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PubMedDate not supplied

An inference system based on fuzzy logic.

We present the use of fuzzy set theory for the management of imprecision and uncertainty. We first introduced fuzzy set theory according to two different perspectives: the logical and the possibilistic/probabilistic point of view. In addition, several examples of fuzzy sets in different contexts have been considered. The nature of imprecision in the measurement process has been investigated at various levels in order to identify different sources of uncertainty. The fuzzy inference system presented has proved to be a good tool for treating linguistic terms in a quantitative way. An application of a fuzzy inference system in computerized electrocardiography will be described. The main purpose of the present study is to show the potential use of fuzzy logic for the treatment of imprecision and uncertainty.

Adolescent↗
PubMed2006

Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.

Ammonia↗
PubMedDate not supplied

A fuzzy logic based closed-loop control system for blood glucose level regulation in diabetics.

In this study, a closed-loop system to control the plasma glucose level in patients with diabetes mellitus type 1 is proposed. This control scheme is based on fuzzy logic control theory to maintain a normoglycaemic average of 4.5 mmol 1(-1) and the normal conditions for free plasma insulin concentration in severe initial state; in particular, when the diabetic patient is subjected to a glucose meal disturbance or fluctuations in the measured glucose level due to error in the measuring instrument. The proposed controller has demonstrated superiority over other conventional controlling therapies. While fuzzy logic controllers have shown promising results in many fields, a comparative study is presented with well-known conventional controllers such as Proportional-Integral-Derivative (PID) and continuous insulin infusion control strategies. The simulated results, for the proposed controller, are presented and discussed.

Adaptation, Physiological↗
PubMed2004

Fuzzy logic for identifying pigments studied by Raman spectroscopy.

Fuzzy logic and linguistic variables are used for the automatic interpretation of Raman spectra obtained from pigments found in cultural heritage art objects. Featured bands are extracted from a Raman spectrum of a reference pigment and the methodology for constructing the library is illustrated. An unknown spectrum is then interpreted automatically and a process for identifying the corresponding pigment is described. A reference library consisting of 32 pigments was built and the effectiveness of the algorithm was tested by the Raman spectroscopic analysis of 10 pigments that are known to have been extensively used in Byzantine hagiography. Binary mixtures of these pigments were also tested. The algorithm's level of identification was good even though extra peaks, noise, and background signals were encountered in the spectra.

Journal Article↗
PubMed2004

Determination of fuzzy logic membership functions using genetic algorithms: application to structure-odor modeling.

Fuzzy logic has been used as a tool in structure-camphoraceous odor relationships. The data base studied included 99 molecules. The rules used to discriminate between camphor and non camphor molecules lead to 77% correct discrimination. Such rules account for the shape and the size of the molecule. Their adjustment by means of genetic algorithms led to 84% correct discrimination between camphor and non-camphor molecules. [figure: see text]. Membership function for the chosen variables.

Algorithms↗
PubMed2006

Fuzzy logic control of bioreactor for enhanced biosynthesis of alkaline protease by an alkalophilic strain of Bacillus subtilis.

Present studies describe the optimization of some cultural parameters such as medium pH, incubation temperature, and agitation rate for the biosynthesis of alkaline protease by Bacillus subtilis IH-72 in a bioreactor using fuzzy logic control. The process of fermentation was carried out in a 7.5-L bioreactor (New Brunswick Scientific, USA) with a working volume of 5 L. All of the parameters were automatically controlled with the help of attached software. The optimum pH, temperature, and agitation for the production of alkaline protease by B. subtilis IH-72 were found to be 9.0, 35 degrees C, and 175 rpm, respectively. The performance of the fuzzy logic of the bioreactor was found to be encouraging for enhanced production of the enzymes. The maximum production of alkaline protease during the present study was found to be 9.6 U mL-1.

Bacillus subtilis↗
PubMed2006

A new approach to diabetic control: fuzzy logic and insulin pump technology.

