A fuzzy control system which is a typical system utilizing fuzzy model is mainly using the Max-Min CRI (Compositional Rule of Inference) method by Zadeh and Mamdani for fuzzy inference. But the Max-Min CRI method suffers from drawbacks including: error-prone weighting strategy, inefficient compositional rule of inference, and subjective formulation of membership functions. Because of these problems in the Max-Min CRI method, the inference often results in significant error regions specifying the difference between the desired outputs and the inferred outputs. To overcome such problems, we propose here a new fuzzy inference system for artificial intelligence control.

Public Health Informatics is a growing academic discipline increasingly contingent on the propagation, manipulation and synthesis of information from a variety of resources. PHI is the intersection of information technology and health care. It deals with the resources, devices, and methods required to optimize the acquisition, storage, retrieval, and use of information in public health. Public health practitioners now do much of their surveillance, support, reporting, data analysis, and data collection via the internet or on computer systems. This article reports and reviews on the issues involved in PHI specially focus on priorities, challenges, and opportunities with their practical applications.

Our experience tells us the power of music on human body and mind. Moreover a series of psycho-physiological studies has revealed the positive effects of music on human autonomous nervous system such as alleviating the symptom of the hypertension. However little has been known about the effects of music on human endocrine system, which plays the dominant role for forming our life. In this study, the effect of music on the secretion of the salivary cortisol, a major glucocorticoid hormone, was investigated in a laboratory experiment. In a stream of stress psycho-physiological study, cortisol is considered as a feasible stress biomarker. In the experiment ten healthy male students were exposed to music, noise, and silence condition followed by a simple but stressful calculation task. As a result, the significant difference in the cortisol responses among the condition was observed; the salivary cortisol was decreased after the music treatment. This result plausibly demonstrated the effects of music on human hormonal secretion and might imply the power of music.

In this paper a novel adaptive filtering scheme for impulsive noise removal in colour images is presented. The noise detection algorithm is based on the concept of aggregated distances assigned to the pixels belonging to the filtering window. The value of the difference between the accumulated distance assigned to the central sample and to the pixel with the lowest rank, serves as an indicator of the presence of impulses injected into the image by the noise process. The output of the proposed filter is a weighted mean of the central pixel of the filtering window and the vector median of its samples. The obtained results show that the proposed filter outperforms existing impulse noise removal techniques for low noise contamination and can be used in various applications in which the detail preserving reduction of impulses play an important role.

This paper includes off line Signature Verification (SV) process with test results using the proposed algorithm Particle Swarm Optimization-Neural Network (PSO-NN) together with statistical analysis, Chi-square test. The verification process is performed in four steps. Signature images are scanned (data acquisition) and image processing is applied to make images suitable for extracting features (pre-processing). Each pre-processed image is then used to extract relevant geometric parameters (feature extraction) that can distinguish signatures of different volunteers. Finally, the proposed verification algorithm is tested on the database that includes 1350 skilled and genuine signatures taken from 25 volunteers. The Chi-square test is applied to see how the signature data fits with probability test function.

Knowledge is a key factor to the personal success. The certifications are the instant tools that are commonly available to assess the personal success. In an e-Learning environment, where the learning projects are delivered with the aim to provide a professional or an academic certification, it is integral that the Learning Management Systems provide security features that will ensure the credibility of the online real-time assessments and the certification. In a conventional examination environment, there will be invigilators to overlook the examinees, on the contrary, in an on-line examination environment; it is vital that an invigilation mechanism is implemented to ensure the integrity of the examination. In this article we present a face based access control system for online e-Learning systems.

The paper presents experimental results on offline signature identification and verification. At the first stage of the presented system, the binary image of the signature undergoes skeletonization process using KMM algorithm to have a thinned, one pixel-wide line, to which a further reduction is applied. For each thinned signature image a fixed number of points comprising the skeleton line are selected. The recognition process is based on comparing the reference signatures with the questioned samples using distance measure computed by means of Shape Context algorithm. The experiments were carried out using a database containing signatures of 20 individuals. For the verification process random forgeries were used to asses the system error. The main advantage of the presented approach lies in utilizing only one reference signature for both identification and verification tasks, whereas the achieved results are comparable with respect to the systems that use several training samples per subject.

