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The authors present the results of a study conducted using time series data from the 1993--2001 period in order to characterise the clinical behaviour of bovine paratuberculosis. The case data, confirmed by macroscopic examination, enzyme-linked immunosorbent assay (ELISA) and comparative tuberculin test, came from the herd health register, located in Tandil in the province of Buenos Aires, Argentina. The upper limit of customary variation was observed in April, with an incidence of 2.5%. In 1997, 1999, 2000 and 2001 the disease was epidemic and a peak of 5.6% occurred in March 1999. Over the long term a rise in the total annual incidence was observed, from 0.7% in 1993 to 10.2% in 2001. Knowledge about the epidemiology of paratuberculosis will help to control the disease and minimise its impact on the national economy, and will also provide new information for use in public health.

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Human-machine information transfer through tactile excitation has addressed new applications in virtual reality, robotics, telesurgery, sensory substitution and rehabilitation for the handicapped in the past few years. Power consumption is an important factor in the design of vibrotactile displays, because it affects energy needs and the size, weight, heat dissipation and cost of the associated electronics. An experimental study is presented on the power required to reach tactile thresholds in electromechanical and piezo-electric transducers. Three different waveforms are considered, with an excitatory period formed by a burst of rectangular 50% duty cycle pulses (R50), rectangular low duty cycle pulses (RLO) and sinusoidal pulses (SIN). Ten different pulse repetition periods (RPs) were considered in the range 1/550-1/25 s. The voltage and current waveforms applied to the transducers at sensation thresholds in a group of 12 healthy subjects were sampled and stored in a digital oscilloscope. The average power was determined for each subject, and differences of two orders of magnitude were measured between the electromechanical and the piezo-electric transducer power consumption. Results show that, for the electromechanical transducer, a smaller power consumption of 25 microW was determined for RP = 1/25 s and the RLO waveform. In the case of the piezo-electric transducer, power of 0.21 microW was determined for SIN excitation and RP = 1/250 s. These results show the advantages of reducing power requirements for vibrotactile displays, which can be optimised by the choice of appropriate types of transducer, excitatory waveforms and pulse repetition periods.

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Tactile spatial resolution is an important factor in the design of vibrotactile arrays. The two-point discrimination distance is used as a measure of tactile spatial resolution. An experimental study is presented showing the effect of pulse burst stimulus parameters, pulse repetition period and duty cycle on two-point vibrotactile spatial discrimination. An array of piezoceramic vibrators is used to measure two-point spatial discrimination on the index finger. In a group of 14 subjects, the average two-point discrimination distance for a pulse repetition period of 1/25s is 2.1 mm (SD = 1.0), whereas for 1/500 s it is 5.1 mm (SD = 0.9). Differences in discrimination distances are statistically significant according to the ANOVA analysis (p < 0.001). Results show that the two-point discrimination distance is better for longer pulse repetition periods. Therefore the pulse repetition period in an excitatory waveform composed of bursts of pulses is important for tactile resolution. No statistically significant differences in discrimination distances are found between bursts of pulses of 50% duty cycle and those of lower duty cycle. The latter result indicates that, by choosing low-duty cycle waveforms for vibrotactile stimulation, the power can be reduced with no loss in two-point discrimination capacity.

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This work is part of a project to develop an expert system for automated classification of the sleep/waking states in human infants; i.e. active or rapid-eye-movement sleep (REM), quiet or non-REM sleep (NREM), including its four stages, indeterminate sleep (IS) and wakefulness (WA). A model to identify these states, introducing an objective formalisation in terms of the state variables characterising the recorded patterns, is presented. The following digitally recorded physiological events are taken into account to classify the sleep/waking states: predominant background activity and the existence of sleep spindles in the electro-encephalogram; existence of rapid eye movements in the electro-oculogram; and chin muscle tone in the electromyogram. Methods to detect several of these parameters are described. An expert system based on artificial ganglionar lattices is used to classify the sleep/waking states, on an off-line minute-by-minute basis. Algorithms to detect patterns automatically and an expert system to recognise sleep/waking states are introduced, and several adjustments and tests using various real patients are carried out. Results show an overall performance of 96.4% agreement with the expert on validation data without artefacts, and 84.9% agreement on validation data with artefacts. Moreover, results show a significant improvement in the classification agreement due to the application of the expert system, and a discussion is carried out to justify the difficulties of matching the expert's criteria for the interpretation of characterising patterns.

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A reasoning method to explicate the conclusions-a posteriori- and to prospect for the next test-a priori-applied to medical expert systems based on fuzzy analog ganglionar lattices is presented. This method is founded on the sensitivity criterion of the consequent respect to the antecedents. It proves to be suited for problems of any complexity, specially when they are formulated on well-established intermediate concepts, such as syndromes, clinical finding, laboratory procedures, etc., as is usually the case in medical procedures. This type of expert system uses the structural properties of the ganglionar lattice to produce explications for its conclusions at different levels of abstraction, and to an arbitrary, but fixed, explicative degree. A measure to evaluate the consequent's achieved preciseness (certainty) is also supplied. A full example of application in the diagnosis of cardiac insufficiency with hypertensive myocardiopathy is shown, and a computational implementation of this analog procedure is described. Finally, the reasoning methods for explicating and prospecting are discussed.

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This work presents an Expert System based on fuzzy analog ganglionar lattices. Its reasoning scheme is designed analogously to the expert's mental organization and it is realized on an (analog) operator called the ganglionar lattice. It is a connectionist system that uses the medical knowledge to define its architecture. The operator evokes some similarities to higher order neural networks and performs as the knowledge base and inference engine of the expert system, in a unified manner. A main feature of this operator is that it exhibits the variables corresponding to all intermediate concepts identified by the expert; this characteristic is shown to be most valuable for assessing, explicating and prospecting in medical applications. Further, it is capable of (i) evaluating a consequent for a variety of non-approximate reasonings with multiple antecendents of different relative importance under limited uncertainty; (ii) explicating the conclusions at different levels of abstraction to suit the user; and (iii) prospecting for the best 'a priori' sequence of unevaluated antecedents, from which to choose following tests. These procedures are based on the objective criterion of the consequent's uncertainty decrease (entropy). All results are produced in numerical form and may be translated into restricted natural language. A simple example of this technology is fully developed. Finally the method's potentials are discussed for future applications.

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