Diabetes is a major health problem. Since the utilisation of insulin in the 1920s there have been myriad problems in developing suitable technologies to formulate and administer correct dosages to temper this metabolic disease. From multiple daily injections, nasal inhalations and enzymatic supplementation these artificial shortcuts still do not have the ability to fully replicate a 'normoglycaemic' state of being. In this paper, we sought to explore the use of insulin pumps and the application of fuzzy logic technology to act as an 'artificial pancreas' in diabetic patients. This paper builds on our previous work [Grant P, Naesh, O. Fuzzy logic and decision-making in anaesthetics. J Roy Soc Med 2005;98(1):7-9 [review]].

Biotechnology↗
PubMed1995

A fuzzy logic diagnosis system for classification of pharyngeal dysphagia.

Identification and classification of the dysphagic patient at risk of aspiration is important from a clinical point of view. Recently, we have developed techniques to quantify various biomechanical parameters that characterize the dysphagic patient, and have developed an expert system to classify patients based on these measurements. The purpose of the present investigation was to develop a fuzzy logic diagnosis system for classification of the patient with pharyngeal dysphagia into four categories of risk for aspiration. Non-invasive acceleration and swallow pressure measurements were obtained and five parameters were extracted from these measurements. A set of membership functions were defined for each parameter. The measured parameter values were fuzzified and fed to a rule base which provided a set of output membership values corresponding to each of the categories. The set of output values were defuzzified to obtain a continuous measure of classification. The fuzzy system was evaluated using the data obtained from 22 subjects. There was a complete agreement between the fuzzy system classification and the clinician's classification in 18 of the 22 patients. The fuzzy system overestimated the risk by half a category in two patients and underestimated by half a category in two patients. The fuzzy logic diagnosis system, together with the biomechanical measures, provides a tool for continued patient assessment on a daily basis to identify the patient who needs further videofluorography examination.

Biomechanical Phenomena↗
PubMedDate not supplied

Tuning of myoelectric prostheses using fuzzy logic.

This contribution concerns the use of a supervisory expert system based on fuzzy logic for the parameter adjusting of myoelectric prostheses. The prosthesis system is an artificial arm produced by INAIL in Vigorso (Bologna, Italy), which is equipped with an on-board actuation system. The expert system guides patients through an interactive session whose aim is to test the prosthesis functionality and, when necessary, to self-adjust the parameters.

Artificial Limbs↗
PubMed1997

Control model of human stance using fuzzy logic.

A control model of human stance is proposed based on knowledge from behavioral experiments and physiological systems. The proposed model is based on the control of global variables specific to body orientation and alignment, rather than on the control of the body's center of mass within the base of support. Furthermore, the proposed control model is not based on purely inverted pendulum body mechanics where only motion at one joint is controlled, as for instance the ankle. In the proposed model, the degrees of freedom are controlled by using reciprocal and synergistic muscle actions at multiple joints. The control model is based on three sets of different global variables which act in parallel: (1) limb length and its derivative, (2) limb orientation and its derivative, and (3) trunk attitude and its derivative. An important feature of the control model is the use of fuzzy logic, which enables us to model experimental findings and physiological knowledge in a meaningful and explicit way using fuzzy if-then rules. In the control model, 36 fuzzy if-then rules are implemented and applied using a four-linked segment model consisting of a trunk, thigh, shank and foot. Uni- and biarticular limb muscles and trunk muscles are represented as torque actuators at each individual joint. In the model, three sets of global variables act in parallel and make corrective and coordinated responses to internal, self-induced perturbations. The data show that the use of global variables and fuzzy logic successfully enables us to model human standing with sway about a point of equilibrium. Small changes in, for example, total body sway are comparable to those seen during natural sway in human stance. The selected controllers--limb length, limb orientation and trunk attitude--seem to be appropriate for human stance control.

Fuzzy Logic↗
PubMed1998

Application of fuzzy logic techniques for the qualitative interpretation of preferences in a collective questionnaire for users of wheelchairs.

