Peter Wide

An electronic tongue based on voltammetry

Abstract Presently, great interest is shown in the concept of an electronic nose. It consists of an array of gas sensors with different selectivity patterns, a signal collecting unit and pattern recognition software applied to a computer. Similar concepts, but for analysis in liquids have also been described, and since they are related to the tasting sense, the term `electronic tongue or `taste sensor was coined. This paper describes how various voltammetric techniques such as large and small amplitude pulse voltammetry can generate information when combined with a multivariate analysis method. A prototype of an electronic tongue was designed, based on the combination of voltammetry, using a double working electrode of gold and platinum, and principal component analysis. It is demonstrated how this electronic tongue is able to classify various samples such as fruit juices, still drinks and milk. It was also possible to follow aging processes of milk and orange juice when stored at room temperature.

A hybrid electronic tongue.

Abstract A hybrid electronic tongue is described based on a combination of potentiometry, voltammetry and conductivity. It was used for classification of six different types of fermented milk. Using ion-selective electrodes, pH, carbon dioxide and chloride ion concentrations were measured. The voltammetric electronic tongue consisted of six working electrodes of different metals (gold, iridium, palladium, platinum, rhenium and rhodium) and an Ag/AgCl reference electrode. The measurement principle is based on pulse voltammetry in which current transients are measured due to the onset of voltage pulses at decreasing potentials. The data obtained from the measurements were treated by multivariate data processing based on principal components analysis and an artificial neural net. The hybrid tongue could separate all six samples. Also, the nature of the micro-organisms in the different fermentations was reflected in the principal component analysis.

Monitoring of freshness of milk by an electronic tongue on the basis of voltammetry

We describe an electronic tongue which consists of a reference electrode, an auxiliary electrode and five wires of different metals (gold, iridium, palladium, platinum and rhodium) as working electrodes. The measurement principle is based on pulsed voltammetry, in which successive voltage pulses of gradually changing amplitudes are applied to the working electrodes connected in a standard three-electrode configuration. The five working electrodes were successively connected and corresponding current-response transients are recorded. The electronic tongue was used to follow the deterioration of the quality of milk due to microbial growth when milk is stored at room temperature. The data obtained were treated with principal component analysis and the deterioration process could clearly be followed in the diagrams. To make models for predictions, projections to latent structure and artificial neural networks were used. When they had been trained, both models could satisfactorily predict the course of bacterial growth in the milk samples.

The combination of an electronic tongue and an electronic nose

Abstract The combination of an electronic tongue and an electronic nose for classification is described. The `electronic nose consists of an array of gas sensors with different selectivity patterns, signal handling and a sensor signal pattern recognition and decision strategy. The `electronic tongue, which was developed for the taste analysis of liquids is based on pulsed voltammetry. Measurement data from the artificial smell and taste sensors are used to produce sensor-specific opinions about these two human-like sensing modalities. Using principal component analysis, it is shown that both the electronic nose and the electronic tongue alone are able to discriminate reasonably between experimental samples. When combining information from both the electronic nose and the electronic tongue, however, the classification properties are clearly improved.

The human-based multi-sensor fusion method for artificial nose and tongue sensor data

Presently, an increased interest is apparent for the development of integrated human-like smell and taste sensing capabilities, e.g. for chemical, paper pulp, food, and medicine applications. This paper will present an original sensor fusion method based on human expert opinions about smell and taste and measurement data from artificial nose and taste sensors. The electronic nose consists of an array of gas sensors with different selectivity patterns, signal handling and a sensor signal pattern recognition and decision strategy. The electronic tongue which was developed for the taste analysis of liquids is based on pulse voltammetry. Measurement data from the artificial smell and taste sensors are used to produce sensor-specific opinions about these two human-like sensing modalities. This is achieved by a team of artificial neural networks and conventional signal handling which approximates a Bayesian decision strategy for classifying the sensor information. Further, a fusion algorithm based on the maximum likelihood principle provides a combination of the smell and respectively taste opinions, into an overall integrated opinion similar to human beings. The proposed integrated smell- and taste-sensing method is then illustrated by an application of real world measurements in the food industry.