This paper proposes a biometric system for authentication that uses the retina blood vessel pattern. The retina biometric analyzes the layer of blood vessels located at the back of the eye. The blood vessels at the back of the eye have a unique pattern, from eye to eye and person to person. The retina, a layer of blood vessels located at the back of the eye, forms an identity card for the individual under investigation. In particular retinal recognition creates an ?eye signature? from its vascular configuration and its artificial duplication is thought to be virtually impossible.

This study presents a new method for finding a reference point in fingerprint images. The proposed method is based on the IPAN99 algorithm, which detects high curvature points on a contour of a graphical object. This algorithm was adjusted in the study to detect high curvature points on friction ridges. It allows locating a reference point on a fingerprint image. Since the IPAN99 algorithm requires that the thickness of an analysed contour should be of one pixel, each fingerprint image was adequately prepared before submitting to the analysis with the IPAN99 algorithm. Evaluation of the efficiency of the method consisted in comparing the distances between coordinates of reference points determined with the use of the proposed method and indicated by an expert. The developed method was compared with other algorithms used for determining a reference point.

This study presents advantages of the most important methods of minutiae-based matching algorithm in fingerprint recognition systems. Minutia matching is the most popular approach to fingerprint identification and verification. Fingerprint matching usually consist of two procedures: minutia extraction and minutia matching. The performance mostly depends on the accuracy of the minutia extraction procedure. Minutiae matching designate the time complexity of applied solution.

This study examines the effectiveness of normalized Levenshtein metrics in the process of recognition of handwritten signatures. Three methods of normalization of the Levenshtein metric were taken into consideration. In addition, it was determined, which signature features are most important during their comparisons with the use of the aforementioned metric. The following signature features were examined: coordinates of signature points, pen pressure in successive points, and different types of pen speed. The influence of individual parameters of the Levenshtein algorithm on the obtained results was also determined, and the best method of normalization was selected.

The important and actual problem of health protection systems is to ensure suitable safety during taking care of patient. This can be done by innovative medical systems, which increase satisfaction of patients. That issue cause realization of more and more complex projects in medical area. The problem is that specification for medical projects is not always well defined and it can caused overhead cost and time of realization. Presented in this paper innovated method helps in prevention of situation, where medical project can not be finished because of undefined cost and time framework.

The scenarios of cooperation between personal healthcare systems are discussed in this paper. Current telemedical solutions for home care provide the patient with a seamless diagnosis based on selected vital parameters. The application of two or more specialized systems monitoring the same subject rises the question of possible interference and cooperation. The cooperation between home care and wearable systems is of particular interest, because of their complementary features. Considerations of various cooperation scenarios led to the specification of three cooperation levels with regard to the required software integration. The paper presents also the design of a cooperation protocol for two prototype surveillance systems, enabling the use of communication resources of the stationary system to carry the messages of the wearable system over the wired transmission channel.

The paper introduces the need of improving skills level of students using Internet network. The solution has been discussed on an example with remarks for the medical diagnostic devices. The laboratory, which is not large enough, for performing all needed training courses, can be provided the trainee after their main work hours. The elaborated solution is supported by various training interfaces, provided by standard Learning Management System (LMS) and the applications controlling machine called Multimedia Applications Management Shell (MAMS). The example platforms were supported by networking Debian Linux services and an open-source technology that is used freely, by many developers.

This work presents the principles of image recognition, where quality-based methods are applied. The neural networks and additional software have been proposed. This goal was achieved by using non-parametric recognition algorithms. In this paper the two-state hybrid classification method has been proposed, where artificial intelligence algorithm is included. In recognition process, the learning method, selection and optimization of diagnostic parameters have been introduced. The integrated part of the classifier structure is voting mechanism, which indicates incorrect states of the system ? for example the unrecognized images. Effectiveness of the system has been shown by means of examples, where ambiguous data have been incorporated ? it is very often a practice of medical diagnostics.

