Amar Rouane

Simple and Efficient Compressed Sensing Encoder for Wireless Body Area Network

Compressed sensing (CS) is an emerging signal processing technique that enables sub-Nyquist measurement of signals having sparse representations in certain bases. Since most physiological signals treated within a wireless body area network (WBAN) are sparse, CS can be applied to WBANs to reduce the number of measurements and minimize the energy consumption of the sensor nodes. In this paper, we propose a simple and efficient CS encoder device used to measure signals within sensor nodes of a WBAN. A digital and an analog models of the proposed CS encoder are presented. As the CS encoder and decoder are tightly coupled, a model of the overall acquisition chain is required in the first stages of development and validation. To do this, we propose a virtual prototyping of the system with SystemC-AMS. A SPICE model and a hardware prototype of the proposed CS encoder are also presented. The simulation results of both models show that the proposed encoder was able to compressively measure an electrocardiogram (ECG) and an electroencephalogram signals with compression ratios of 6:1 and 4:1, respectively, which save 82.9% and 75% of the energy consumption of transceivers. The experiment results were consistent with those of the model and show that the hardware prototype was able to compressively measure an ECG signal with a compression ratio of 8:1. Comparison with a random demodulator (RD) was carried out and shows that the proposed encoder outperformed RD in terms of compression ratio and reconstruction quality.

Compressed Sensing: A Simple Deterministic Measurement Matrix and a Fast Recovery Algorithm

Compressed sensing (CS) is a technique that is suitable for compressing and recovering signals having sparse representations in certain bases. CS has been widely used to optimize the measurement process of bandwidth and power constrained systems like wireless body sensor network. The central issues with CS are the construction of measurement matrix and the development of recovery algorithm. In this paper, we propose a simple deterministic measurement matrix that facilitates the hardware implementation. To control the sparsity level of the signals, we apply a thresholding approach in the discrete cosine transform domain. We propose a fast and simple recovery algorithm that performs the proposed thresholding approach. We validate the proposed method by compressing and recovering electrocardiogram and electromyogram signals. We implement the proposed measurement matrix in a MSP-EXP430G2 LaunchPad development board. The simulation and experimental results show that the proposed measurement matrix has a better performance in terms of reconstruction quality compared with random matrices. Depending on the compression ratio, it improves the signal-to-noise ratio of the reconstructed signals from 6 to 20 dB. The obtained results also confirm that the proposed recovery algorithm is, respectively, 23 and 12 times faster than the orthogonal matching pursuit (OMP) and stagewise OMP algorithms.

Impedance measurement of a fuel cell on load

The improvement of the effectiveness and the life time of fuel cells requires the optimization of components such as membranes and electrodes and enhancement the flow of gases. To this end, the impedance measurement is essential. In this paper we present an electronic measurement instrumentation developed in our laboratory, to measure and plot the impedance of the fuel cell on load. Impedance measurements were taken by using the load modulation method. This instrumentation has been developed around a VXI system stand which controls electronic cards. Software under HPVEEreg was developed for automatic measurements and layout. The theoretical result obtained by a simulation under PSPICEreg consolidates us in the possibility of obtaining correct and exploitable results. The experimental results are preliminary results on a 12 V vehicle battery (Impedance measurements on a PEMFC are in progress). The similitude in the graph form and in order of magnitude of the values obtained (both theoretical and practical) enables us to validate our instrumentation. One of the future uses for this instrumentation is to integrate it on a vehicle as an embedded system to monitor the degradation of fuel cell membranes.

An Electronic Measurement Instrumentation of the Impedance of a Loaded Fuel Cell or Battery

In this paper we present an inexpensive electronic measurement instrumentation developed in our laboratory, to measure and plot the impedance of a loaded fuel cell or battery. Impedance measurements were taken by using the load modulation method. This instrumentation has been developed around a VXI system stand which controls electronic cards. Software under Hpvee® was developed for automatic measurements and the layout of the impedance of the fuel cell on load. The measurement environment, like the ambient temperature, the fuel cell temperature, the level of the hydrogen, etc…, were taken with several sensors that enable us to control the measurement. To filter the noise and the influence of the 50Hz, we have implemented a synchronous detection which filters in a very narrow way around the useful signal. The theoretical result obtained by a simulation under Pspice® of the method used consolidates the choice of this method and the possibility of obtaining correct and exploitable results. The experimental results are preliminary results on a 12V vehicle battery, having an inrush current of 330A and a capacity of 40Ah (impedance measurements on a fuel cell are in progress, and will be the subject of a forthcoming paper). The results were plotted at various nominal voltages of the battery (12.7V, 10V, 8V and 5V) and with two imposed currents (0.6A and 4A). The Nyquist diagram resulting from the experimental data enable us to show an influence of the load of the battery on its internal impedance. The similitude in the graph form and in order of magnitude of the values obtained (both theoretical and practical) enables us to validate our electronic measurement instrumentation. One of the future uses for this instrumentation is to integrate it with several control sensors, on a vehicle as an embedded system to monitor the degradation of fuel cell membranes.