Active participation of users in the evaluation of technical aids is essential, since they are part of the interface with the system and constitute a fundamental source of design criteria. In this study, 88 active users of wheelchairs were interviewed by means of a written questionnaire about their opinion concerning the adaptation of his/her wheelchair to the office workplace. A conceptual framework was introduced linking objective measurements of the user-wheelchair interface to the subjective preferences expressed by the user. Discriminant analysis was used in order to select and quantify the importance of the most significant factors influencing the user's opinions. Fuzzy logic was introduced for the qualitative interpretation of the relationship between those significant factors, based on an inductive algorithm for generating fuzzy rules. Fuzzy logic enables a person to model the uncertainty within the subjective formulation of knowledge or opinions. From the results, a mismatch between actual performance of conventional wheelchairs and requirements of office work became evident. The proposed methods make it possible to determine reliable rules explaining subjective preferences; thus, they provide a flexible means of interpreting user questionnaires and obtaining new design criteria.

Equipment Design↗
PubMed1998

Segmentation of intrathoracic airway trees: a fuzzy logic approach.

Three-dimensional (3-D) analysis of airway trees extracted from computed tomography (CT) image data can provide objective information about lung structure and function. However, manual analysis of 3-D lung CT images is tedious, time consuming and, thus, impractical for routine clinical care. We have previously reported an automated rule-based method for extraction of airway trees from 3-D CT images using a priori knowledge about airway-tree anatomy. Although the method's sensitivity was quite good, its specificity suffered from a large number of falsely detected airways. We present a new approach to airway-tree detection based on fuzzy logic that increases the method's specificity without compromising its sensitivity. The method was validated in 32 CT image slices randomly selected from five volumetric canine electron-beam CT data sets. The fuzzy-logic method significantly outperformed the previously reported rule-based method (p < 0.002).

Animals↗
PubMed1996

Computed tomography image enhancement using the concept of fuzzy logic.

Diagnostic features in computed tomography (CT) images vary widely due to the vague nature (fuzziness) of functional characteristics in organ pathologies. Classical image enhancement techniques cannot adapt to the characteristics of this nature. A method based on fuzzy logic is given in this paper. In this method the image of interest is transformed into a fuzzy plane using fuzzifiers which can be changed to select a crossover point. A contrast intensification operator (INT) is then applied. The operator increases the grade of membership of those values which lie above the crossover point and decreases the same for those pixels which lie below it, thereby increasing the contrast and reducing the fuzziness. Quantitative measures of fuzziness which reflect a sort of quantitative measure of image quality have also been studied. Using digitized CT images it has been shown that at early stages of a disease, when the contrast of the pathological tissues is very low, the visibility of the disease could be considerably improved using this technique.

Fuzzy Logic↗
PubMed1990

Fuzzy Logic for medical expert systems.

The use of linguistic approximation enables knowledge to be represented in a more meaningful way and this is especially important in medical domain as it involves a lot of subjective decision making; Fuzzy Logic, introduced by Zadeh, has the ability to represent this imprecise expression. In this paper, an alternative approach of Fuzzy Logic in handling the approximate reasoning in expert systems will be described. The approach does not use the General Modus Ponen on the compositional rule of inference, but instead it uses a collection of rules to specify the properties of the inference (in making decision). An example of medical domain is described as its application.

Diagnosis, Computer-Assisted↗
PubMed2002

Application of a sediment quality triad and different statistical approaches (Hasse diagrams and fuzzy logic) for the comparative evaluation of small streams.

In order to evaluate the ecotoxicological contamination of 12 aquatic sites in streams within the catchment area of the Neckar River, a sediment quality triad (SQT) approach was applied. In contrast to Chapman's original triad approach, not only sediments, but also surface waters were examined. In brief, to obtain a comprehensive insight into the potential ecotoxicological hazard, both acute toxicity and more specific effects such as mutagenic, genotoxic, teratogenic, dioxin- and estrogen-like responses were recorded. Different statistical methods (ranking, cluster analyses, Hasse diagram techniques, and fuzzy logic) for the evaluation and presentation of the SQT data were compared with respect to the needs of environmental decision-making. Results document advantages and disadvantages of the methods applied for the evaluation and classification of data within the complex data matrixes. The ranking procedure presented as well as the Hasse diagram technique seem to be suitable tools to elucidate the pattern of the ecotoxicological load. However, these classification methods require expert knowledge to interpret the ranking results with respect to decision-making in environmental sciences and policy. In contrast, fuzzy logic allows both to develop site-specific expert systems in order to assess the ecotoxicological burden and to give insight into the pattern of the contamination.

Animals↗
PubMed2005

Modeling uncertainty in clinical diagnosis using fuzzy logic.

