carotid artery). The waveform obtained is known as Neck cardiogram (NCG). It uses a simple method of signal acquisition, using three surface electrodes and an amplifier. The work aims to prove the significance of NCG in diagnosis of certain diseases that may not be prominent in normal ECG. The acquired ECG and NCG of the patient is compared using Matlab software and LabVIEW environment. The analysis of the waveforms is done using Daubechies wavelet transform and Higuchi fractal dimension. The analysis was done on large group of subjects including thyroid patients, cardiac patients and healthy subjects. The results obtained suggested NCG can be used as a tool to diagnose certain abnormalities. NCG can be used to record heart’s electrical activity for people with no upper limbs. This method of single lead system provides easier way of recording heart’s activity compared to the chest electrodes used in 12-lead system.

Compressive sensing and sparse decomposition in precision machining process monitoring: From theory to applications

Precision machining has been claimed to be the backbone to modern industry. It has been widely applied to the key parts’ production in the aerospace, medical and automotive industries. One of the main problems related to precision machining productivity and safety is the machining condition. By utilizing the acquired information from sensory measurements to direct the further actions, the signal processing bridges the gap between human instruction and full automation. Traditional signal acquisition and processing methods are mainly based on Shannon’s Sampling theory, Fourier methods or wavelet analysis. While these techniques meet challenges in precision machining environment, such as machining at high speed, low signal to noise ratio, and high sampling rate. These factors limit their applications especially the online monitoring implementation. The newly developed compressive sensing theory and sparse decomposition techniques provide a possible solution to these problems, while limited studies have been investigated. This paper serves as an introduction to the theory and shows the theory’s potentials in machining condition monitoring by reviewing related literatures and demonstrating case studies from real experiments.

Magnetic-based biomolecule detection using giant magnetoresistance sensors

This paper presents a novel microfluidic chip for in-vitro detection of biomolecules tagged by magnetic microparticles (MAPs) suspended in a static fluid. The system consists of two microfluidic channels: a reference channel in which bare MAPs are suspended and a detection channel in which magnetically tagged biomolecules are suspended (LMAPs). The LMAPs are functionalized MAPs (of the same magnetic volume as the ones in the reference channel) with attached biomolecules. The overall, non-magnetic volume of the LMAPs is greater than that of the bare MAPs. Current carrying microconductors are positioned underneath the channels in order to impose a magnetic field gradient to the MAPs and LMAPs and move them from the inlet to the outlet of the channels without flow. The innovative aspect of the proposed method is that the induced velocity on the MAPs and LMAPs, while imposed to the same magnetic field gradient, is inversely proportional to their overall, non-magnetic volume. This is due to the enhanced Stokes drag force exerted on the LMAPs, resulting from the greater volume and altered hydrodynamic shape. This induced velocity is measured by utilizing Giant Magnetoresistance (GMR) sensor pairs fabricated underneath the first and the last microconductors. Detected differences in velocity between the LMAPs and the reference MAPs indicate the presence of biomolecules in the static liquid sample. We also present a novel method for signal acquisition and demodulation: expensive function generators, data acquisition devices, and lock-in amplifiers were substituted by a generic PC sound card and an algorithm combining the Fast Fourier Transform of the signal with a peak detection routine. Experiments with functionalized MAPs and magnetically tagged Escherichia coli (representing the LMAPs) were carried out as a proof of concept. In order to identify the detection limit of the GMR sensor, single MAP (2.8 μm diameter) detection was performed.

A novel biometric authentication approach using ECG and EMG signals

Security biometrics is a secure alternative to traditional methods of identity verification of individuals, such as authentication systems based on user name and password. Recently, it has been found that the electrocardiogram (ECG) signal formed by five successive waves (P, Q, R, S and T) is unique to each individual. In fact, better than any other biometrics’ measures, it delivers proof of subject’s being alive as extra information which other biometrics cannot deliver. The main purpose of this work is to present a low-cost method for online acquisition and processing of ECG signals for person authentication and to study the possibility of providing additional information and retrieve personal data from an electrocardiogram signal to yield a reliable decision. This study explores the effectiveness of a novel biometric system resulting from the fusion of information and knowledge provided by ECG and EMG (Electromyogram) physiological recordings. It is shown that biometrics based on these ECG/EMG signals offers a novel way to robustly authenticate subjects. Five ECG databases (MIT-BIH, ST-T, NSR, PTB and ECG-ID) and several ECG signals collected in-house from volunteers were exploited. A palm-based ECG biometric system was developed where the signals are collected from the palm of the subject through a minimally intrusive one-lead ECG set-up. A total of 3750 ECG beats were used in this work. Feature extraction was performed on ECG signals using Fourier descriptors (spectral coefficients). Optimum-Path Forest classifier was used to calculate the degree of similarity between individuals. The obtained results from the proposed approach look promising for individuals’ authentication.