New biosensor for non-invasive glucose concentration measurement

In this paper, a non-invasive method for measuring the concentration of glucose contained in a saline solution is presented. The principle and the method of an electromagnetic biosensor to determine the glucose concentration are described. The results show the reproducibility and the correlation between the signal characterizing the concentration and the concentration of glucose. The influence of temperature and its compensation and, more generally, the feasibility of this approach are stated. The results demonstrating the possibility to detect a concentration down to 0.1 g/l are also presented with the intent of biological applications.

Study of an electronic load for measuring the internal impedance of a PEM fuel cell

In order to further understanding the behavior of PEM fuel cell and optimize their performance, it is necessary to perform measurements in real time. The measure of internal impedance of a fuel cell in load is of great importance. In this work, we present the impedance measurement method of a PEM fuel cell by electrochemical impedance spectroscopy method (EIS), as well the study of an electronic load for the implementation of the measurement technique. The theoretical results are obtained by a simulation with PSPICE software.

SystemC-AMS based virtual prototyping of wireless body sensor network using compressed sensing

Compressed sensing (CS) is applied in wireless body sensor network (WBSN) to reduce the data rate and minimize the power consumption of the sensor nodes. However, as the CS encoder and decoder are tightly coupled, a model of the overall acquisition chain is required in the first stages of development and validation. To overcome this issue, we propose a virtual prototyping of WBSN based on CS with SystemC-AMS 1.0. The proposed model consists of three sensor nodes which capture electrocardiogram (ECG), electromyogram (EMG) and respiration (RESP) signals. The proposed virtual prototype had allowed a functional verification of WBSN at system level and a rapid exploration of the impact of compression ratio on the quality of reconstruction. Results show how to tailor the measurement matrix for a best tradeoff between the compression ratio, the quality of reconstruction, and the energy consumption.

Four electrode embedded bioimpedance measurement system

A new extension of the AD5933 impedance measurement chip is presented. It allows to use the chip in the four electrode configuration to reduce the artifact effects of interface impedance between the electrode and the sample to be measured. The measurement approach is validated on various test circuits, and the system has been able to measure small physiological samples (50 ul) in a four microelectrode configuration and with a low sensitivity to interface impedances. The system is a good candidate for any embedded bioimpedance measurement system which requires a low sensitivity to interface impedances.

Fast and efficient signals recovery for deterministic compressive sensing: Applications to biosignals

Compressed sensing is a technique that is suitable for compressing and recovering signals having sparse representations in certain bases. Compressed sensing has been widely used to optimize the measurement process of power and bandwidth constrained systems like wireless body sensor network. The central issues with compressed sensing are mainly the construction of measurement matrices and the development of efficient recovery algorithms. In this paper, we proposed a simple and fast recovery algorithm which performed a thresholding in the discrete cosine transform domain. We validated it by recovering electrocardiogram and electromyogram signals taken from the Phyiobank database. The simulation and experimental results have shown that the proposed recovery algorithm was 25 and 12 times faster than orthogonal matching pursuit and stagewise orthogonal matching pursuit, respectively. In addition, depending on the compression ratio, the signal-to-noise ratio of recovered signals were improved up to 2 dB.

Simple deterministic measurement matrix: application to EMG signals

In a wireless body sensor network (WBSN), the available energy and bandwidth are limited. Therefore, compressing the electromyogram (EMG) signal is of great importance since it is generally sensed at a relatively high frequency of the order of kHz. In this paper, we use the compressed sensing (CS) technique to compress and recover the EMG signal. The main advantage with CS is that its compression process requires less computational complexity. We propose a deterministic measurement matrix that greatly facilitates the implementation of the encoder device. The simulation and experiment results showed that the proposed approach can compress and recover the EMG signal without perceptible loss if the compression ratio was greater than or equal to 0.25, which saved up to 75 % of both the available bandwidth and power consumption of the transceiver. A comparison with the current stat-of-the-art of EMG compression shows that we obtained a better performance. Furthermore, the proposed encoder has the lowest computational complexity.