Injuries are a major cause of death around the globe. According to statistics, around 5 million people die each year world wide remaining another few millions disabled due to injuries. The world health organizations reveals that more than 90% of the injury related deaths are from low and middle income countries. But the worrying factor is that the most of the injury related deaths in these countries could have been prevented with a concerted effort. Most of the developed countries use injury surveillance systems to monitor injury cases and take preventive measures. However, low and middle income countries can not afford for such systems because of the lack of funds and basic infrastructure, like Internet. This paper proposes an effective injury surveillance system for those countries which can be functioned with minimum resources and minimum cost

Two contrasting approaches toward an epidemic study were illustrated as a pilot study; the regression analysis which is rather conventional methodology used in the past/present epidemic studies, and the other is the classifier analysis which is in the soft computing toolbox. The dataset we used for this study is obtained from a part of a cohort study which principally focused on a fatigue syndrome of the elementary and junior high school educates. In the classifier analysis we employed a major supervised machine-learning algorithm, K-Nearest Neighbour (K-NN), coupled with Principal Component Analysis (PCA). As a result, the performance that was found by cross validation method in the classifier analysis provides better results than that of the regression analysis. Finally we discussed the availability of both analyses with referring the technical and conceptual limitation of both approaches.

In the paper a method of optimal selection of utterances used as command entry-words for voice controlled application is presented. Voice controlled programs seem to be particularly useful in the area of medical informatics, where a physician interacts with a program by voice while operating the medical device or being involved in examinations requiring manual activities. The proposed method selects command words from sets of proposals defined for each command so as to minimize the overall probability of incorrect command recognition. First the entry-word dissimilarity matrix is calculated. The word dissimilarities are evaluated using HMM models consisting of appropriately trained acoustic models of the phonemes constituting words. The trained HMM is used as the sample utterance generator for the word. The artificially created utterance samples are then recognized by speech recognizers created for pairs of words. The estimation of correct recognition probability is used as the word dissimilarity measure. The word dissimilarities are then used to determine the average assessment of words selections that can be used as commands. Selection is created by choosing single word from sets of candidates defined for each command. Finally, suboptimal selection is found by using genetic algorithm. Experiments carried out prove that suboptimal selection of command entry-words can observably increase the accuracy of spoken commands recognition in many cases.

The article presents two methods of determination of cepstral parameters commonly applied in digital signal processing, in particular in speech recognition systems. The solutions presented are part of a project aimed at developing applications allowing to control the Windows operating system with voice and the use of MSAA (Microsoft Active Accessibility). The analysed voice signal has been visually presented at each of the crucial stages of developing cepstral coefficients.

Pancreatic cancer is the second most common malignancy of the gastrointestinal tract. The only potentially curative treatment is complete surgical resection but it can be performed only in patients without metastatic disease and entire resection with negative surgically and microscopically margins (R0 resection). Complete resection of the tumour with vessels? involvement is still controversial. However, many authors proved that venous as well as arterial resection and reconstruction did not influence on final outcome. Proper preoperative staging helps in relevant treatment (surgery, radiochemotherapy or combination of these methods). The most common diagnostic step is MDCT with CTA which improves high sensitivity and specificity. The purpose of the study was to assess vessels? infiltration by pancreatic carcinoma on the basis of CTA and surgery. CTA showed 88,9% sensitivity in diagnosing vessel?s involvement, however in some cases surgery is the method of choice in assessing tumours as resectable or unresectable.

This paper describes the in-hospital outcome of urgent percutaneous coronary interventions (PCI) with delayed PCI in patients suffering from non-ST-segment elevation acute coronary syndromes (NSTE-ACS). The time when the PCI should be performed is still under debate. Results from 620 patients hospitalized in Silesian Centre of Heart Diseases in Zabrze in years 2002- 2005 were included in this study for analysis. Patients were divided into two groups: group I ? patients with urgent PCI and group II ? patients with delayed PCI. The frequency of Thrombolysis In Myocardial Infarction grade 3 flow (TIMI 3) before PCI was significantly higher achieved in the second group (36.67% vs. 50.78%, p=0.05). Patients from group II had significantly more often TIMI 3 flow after PCI (82.72% vs. 92.55%, p=0.00036). The angiographic success evaluated as TIMI 3 flow after PCI occurred significantly more frequent in patients with delayed PCI than in patients with urgent PCI.

