Current physical biometric verification systems are hampered by a major vulnerability: spoofing. Keeping biological information, such as the face, fingerprints, and irises, concealed from others in daily life is difficult, and therefore theft and counterfeit of exposed biological information can be relatively easily accomplished by first capturing an individual’s targeted information as an image and then using the data to reproduce a model. Here, I propose a new method of physical biometric verification that uses dynamic data which are difficult to spoof. This basic concept can be applied to several types of biometric verification, such as those based on finger geometry, finger veins, irises, and the contour of the eyelid. I also propose an algorithm for this new verification method and provide experimental examples of its application.

Problem of pattern recognition is accompanying our whole life, therefore methods of automatic pattern recognition is one of the main trend in Artificial Intelligence. Multiple classifier systems (MCSs) are currently the focus of intense research. In this conceptual approach, the main effort is concentrated on combining knowledge of the set of individual classifiers. Proposed work presents a brief survey of the main issues connected with MCSs and provides comparative analysis of some classifier fusion methods.

The area of biometric, without a doubt, is one of the most dynamic areas of interest, which recently has displayed a gamut of broader links to other fields of sciences. Among those are visualization, robotics, multidimensional data analysis, artificial intelligence, learning, data fusion and data synthesis. The topic of this keynote is reviewing state-of-the-art in multi-modal data fusion, fuzzy logic and neural networks and its recent connections to advanced biometric research. Application examples are provided.

This paper presents a new method of recognizing handwritten signatures. Signature was treated as a collection of features of specific values. As features the values of x, y coordinates of signature points have been used. The method discussed in the paper is a modification of the method based on least squares contour alignment. This modification consists of dividing signatures into windows of the preset size and measuring the value of similarity between the windows according to their position in the signature. The effectiveness of the method was verified in practice. During the study, the influence of the parameters of the method on the obtained results was determined.

The paper puts forward a new method of determination of signatures’ characteristic points. The method is based on seeking points of the highest curvature using the IPAN99 algorithm. The way of IPAN99 algorithm parameters’ automatic selection for a particular signature has been fully described. Moreover, the way of determination of additional characteristic points, important for a signatures analysis, has been shown. The presented results of carried out experiments confirm that the proposed method is useful for signature recognition and verification.

This paper presents a new estimation method of fingerprint orientation field. An accurate estimation of fingerprint orientation fields is an essential step in automatic fingerprint recognition systems (AFIS). Most popular, gradient–based method is very sensitive to noise (image quality). Proposed algorithm is a modification of, more resistant to noise, mask-based method, which provides orientation limited to discrete values. This modification is based on aggregation of pixel values differentiation and was used to more precise estimation of magnitude of orientation vectors. This approach allows to obtain a continuous values of orientation field still maintaining robust to noise.

This paper presents a method for automatic lip traces recognition based on lip furrows arrangement. First, lip trace is scanned and subjected to image processing and feature extraction. Then, identification is performed by comparing lip trace characteristics with a collection of comparative lip prints characteristics stored in a database. The proposed solution gives a satisfactory level of identification accuracy. After further improvement, it can be used as part of a system performing analysis of traces recovered from crime scenes.

In this paper we present a novel approach that enables the determination and measurement of important features associated with the human body movement. This information can be used in the construction of a biometric personal identification system. Biometrics is, essentially, a pattern recognition system based on measurements of unique physiological or behavioural features as acquired from an individual. The domain of biometric techniques is currently placed within recently developed disciplines of science. Biometry or biometrics is simply defined as automatically recognizing a person using distinguishing traits and is widely used in various security systems. Biometry can be defined as a method of personal identification based on individuals" physical and behavioural features. Physiological biometrics covers data coming directly from a measurement of part of a human body, for example a fingerprint, the shape of the face, or from the retina. Behavioural biometrics analyses data obtained on the basis of an activity performed by a given person, for example speech and the handwritten signature. The system of biometrics defined above can now be expanded, and a new biometrics system can be considered. In our approach, human foot pressure on a surface is measured and the pressure data retrieved. The pressure parameters are collected without the necessity of any movements of the feet.

The Medical information systems evolve constantly. The quality of the medical information system relies on competences, qualifications, and the organization of the participating partners. Those last ones belong to heterogeneous and autonomous information systems. So, it is necessary to assure a permanent cooperation. This paper shows a coherent architectural framework that allows the development of interoperable medical information systems in measure or these systems evolve. The essential idea is to use concepts of multi-agent systems to perform the different activities of medical information system and thus, to adapt the solutions provided by the agent paradigm to solve the different problems encountered while establishing a medical information system.