A glove equipped with finger flexion sensors as a command generator used in a fuzzy control system

We propose a method where a glove generates commands based on position measurements. The glove is equipped with sensor electrodes between which capacitances are formed. There are also airtight polyvinyl chloride tubes placed along the fingers that are connected with pressure sensors on the wrist. When the angles of the fingers change the output of the sensors will change. The combined sensor outputs form a pattern that corresponds to different finger flexions. Commands can be generated by different finger flexions. The glove is simple and it can generate sufficient signals for a fuzzy control system. This paper describes a technique to create fuzzy commands by the use of fuzzy measures of the real world, to be used in a fuzzy controller. The hand generates commands both in Boolean measures, on/off etc., as well as in fuzzy measures, i.e., closer, even closer, etc.

A dynamic safety system based on sensor fusion

Machines in industry, including industrial robots, have in many cases dramatically reduced the man-made work and improved the work environment. New machines introduce, however, new risk factors. Traditionally machines are safeguarded by means that more or less rigidly separates the machines from the personnel. This works well in many traditional areas, i.e., where industrial robots are involved. There is however a risk that the safety system limits the valuable flexibility of the robot, which can be considered as a quality that tends to become even more valuable in the progress of programming possibilities and sensor technology. This article shows an example how a safety system can be designed to achieve increased flexibility in co-operation between human and production safety strategy. The proposed safety system is totally based on sensor information that monitors the working area, calculate the safety level and improve the system dynamically, e.g., reduce the robot capability in conjunction to the system safety level. The safety system gain information from the sensors and calculates a risk level which controls the robot speed, i.e., the speed is reduced to achieve a sufficiently low risk level. The sensor data is combined with fuzzy-based sensor fusion and fuzzy rules. The safety system is based on sensor information, hence it automatically adjusts to changes in the guarded area as long as the functionality of the sensors is maintained. Finally, we present a system implementation in an industrial robot application.

Renal preservation in children with neurogenic bladder-sphincter dysfunction followed in a national program.

PURPOSEnNeurogenic bladder-sphincter dysfunction (NBSD) constitutes the major reason for morbidity in children with spina bifida. The aim of this study was to identify risk factors for renal damage in children with NBSD followed according to the Swedish national guidelines.nnnMATERIALS AND METHODSnRecords and cystometries from 6 to 16 years (median 11) follow up of 41 consecutive children born 1993-2003 with NBSD were evaluated. The children were divided into a high pressure group (baseline pressure above 30 cmH(2)O at maximal clean intermittent catheterization volume in at least two cystometries) and a low pressure group. Most children (34/41) were followed from birth.nnnRESULTSnAlthough renal scarring on DMSA-scintigraphy was found in 5/41 children, all but one had normal renal function. Two already had renal scars on entering the follow-up program at age 2.5 and 3 years. Renal scarring was more frequent in the high pressure group (P < 0.01). Most children with renal scars (4/5) had a combination of low compliant bladder and insufficient compliance with treatment and follow up.nnnCONCLUSIONnHigh baseline pressure is confirmed as a risk factor that, in combination with complex social issues, creates a demanding situation for families and professionals. A structured early follow up with treatment compliance effectively prevents renal damage.

An air-quality sensor system with fuzzy classification

sensor system for the measurement of air quality is presented and evaluated. It is based on the approach of mimicking the advantages of human olfactory sensing, using gas sensor measurements and f ...

A fuzzy approach to multi-sensor data fusion for quality profile classification

A multi-sensor system is considered where the sensors comprising it utilize the principles of human olfactory sensing and the processing of the sensor measurements is done by a fuzzy sensor fusion technique. The emphasis of the paper is on the fuzzy fusion technique used for the classification of the numerical measurements of a quality characteristic in different fuzzy quality profiles.