The influence of TSH on bones is still vastly unknown and the information that is known is considered controversial. This important relationship has not been studied in detail. The aim of our research was to assess the correlation between TSH, thyroid hormone and bone mineral density in children measured by DXA scanning. Our study group included 36 children (16 girls and 20 boys) mean age 12.9 ? 3.3 years. Basic anthropometrical measurements were performed (height, weight, body mass index- BMI), in all subjects. Blood was collected and measured for TSH and FT4. Bone mineral density of lumbar spine (L2-L4 BMD) and total body (Total Body BMD) were measured by DXA and expressed as bone mineral content (BMC [g]) and bone mineral density (BMD [g/cm2]). BMD Z-Score was also calculated. Correlation between the parameters obtained by DXA and anthropometrical data, TSH and thyroid hormone concentration were calculated. A statistically significant positive correlation was observed between height, weight and BMI and BMD which was calculated. Weight and BMI also had a statically significant correlation with Z-Score and total bone mineral content (BMC ? expressed in grams). There was a statistically significant positive correlation between TSH level and Z-Score for both L2-L4 lumbar spine and for total body. TSH did not correlate significantly with BMD [g/cm2] and BMC [g]. FT4 was negatively and significantly correlated with Z-Score for both L2-L4 lumbar spine and for total body. There was also no significant correlation between FT4 and BMD [g/cm2] and BMC [g]. Conclusion: 1. Thyroid stimulating-hormone (TSH) appears to be associated with maintenance of bone mineral density in children. 2. BMD Z-Score especially from L2-L4 lumbar spine assessed by DXA scanning is correlated best with hormonal and biochemical factors potentially influencing bone mineralization in children.

Matrix metalloproteinases (MMPs) are implicated in the pathogenesis of motor neuron degeneration in amyotrophic lateral sclerosis (ALS) and might be potential markers of diagnosis, prognosis and monitoring treatment effects. The aim of the present study was evaluation of the MMPs significance in cerebrospinal fluid (CSF MMPs) of patients with ALS in relation to severity of the disease. Metalloproteinases MT-MMP-1, MMP-2, MMP-9 and additionally age of subjects and disease duration were analyzed. The results demonstrate that the error of differentiation between healthy subjects and ALS patients (for MMP-2 feature) as well as between mild and severe ALS states (for CSF MMPs set) equalled to 0.033. In conclusion, the pattern recognition approach may be useful for differentation of ALS progressing on the basis of CSF MMPs features.

The reconstruction of the osseous structures in the pelvic region after bone tumour resection is highly complex and challenging. Up to now the reconstruction of the pelvis defects by autologous or allogenous grafts (for instance the fibula transplants) are highly unsatisfied because of large shape differences. Therefore there is a huge demand for patient-specific and anatomically shaped implants. Our pelvis reconstruction planning approach is based on the statistical shape model. For generation of the statistical pelvis shape model a large data pool of CT datasets has been collected. The following CT data segmentation and surface processing methods delivered the required pelvis geometries. Via Procrustes analysis of the collected pelvis surfaces the parameterized pelvis shape mean model has been calculated and the principal component analysis (PCA) [3] applied for estimating the anatomically optimal graft or implant geometry. We will demonstrate on the clinical pelvis reconstruction case that the using of statistical shape models in the oncologic surgery planning is robust and very promising method.

In modern obstetrics the cardiotocography is a routine method of fetal condition assessment based mainly on analysis of the fetal heart rate signals. The correct interpretation of recorded traces from a bedside monitor is very difficult even for experienced clinicians. Therefore, computerized fetal monitoring systems are used to yield the quantitative description of the signal. However, the effective techniques enabling automated conclusion generation based on cardiotocograms are still being searched. The paper presents an attempt to diagnose the fetal state basing on seventeen features describing the cardiotocographic records. The proposed method applies the unsupervised classification of signals. During our research we tried to classify the fetal state using the fuzzy c-means (FCM) clustering. We also tested how the efficiency of classification could be influenced by application of principal component analysis (PCA) algorithm. The obtained results showed that unsupervised classification cannot be considered as a support to fetal state assessment.

Article presents proposal of unified workflow for creation models of human head for usage in deformational method of forensic face reconstruction. Preparation of each model is made in two stages First one is creation of traditional dowel-clay reconstruction, second is in short triangle mesh preparation as a result of digitization. Article should be start point for discussion how obtain best results not only at computer science level but also anthropological. As a long time result we want to create database of standard reconstruction models with main races and genders at least.

The development of advanced spatial-positioning and monitoring systems for medical monitoring and emergency response using RFID & Wi-Fi technologies is a large-scale research project being conducted at the ward W21C of Foothills Hospital, Calgary, Canada by University of Calgary. The scope of this project is to support real-time location tracking of medical equipments and personnel in hospital settings. In this context, we developed an innovative, interactive, decision-support medical system for tracking of personnel and high value medical equipments. The goal behind development of such a system is to provide a convenient, easy to use interface using existing technologies that allows to visualize and analyse clinical pathways and health care provider?s workflow pattern as well as to perform time motion studies and more advanced statistical pattern analysis. While achieving this goal, we aim to also fill the existing void of documentation and present to scientific community functional issues encountered along with their importance in success.