The development of advanced spatial-positioning systems for medical monitoring and emergency response using RFID and Wi-Fi technologies is a current research focus of many healthcare organizations. The goal of such system is to support real-time location tracking of medical equipments and personnel in hospital settings using RTLS technology. This paper presents a spatial-temporal data analysis based on data collected at the W21C of Foothills Hospital, Calgary, Canada. The collected data, comprising real-time observations and tracking paths, has been used to perform advanced statistical pattern analysis and visualization of work-flow patterns in health care system. From this analysis, we bring forward some insights into medical resource, asset and facility utilization in a clinical care ward of a regional healthcare organization. This gained knowledge could be used as one of the inputs in improving patient care, responsiveness, and infection control practices.

In this paper an algorithm of calculating nondeterministic decision rules from the decision table was presented. The algorithm uses additional conditions imposed on rules. This is a greedy algorithm. The nondeterministic decision rules were used in the process of classification of new examples, for medical data sets. The decision tables from the UCI Machine Learning Repository were used. The achieved results allow us to state that nondeterministic decision rules can be used for improving the quality of classification.

This paper describes a method to accomplish ‘a pre-planned guided search of interesting and known knowledge and information sources for decision making in public health medicine’, i.e. a search protocol. The protocol is based around a knowledge base of known information and knowledge sources. These sources have been useful in earlier public health studies. The database of sources is maintained and updated as a consequence of each new study on which the search protocol is used. The paper outlines how the protocol has been created, built and tested. The results of using the protocol on five different public health studies are presented and analysed.

A big problem in applying DNA microarrays for classification is dimension of the dataset. Recently we proposed a gene selection method based on Partial Least Squares (PLS) for searching best genes for classification. The new idea is to use PLS not only as multiclass approach, but to construct more binary selections that use one versus rest and one versus one approaches. Ranked gene lists are highly instable in the sense, that a small change of the data set often leads to big change of the obtained ordered list. In this article, we take a look at the assessment of stability of our approaches. We compare the variability of the obtained ordered lists from proposed methods with well known Recursive Feature Elimination (RFE) method and classical t-test method. This paper focuses on effective identification of informative genes. As a result, a new strategy to find small subset of significant genes is designed. Our results on real cancer data show that our approach has very high accuracy rate for different combinations of classification methods giving in the same time very stable feature rankings.

Main role of this article is presentation, in a very short way, most important results of over two years of work board of experts from two universities, two clinical hospitals, city hall and also medical software and hardware suppliers. As a main purpose of strategy improvement of health care level in region was set. This aim will be achieved by telemedical infrastructure development, creation and implementation of procedures and instant training of staff. Strategy is focused on three main aspects. First one groups medical projects, second infrastructure project and third one is regional centre of coordination. In medical area proposed changes are mainly focused on telemedical support for emergency services, remote medical consultations and complex home monitoring of patients. Main solution for infrastructure assumes creation of integrated information system for hospitals and emergency units. I this part of the strategy selection of the proper standards for data storing and exchange. Probably one of the best choices is OpenEHR. Last part is centre of cooperation which consists of coordination centre of telemedical services, telemedical projects management unit, and training facility.

This paper describes the ant-based vehicle navigation algorithm (known from literature) and then proposes its modification. Because the performance of these two versions of the algorithm is unsatisfactory, the new, really revised algorithm is introduced. Experiments performed on real-world data show, that this new algorithm is much more efficient and gives better results than its predecessors. The proposed algorithm may be used in the rescue, where ambulances need the useful and efficient method to plan a route to the patient.

In the paper, the method of short word deletion errors correction in automatic speech recognition is described. Short word deletion errors appear to be a frequent error type in Polish speech recognition. The proposed speech recognition process consists of two stages. At the first stage the utterance is recognized by a typical speech recognizer based on forward bigram language model. At the second stage the word sequence recognized by the first stage recognizer is analyzed and such pairs of adjacent words in the recognized sequence are localized, which are likely to be separated by a short word like conjunction or preposition. The probability of short word appearance in context of found words is evaluated using centered trigrams and backward bigram language model for short words prone to deletion. The set of probabilistic language properties used to correct deletions is called here Local Bidirectional Language Model (in contrast to purely forward or backward model used typically in speech recognition). The decision of short word insertion is based on comparison of deletion error probability of the first stage recognizer and the error probability of the decision based only on centered trigrams and backward model. Despite its simplicity, the method proved to be effective in correcting deletion errors of most frequently appearing Polish prepositions. The method was tested in application to medical spoken reports recognition, where the overall short word deletion error rate was reduced by almost 45%.

The goal of the paper is to present a speech nonfluency detection method based on linear prediction coefficients obtained by using the covariance method. The application “Dabar” was created for research. It implements three different methods of LP with the ability to send coefficients computed by them into the input of Kohonen networks. Neural networks were used to classify utterances in categories of fluent and nonfluent. The first one was Kohonen network (SOM), used to reduce LP coefficients representation of each window, which were used as input data to SOM input layer, to a vector of winning neurons of SOM output layer. Radial Basis Function (RBF) networks, linear networks and Multi-Layer Perceptrons were used as classifiers. The research was based on 55 fluent samples and 54 samples with blockades on plosives (p, b, d, t, k, g). The examination was finished with the outcome of 76% classifying.