This paper describes a fuzzy approach to computer-aided medical diagnosis in a clinical context. It introduces a formal view of diagnosis in clinical settings and shows the relevance and possible uses of fuzzy cognitive maps. A constraint satisfaction method is introduced that uses the temporal uncertainty in symptom durations that may occur with particular diseases. The method results in an estimate of the stage of the disease if the temporal constraints of the disease in relation to the occurrence of the symptoms are satisfied. A lightweight fuzzy process is described and evaluated in the context of diagnosis of two confusable diseases. The process is based on the idea of an incremental simple additive model for fuzzy sets supporting and negating particular diseases. These are combined to produce an index of support for a particular disease. The process is developed to allow fuzzy symptom information on the intensity and duration of symptoms. Results are presented showing the effectiveness of the method for supporting differential diagnosis.

Algorithms↗
PubMed2005

A heuristic fuzzy logic approach to EMG pattern recognition for multifunctional prosthesis control.

This paper presents a heuristic fuzzy logic approach to multiple electromyogram (EMG) pattern recognition for multifunctional prosthesis control. Basic signal statistics (mean and standard deviation) are used for membership function construction, and fuzzy c-means (FCMs) data clustering is used to automate the construction of a simple amplitude-driven inference rule base. The result is a system that is transparent to, and easily "tweaked" by, the prosthetist/clinician. Other algorithms in current literature assume a longer period of unperceivable delay, while the system we present has an update rate of 45.7 ms with little postprocessing time, making it suitable for real-time application. Five subjects were investigated (three with intact limbs, one with a unilateral transradial amputation, and one with a unilateral transradial limb-deficiency from birth). Four subjects were used for system offline analysis, and the remaining intact-limbed subject was used for system real-time analysis. We discriminated between four EMG patterns for subjects with intact limbs, and between three patterns for limb-deficient subjects. Overall classification rates ranged from 94% to 99%. The fuzzy algorithm also demonstrated success in real-time classification, both during steady state motions and motion state transitioning. This functionality allows for seamless control of multiple degrees-of-freedom in a multifunctional prosthesis.

Adult↗
PubMed1997

Computer-assisted interpretation of electromyograms of corpora cavernosa using fuzzy logic.

An electromyogram of the corpora cavernosa (CC-EMG) imparts information on the autonomic cavernous innervation and/or the cavernous smooth muscles. The CC-EMG is interpreted mainly by evaluation of signal patterns of higher activity. The time required for interpretation is reduced by the implementation of a computer-assisted diagnosis program with a Microsoft Windows user interface. The program offers four levels of diagnosis: on the first level, recordings can be edited; on the second and third levels, signal patterns can be searched or evaluated; and on the last level the final diagnosis is provided. The computer-assisted interpretation is based on digital measurement data. These data have been obtained through a 170.6-Hz sampling frequency and a quantization of 10 V/12 Bit of the amplified signal. The first task of this diagnosis program is to discover and extract signal patterns of higher activity from data stored on the hard disk of a personal computer (PC). For a mathematic description of these patterns the following features were defined: relative time position, relative reproducibility, part of normal phases, and part of whip phases. Syntactic pattern recognition was introduced to identify the characteristic signal forms. An evaluation of the patterns could be derived from these features using fuzzy logic. For a summary of the evaluated patterns the variable global normality was established. The global normality forms an important evaluation basis along with the global synchronism, which represents an investigator's first impression of a recording. The final diagnosis is completed using fuzzy logic. The program was tested by comparison of expert and computer diagnoses. A total of 30 records were independently evaluated by an expert team and the computer program. With reference to the four classified levels of diagnosis a correspondence of 70% could be found. Furthermore, the rate in each of the classified levels was higher than 50%. The discrimination between normal and abnormal evaluation was 80% for clinical routine. Our results show that a computer-assisted interpretation of the CC-EMG can be achieved using mathematically based software. Within the last 7 months this computer-assisted CC-EMG program proved to be of great help in routine diagnosis. Furthermore, it demonstrated results comparable with a blinded-expert interpretation. This approach should bring about dramatic improvements in the diagnosis of erectile dysfunction.

Electromyography↗