Algorithm for heart rate extraction in a novel wearable acoustic sensor.

Phonocardiography is a widely used method of listening to the heart sounds and indicating the presence of cardiac abnormalities. Each heart cycle consists of two major sounds – S1 and S2 – that can be used to determine the heart rate. The conventional method of acoustic signal acquisition involves placing the sound sensor at the chest where this sound is most audible. Presented is a novel algorithm for the detection of S1 and S2 heart sounds and the use of them to extract the heart rate from signals acquired by a small sensor placed at the neck. This algorithm achieves an accuracy of 90.73 and 90.69%, with respect to heart rate value provided by two commercial devices, evaluated on more than 38 h of data acquired from ten different subjects during sleep in a pilot clinical study. This is the largest dataset for acoustic heart sound classification and heart rate extraction in the literature to date. The algorithm in this study used signals from a sensor designed to monitor breathing. This shows that the same sensor and signal can be used to monitor both breathing and heart rate, making it highly useful for long-term wearable vital signs monitoring.

A new method to access information for underground omni-dimensional vibration vector

Purpose – The purpose of this paper is to propose a new method to achieve omni-directional vibration vector signal acquisition, and use this method to improve the accuracy of the underground explosion point localization. Design/methodology/approach – Following an introduction, this paper describes the design principle of a sensor structure, and discusses the rationality of the spherical structure of the sensor through finite element analysis. The sensor prototype is designed according to the above method, and its performance is tested by the sensor calibration experiment. Finally, applications are also discussed. Findings – This paper shows that the method for underground omni-directional vibration signal acquisition is reasonable and feasible. The vibration sensor, designed by this method, of which the triaxial dynamic characteristics are consistent, and the three-dimensional vibration information acquired by this sensor can achieve high-precision localization for an underground explosion point. Originality/value – The paper describes a new method for omni-directional vibration vector signal acquisition. The vibration sensor is developed based on this method, which has a broad application prospect in the positioning of an underground explosion point, the evaluation of explosive power and other underground projects.

A transient signal acquisition and processing method for micro-droplet injection system inductively coupled plasma mass spectrometry (M-DIS-ICP-MS)

An optimal signal acquisition and processing method for use with intermittent small-sized sample introduction techniques, such as the micro-droplet injection system (M-DIS), was investigated.

A Method of Acquiring and Processing GIC Signal in High-Speed Rail Track Circuit

The high-speed railway is a typical ground systems, if subjected to a larger GIC, will lead to serious incidents. For the power supply and wiring pattern of high-speed railway is different from the public grid, then how to monitor the GIC impact on the high-speed rail electrical systems need to be studied. The paper study the process and pattem of GIC in high-speed rail track circuit, and propose a signal acquisition method of GIC in the track circuit. The sampled signal will be go through the low-pass filter designed by the window function to obtain the GIC.

An Efficient Signal Acquisition Method for GPS Software-Defined Radio Receivers

With the development of the computationalpower of programmable processors, the Software-DefinedRadio (SDR) approach for GPS receivers has been widelyconsidered. However, in comparison with the conventionalhardware receivers, the computational speed of the SDRreceivers is still a problem needed to be improved. As afirst process of the digital processing part, and also themost resource consuming process of a GPS receiver, thesignal acquisition process is very important and neededto be improved in order to suit with the SDR approach.This paper introduces a hybrid signal acquisition methodleveraging the conventional serial search acquisition (typical in hardware receivers), and the FFT-based parallelsearch (typical in SDR receivers) in order to significantlyimprove the acquisition sensitivity, meanwhile keep thecomputational complexity still comparable with that of theFFT-based parallel method.