Learning is a process involved in multiple timescales. As per biology, changes which last from milliseconds to seconds and hours to days are the main mediators for the formation of short-term and long-term memory. It is obvious that, memory formation is neither static nor it is restricted into a one phase of life. Every step we keep in our life, even it succeed or fail or no matter what happen, we learn from them and acquire invaluable knowledge on that, which makes us easy manipulation on similar events in future. Thus continuous learning in a dynamic environment is a necessary qualification for the researches which are interested in studying phenomena, such as addiction, stress, noise, etc on such a dynamic learning environments. This research proposes a new approach of modelling our nervous system with the intention of implementing learning on dynamic environment.

In some applications it is important to detect the QRS complex in the ECG waveform with possibly low time delay. Traditional software detectors of the QRS complex implement algorithms usually based on cascades of digital filters that introduce delays up to parts of a second. On the other hand, hardware QRS detectors fulfil the low delay requirements, but have worse adaptive features for the changing ECG shape. In this paper a new approach to QRS detection is presented. The proposed detector is based on a Field Programmable Analog Array (FPAA). This solution makes it possible to modify the parameters of particular blocks of the detector or even the whole structure without any changes in hardware, while the processing path is fully analog and does not introduce an additional delay. The most interesting feature of the FPAA is the dynamic reconfigurability. The parameters can be changed during runtime without any reset of the circuit or any other disturbances of the system functionality. The prototype QRS detector was built using the AN221E04 circuit from the Anadigm company.

Cardiotocography is a biophysical method of fetal monitoring during pregnancy and labour. It is mainly based on recording and analysis of fetal heart activity. The computerized fetal monitoring systems provide the quantitative description of the recorded signals but the effective methods supporting the conclusion generation are still needed. The evaluation of the signal can be made using criteria recommended by FIGO. Nevertheless, the quantitative description of the traces is inconsistent with qualitative nature of the obstetric knowledge. Therefore, we applied the fuzzy system based on Takagi-Sugeno-Kang model to evaluate and classify signals. FIGO guidelines were used for developing a set of fuzzy conditional rules defining the system performance. The proposed system was evaluated using data collected with computerized fetal surveillance system ? MONAKO. The classification results confirm the improvement of the fetal state evaluation quality while using the proposed fuzzy system support.

In this paper a new method of maternal electrocardiogram suppression for fetal component extraction from one-channel maternal abdominal bioelectric signals is proposed. The method performs maternal ECG estimation by application of state-space averaging. The estimated signal is subtracted from the original one and this way suppressed. The method parameters allow us to balance between the precision of maternal ECG suppression and the necessity not to attenuate the fetal QRS complexes. A small database of the maternal abdominal bioelectric signals is used to investigate the developed system for fetal heart rate determination. The final assessment is based on the detection performance index. It is shown that by proper choice of the parameters we can tune the system so that it is more effective than the classical approach based on template subtraction.

The paper presents some aspects of telemedical fetal monitoring where the biomedical signals are acquired remotely at patient?s home and wirelessly transmitted to the central computer through the GSM network and Internet. Signals are acquired during the monitoring sessions, and along with analysis results, they create uniform data structure describing the medical history of patient since the first monitoring to the labour. The proposed structure of database was based on the currently used in centralized monitoring systems, and extended by information essential for remote monitoring purposes. Internet-based telemedical systems allow for remote access to collected data, however, it is necessary to secure the database against unauthorized access to patient?s personal data and medical history. The proposed structure of database records allows for easy searching and viewing of patient data forms and monitoring traces. These features cause that the database constitutes valuable research material, which enables to relate parameters of particular monitoring records, acquired during pregnancy, to the real fetal outcome.