In the work algorithms commonly utilized in continuous speech recognition systems were applied to detection of speech disorders. The used algorithms were briefly described and the final method of speech disorders detection was presented. The article includes the results of the short test performed in order to check the effectiveness and accuracy of the method. The aim of the test was detection and classification of fricative phonemes prolongation one of the most common speech disorders in the Polish language. It is worth emphasizing that this method enables detection of a category of speech disturbance (e.g. fricative, nasal, vowels, etc… prolongation), but also provides the information about a specific phoneme being disturbed.

The paper presents a concept of a sensor of weightlifter’s trunk inclination angle with the use of Kalman filter algorithms to estimate the trunk inclination angle. The paper presents changes of trunk inclination angle obtained using the algorithm presented. The application of an accelerometric and gyroscopic sensor in the measuring system combined with the algorithms presented in the paper enables precise representation of angle changes during the exercise.

The article describes the concept of measurement of the mechanical strength of trabecular bone dissected from human femoral head. When the studies are performed based on the human trabecular bone, there is a risk that correlation can be not achieved due to high discrepancy in the distribution of the bone density and mechanical properties. The compressive tests and X-ray microcomputed tomography with associated density phantom were used to deliver quantitative data. There is a conclusion that the selection of the region in the femoral head has to be performed very carefully. The region where cylinder is dissected can influence the results and produce fake data, which could not be correlated in the density of bone.

There is growing evidence suggesting that the magnitude of cortisol awaking response (CAR), which is characterized by a profound increase of salivary cortisol secretion after awakening, plausibly reflects the level of a chronic stress, social stress, anxiety, etc. In this study the alternation of CAR at the start and at the end of two weeks session of self-instruction for good sleep was investigated; by which we anticipated that the self-instruction for good sleep would bring-forth a positive affection for the participants, and would result in decline of cortisol awakening response (CAR). Nevertheless, as a result unexpectedly, subjects did not change their sleep and dietary habits along with the instruction, moreover the increased CAR was observed. This result implies that the suggestion of an impractical instruction would solely be taken as a stressful task for participants, even though they know that it is effective to improve their sleep. On the contrary, if one develops an instruction with practicable indication for daily life, it is highly possible to observe a positive effect of the instruction on CAR.

Intermittent hypoxia (IH) elicits two forms of respiratory plasticity, which are initiated during and after exposure to IH, i.e. a long-term facilitation and a progressive augmentation of respiratory motor output. IH is often used as a model of sleep apnea and/or respiratory plasticity in humans and animals. Procedures of IH are also applied in sport medicine and rehabilitation of respiratory diseases. The aim of the present paper is an analysis of a metabolic response to acute intermittent hypoxia in a rat model. The animals were placed and monitored in a whole body plethysmographic chamber. The rats were exposed to five consecutive cycles consisting of 10-min hypoxic stimulus period separated by 10-min normoxic intervals, and additionally they were monitored up to 1 h after the final hypoxic exposure. The metabolism software analyzer recorded following variables (features): metabolic rate, carbon dioxide production, oxygen consumption and respiratory quotient. The obtained results demonstrated that acute IH causes metabolic effects during and after intermittent stimuli, which may be effectively recognized by an application of the k-NN classifiers.

Electron paramagnetic resonance spectroscopy at X-band (9.3 GHz) is used as the tool of optimalization of storage of thermally sterilized aminoglycoside antibiotic – streptomycin. Thermal sterilization at different conditions was performed according to the norms. Changes in free radicals system of this drug during storage after sterilization were detected. Lineshape analysis and microwave saturation of EPR spectra were done. Free radical concentrations were determined. Microwave saturation EPR analysis is proposed as useful method to determine the best conditions of storage of sterilized drugs.

The paper provides a preview of some work in progress on the computer system to support breast cancer diagnosis. Diagnosis approach is based on microscope images of the FNB (Fine Needle Biopsy) and assumes distinguishing malignant from benign cases. Studies conducted focus on two different problems, the first concern the extraction of morphometric parameters of nuclei present in cytological images and the other concentrate on breast cancer nature classification using selected features. Studies in both areas are conducted in parallel. This work is devoted to the problem of feature selection from the set of determined features in order to maximize the accuracy of classification. Morphometric features are derived directly from a digital scans of breast fine needle biopsy slides and are computed for segmented nuclei. The quality of feature space is measured with four different classification methods. In order to illustrate the effectiveness of the approach, the automatic system of malignancy classification was applied on a set of medical images with promising results.

The following research characterises the system for remote data collection of blood glucose concentration. Based on the data an algorithm was introduced in order to determine the infusion of insulin. This paper presents a glucose measurement method using the test strips, instructions for collecting the source data, as well as the process of adjusting the insulin dosage.