English

Hospitals need several measurement systems that can measure physiological parameters of the patient. Measurement systems should be able to measure accurately the vitals of patients like heart conditions, body temperature, electrical activity of the muscles etc. Approaching EMG is used to monitor the patient during the exercise and advise him to stop as he is the fatigue condition. During muscle activation, the signal is produced from small electrical currents generated by the exchange of ions across the muscle membranes using surface electrodes is amplified and recorded with instrument known as the EMG. The pc based signal acquisition is efficient and effective method for biomedical signal acquisition and monitoring. In this paper a simple and cost effective method for detecting voluntary muscle movement of human being is proposed .in this work .EMG signal is picked up from the hand biceps using simple computer interface and processed by MATLAB based filter algorithm for online clean display.

A Review on Signal Acquisition Methods for Tool Wear Monitoring in Turning Process

On-line monitoring of tool wear in turning is vital to increase machine utilization as scrapped components, machine tool breakage and unscheduled downtime result from worn tool usage cause huge economic loss. Several techniques have been developed for monitoring wear levels on the cutting tool on-line. Keeping in to account the difficulties encountered during the implementation of tool condition monitoring (TCM). The signal acquisition is one of the key elements used during the implementation of TCM. This paper provides an in depth coverage of various signal acquisition methods used in TCM.

Technologies for Developing Ambulatory Cough Monitoring Devices

Cough is a prevailing symptom in most lung diseases. While cough sounds themselves can be very instrumental in the diagnosis of certain diseases, their intensity and frequency also infers the intensity of the particular illness. There is an imperative need for a robust system for identifying and analyzing cough sounds. In implementing such systems, researchers are confronted with technical challenges such as the choice of sensors and methods of signal acquisition, the real time analysis of the acquired signals, and the accurate identification of cough events, distinguishing them from similar sounds such as speech, laughing, throat clearing and sneezing. Previous approaches have employed external environmental sensing methods to achieve more accurate detections at the expense of mobility, scalability and real-time cough sensing. Alternative approaches have proposed wearable cough sensing methods, which, while mobile, can often face challenges in terms of robustness and obtrusiveness. In this paper, we explore the strengths and shortcomings of the various techniques that have been proposed for automatic detection and analysis of cough sounds. We also suggest the next steps in furthering the state of the art.

一种基于KSVD-ETF的测量矩阵优化方法

压缩感知将数据的采样和压缩同时处理，仅需少量测量就能重建信号。测量矩阵直接影响着信号适应的稀疏度范围和重建效果。为了减小测量矩阵与稀疏变换矩阵的互相干性，提出一种基于KSVD-ETF的测量矩阵和稀疏表达字典联合优化的方法，在对测量矩阵进行ETF优化的同时利用KSVD方法更新优化表达字典，实验结果中利用该方法优化矩阵所得重建信号PSNR有所提高，表明优化测量矩阵的方法在重建效果方面有一定的优势。 Compressive sensing, a novel signal acquisition method, is a joint sensing-compression process which requires a small number of measurements to reconstruct signal. Measurement matrix, a very important part in compressive sensing, directly affects the adaptive sparsity, the required number of measurements and the reconstruct performance of the signal. In order to decrease the mutual coherence between the measurement matrix and sparse transformed matrix and improve the quality of reconstruction, this paper addresses the joint optimization between measurement matrix and sparse dictionary based on the KSVD-ETF. While optimizing the measurement matrix by ETF, we use the KSVD method to update the dictionary. The PSNR of the reconstructed signal is improved with the optimized measurement matrix from the experimental results, indicating that this method of optimizing the measurement matrix has certain advantages in the effect of reconstruction.

Advances in Signal Acquisition and Signal Processing of Coriolis Flow Meters

Abstract Smart signal acquisition and signal processing methods are necessary for a robust and highly dynamic mass flow measurement on basis of the Coriolis principle, which allows the direct determination of the mass flow independent of process conditions with a precision of 0.2% of reading. Optical sensors which record the movement of the flow pipe have been designed and arranged with focus on fast signal processing and low complexity for a Cramer-Rao optimal information analysis. Therefore it is possible to recognize and compensate superimposed movements of the flow pipe in all six degrees of freedom as well as aging effects of the sensor elements. This leads to an increased zero point stability and a greater flow measurement range. Several algorithms for online phase estimation like Hilbert transform, correlation, discrete-time Fourier transform and quadrature demodulation in combination with minimum phase filters are investigated to develop a system with minimal time delay.

