S. Marco

Signal and Data Processing for Machine Olfaction and Chemical Sensing: A Review

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing.

Gas identification with tin oxide sensor array and self organizing maps: adaptive correction of sensor drifts

Low cost tin oxide gas sensors are inherently nonspecific. In addition they feature several non-desirable behaviors such as slow time response, nonlinearities and long term drifts. This paper shows that the combination of a gas sensor array together with self organizing maps can solve the gas classification problems. That is, the system is able to determine the gas present in the test chamber with error rates lower than 3%. The correction of the sensor drift with an adaptative SOM has also been investigated.

High-performance piezoresistive pressure sensors for biomedical applications using very thin structured membranes

High-sensitivity pressure sensors for invasive blood pressure measurements are described. To reduce the unavoidable nonlinearity increase with sensitivity, structured membranes are used. A novel technology based on electrochemical etch-stop and n-diffusions with different junction depths is used to obtain bosses of reduced thicknesses. Based on this technology new structures for pressure sensors have been assessed. The results show that these devices exhibit performances impossible to achieve with classical designs based on flat diaphragms.

An intelligent detector based on temperature modulation of a gas sensor with a digital signal processor

Abstract An intelligent detector based on a hot-plate gas sensor and a digital signal processor (DSP) is presented. The work comprises sensor measurements and gas identification with a pattern recognition (PARC) system along with a systematic verification of both stages, thanks to clustering validity methods and performance tests. Commercial silicon micromachined tin-oxide sensors have been used to capture dynamic measurements modulating the sensor heater at different temperatures, waveforms and frequencies. Feature extraction is based on the spectral and transient analysis of the sensor output signals. The PARC systems are based on self-organizing maps (SOM) and recent variations of these well-known neural networks. The proposed hardware is in charge of the whole system: the sensor temperature modulation and signal processing.

Design of a modular micropump based on anodic bonding

A simple and reliable technology for the fabrication of micromachined micropumps is presented. The assembling of different wafers to produce valves and cavities is usually the critical step regarding final yield. Our technology uses exclusively the well known anodic bonding technique for this purpose. The prospective performance of the devices has been evaluated by finite element methods and system level simulations.

Thermal modeling and management in ultrathin chip stack technology

This paper presents a thermal modeling for power management of a new three-dimensional (3-D) thinned dies stacking process. Besides the high concentration of power dissipating sources, which is the direct consequence of the very interesting integration efficiency increase, this new ultra-compact packaging technology can suffer of the poor thermal conductivity (about 700 times smaller than silicon one) of the benzocyclobutene (BCB) used as both adhesive and planarization layers in each level of the stack. Thermal simulation was conducted using three-dimensional (3-D) FEM tool to analyze the specific behaviors in such stacked structure and to optimize the design rules. This study first describes the heat transfer limitation through the vertical path by examining particularly the case of the high dissipating sources under small area. First results of characterization in transient regime by means of dedicated test device mounted in single level structure are presented. For the design optimization, the thermal draining capabilities of a copper grid or full copper plate embedded in the intermediate layer of stacked structure are evaluated as a function of the technological parameters and the physical properties. It is shown an interest for the transverse heat extraction under the buffer devices dissipating most the power and generally localized in the peripheral zone, and for the temperature uniformization, by heat spreading mechanism, in the localized regions where the attachment of the thin die is altered. Finally, all conclusions of this analysis are used for the quantitative projections of the thermal performance of a first demonstrator based on a three-levels stacking structure for space application.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

A portable electronic nose based on embedded PC technology and GNU/Linux: hardware, software and applications

This paper describes a portable electronic nose based on embedded PC technology. The instrument combines a small footprint with the versatility offered by embedded technology in terms of software development and digital communications services. A summary of the proposed hardware and software solutions is provided with an emphasis on data processing. Data evaluation procedures available in the instrument include automatic feature selection by means of SFFS, feature extraction with linear discriminant analysis (LDA) and principal component analysis (PCA), multi-component analysis with partial least squares (PLS) and classification through k-NN and Gaussian mixture models. In terms of instrumentation, the instrument makes use of temperature modulation to improve the selectivity of commercial metal oxide gas sensors. Field applications of the instrument, including experimental results, are also presented.

A time-domain method for the analysis of thermal impedance response preserving the convolution form

The study of the thermal behavior of complex packages such as multichip modules (MCMs) is usually carried out by measuring the so-called thermal impedance response, that is: the transient temperature after a power step. From the analysis of this signal, the thermal frequency response can be estimated, and consequently, compact thermal models may be extracted. We present a method to obtain an estimate of the time constant distribution underlying the observed transient. The method is based on an iterative deconvolution that produces an approximation to the time constant spectrum while preserving a convenient convolution form. This method is applied to the obtained thermal response of a microstructure as analyzed by finite element method as well as to the measured thermal response of a transistor array integrated circuit (IC) in a SMD package.

A new method to analyse signal transients in chemical sensors

Many chemical sensors exhibit exponentially decaying responses to a step change in the concentration. The determination of the time constant can greatly improve the specificity of the sensor. A spectroscopic method to determine the time-constant distribution is theoretically presented and its application to the analysis of the response to alcohol sensors is illustrated.