In this paper the problem of unsatisfactory diagnostic efficiency of pseudorandom testing (PRT) technique used to detect faults of digital circuits in testing medical systems of critical importance is presented. The simulations have revealed a weakness of commonly used PRT technique that generally does not assure that all stuck at faults are detected. Thus, it is suggested that PRT technique should be supplemented with additional deterministic testing sequences to enhance fault detection. To design built-in selftesting (BIST) structures a genetic algorithm and digital system stochastic model were used. By employing the stochastic model it is possible to reduce considerably the computer simulation time required for BIST architecture design. In particular, an effect of proportional and ranking selections on the convergence of genetic algorithm in searching for a globally optimal solution, while maintaining the diversity of the population of individuals and limiting its premature stagnation.

Reduction of this type may help to solve one of the greatest problems in pattern recognition, i.e. the compromise between the time of making a decision and its correctness. In the analysis of biomedical data, classification time is less important than certainty that classification is correct, i.e. that reliability of classification is accepted by the algorithm?s operator. It is usually possible to reduce the number of wrong decisions, using a more complex recognition algorithm and, as a consequence, increasing classification time. However, with a large quantity of data, this time may be considerably reduced by condensation of a set. Condensation of a set presented in this article is incremental, i.e. formation of the condensed reference set begins from a set containing one element. In each step, the size of the set is increased with one object. This algorithm consists in dividing the feature space with hyperplanes determined with pairs of the mutually furthest points. The hyperplanes are orthogonal to segments linking pairs of the mutually furthest points and they go through their centre.

Color is an inseparable element of our lives and is a part of everything we perceive. Colour has a strong impact on our decision making process. Therefore there is a direct connection between the colour and psychological functions. Kansei is a Japanese concept, which abstracts the subjective internal process in the brain, which is activated by external stimuli. Furthermore, Kansei is a function of the brain which integrates sensibility, sense, sensitivity, aesthetics, emotion, affection and intuition. Therefore measuring Kansei is a broader aspect of measuring psychological functioning of the brain. In this research, colour interaction and respective psychological functioning is measured using Kansei measurement method. Further the result of this research was compared with an circumflex model for personality and emotions to recognize the variability of colours in terms of emotional regions. The results indicate that colours have a variable nature and are associated with several different emotions in several different intensities. Colours which have longer wavelengths are more arousing and they generate more psychological functioning than the colours which have shorter wavelengths.

In this study, the change in the synchronization between heartbeat and music was investigated. The phenomena of the synchronization between human heartbeat and musical tempo has been reported in several previous studies, however, it has not yet been fully investigated including the effect of changing the tempo of musical piece on the synchronization. In the experiment, the subjects were exposed to musical pieces in which the tempo was manipulated to gradually increasing (named ?Up? condition), decreasing (?Down?) and constant (?Flat?). Through the analysis by our developed software, Cardio-Music Synchrogram, the shortest length of the total synchronization periods was observed in Flat condition. Furthermore, the temporal change in the synchronization was investigated.

Recent behavioural medicine studies have revealed that the human secretory substances change according to his/her mental states. Especially, those substances transiently get increase (or decrease) against the short-term experimental stressors. However, the relation with rather longer stressor, or daily stressor, has not yet well understood or reported discrepant results. One possible reason for this discrepancy might be brought from uncertainty of the psychological evaluation, which is the score of subjective questionnaire. We then introduced an evaluation criterion of attributes based on rough set theory to analyze the relation between the psychological state and a major immune substance. As a result, several items in the questionnaire were extracted as dominant items, while there was still no correlation between them.

The article presents an analysis?s attempt of the emotional and physiological state of the driver while driving a vehicle. This approach takes into account the correlation of biomedical parameters with the fuzzy classification of facial expression. Based on the results of the experiment, carried out in the real road conditions, driver?s emotional states were determined and identified and then combined with the easily measurable indicators of cardiovascular system.

This paper was aimed at evaluating the mental work-load (MWL) with psycho-physiological indices. Especially, we focused on the intermittent type of MWL, which is assumed as a predisposing factor of various somatic and mental disorders. In the experiment, we introduced a facial skin thermo image comparing with conventional physiological indices, such as electrocardiogram (ECG) and electroencephalogram (EEG). As a result, the facial skin image was suggested to be a useful tool for evaluating such an intermittent type of MWL.

In the paper music therapy was briefly discussed, paying special attention to the state of art under the aspect of stimulation methods which are typically taken into consideration in this process. The purpose of the study is to discuss the possibility of proper defining of the crucial parameters for music therapy, depending on the unique determinants of the individual patient?s character. It is pointed out, that in a therapy especially a metre and rhythm should be considered as the main elements of the generator for music stimulation.