High-sensitive GPS signal acquisition method based on wavelet filtering

With regard to the low operation efficiency of Global Positioning System(GPS) weak signal high-sensitive acquisition algorithm,a new acquisition method applying wavelet transform and synchronized data blocks accumulation was proposed.The sampled Intermediate Frequency(IF) signal was processed using discrete wavelet transform and Signal-to-Noise Ratio(SNR) was improved by the different characteristics of useful signal and noise during wavelet transform.Meanwhile the quantity of baseband data was decreased.Frequency compensation and synchronized data blocks accumulation method were adopted to reduce the Doppler search range and improve SNR effectively.The simulation results show that compared with traditional high-sensitive acquisition method,the proposed method can obviously reduce the acquisition time and improve the performance of weak signal acquisition.

Development and Validation of a Combined Methodology for Assessing the Total Quality Control of Herbal Medicinal Products – Application to Oleuropein Preparations

Oleuropein (OE) is a secoiridoid glycoside, which occurs mostly in the Oleaceae family presenting several pharmacological properties, including antioxidant, cardio-protective, anti-atherogenic effects etc. Based on these findings OE is commercially available, as Herbal Medicinal Product (HMP), claimed for its antioxidant effects. As there are general provisions of the medicine regulating bodies e.g. European Medicines Agency, the quality of the HMP’s must always be demonstrated. Therefore, a novel LC-MS methodology was developed and validated for the simultaneous quantification of OE and its main degradation product, hydroxytyrosol (HT), for the relevant OE claimed HMP’s. The internal standard (IS) methodology was employed and separation of OE, HT and IS was achieved on a C18 Fused Core column with 3.1 min overall run time employing the SIM method for the analytical signal acquisition. The method was validated according to the International Conference on Harmonisation requirements and the results show adequate linearity (r2 > 0.99) over a wide concentration range [0.1–15 μg/mL (n=12)] and a LLOQ value of 0.1 μg/mL, for both OE and HT. Furthermore, as it would be beneficial to control the quality taking into account all the substances of the OE claimed HMP’s; a metabolomics-like approach has been developed and applied for the total quality control of the different preparations employing UHPLC-HRMS-multivariate analysis (MVA). Four OE-claimed commercial HMP’s have been randomly selected and MVA similarity-based measurements were performed. The results showed that the examined samples could also be differentiated as evidenced according to their scores plot. Batch to batch reproducibility between the samples of the same brand has also been determined and found to be acceptable. Overall, the developed combined methodology has been found to be an efficient tool for the monitoring of the HMP’s total quality. Only one OE HMP has been found to be consistent to its label claim.

Acquisition technology research of EEG and related physiological signals under +Gz acceleration

With the continuous improvement of maneuvering performance of modern high-performance aircraft, the protection problem of flight personnel under high G acceleration, the development as well as research on monitoring system and the equipment for human physiological signals processing which include electroencephalogram (EEG) have become more and more important. Due to the particularity of +Gz experimental conditions, the high-risk of human experiments and the great difficulty of dynamic measurement, there is little research on the synchronous acquisition technology of EEG and related physiological signals under +Gz acceleration environment. We propose a framework to execute human experiments using the three-axial high-performance human centrifuge, develop reasonable operation mode and design a new experimental research method for EEG signal acquisition and variation characteristics on three-axial high-performance human centrifuge under the environment of +Gz acceleration. We also propose to build the synchronous real-time acquisition plan of EEG, electrocardiogram, brain blood pressure, ear pulse and related physiological signals under centrifuge +Gz acceleration with different equipments and methods. The good profiles of EEG, heart rate, brain blood pressure and ear pulse are obtained and analyzed comparatively. In addition, the FMS hop-by-hop continuous blood pressure and hemodynamic measurement system Portapres are successfully applied to the ambulatory blood pressure measure under centrifuge +Gz acceleration environment. The proposed methods establish the basis and have an important guiding significance for follow-up experiment development, EEG features spectral analysis and correlation research of all signals.

Fast Algorithm with Improved Circular Correlation Method for GPS Signal Acquisition

In order to improve acquisition speed and carrier frequency accuracy, a fast algorithm to acquire GPS signal is proposed. Signal-to-Noise Ratio is improved by coherent integration and non-coherent integration. The advantages of serial sliding algorithm and circular correlation algorithm are combined to achieve high carrier frequency accuracy. Removing the information of C/A code makes serial search from two-dimensional to one-dimensional to achieve less computation. Simulation shows weak signal of-30dB S/N is successfully acquired. The error of carrier frequency is controlled within 50Hz. So the data processing efficiency for the tracking loop is greatly increased.