Joško Šoda

A novel approach for monitoring writing interferences during navigated transcranial magnetic stimulation mappings of writing related cortical areas.

BACKGROUND It has recently been shown that navigated repetitive transcranial magnetic stimulation (nTMS) is useful in preoperative neurosurgical mapping of motor and language brain areas. In TMS mapping of motor cortices the evoked responses can be quantitatively monitored by electromyographic (EMG) recordings. No such setup exists for monitoring of writing during nTMS mappings of writing related cortical areas. NEW METHOD We present a novel approach for monitoring writing during nTMS mappings of motor writing related cortical areas. COMPARISON WITH EXISTING METHOD(S) To our best knowledge, this is the first demonstration of quantitative monitoring of motor evoked responses from hand by EMG, and of pen related activity during writing with our custom made pen, together with the application of chronometric TMS design and patterned protocol of rTMS. RESULTS The method was applied in four healthy subjects participating in writing during nTMS mapping of the premotor cortical area corresponding to BA 6 and close to the superior frontal sulcus. The results showed that stimulation impaired writing in all subjects. The corresponding spectra of measured signal related to writing movements was observed in the frequency band 0-20 Hz. Magnetic stimulation affected writing by suppressing normal writing frequency band. CONCLUSION The proposed setup for monitoring of writing provides additional quantitative data for monitoring and the analysis of rTMS induced writing response modifications. The setup can be useful for investigation of neurophysiologic mechanisms of writing, for therapeutic effects of nTMS, and in preoperative mapping of language cortical areas in patients undergoing brain surgery.

Pre-Processing for Image Sequence Visualization Robust to Illumination Variations

Several images (a sequence) may be used to obtain better image quality. This method is perfect for super-resolution algorithms, which improve sub-pixel clarity of the image and allow a more detailed view. It is possible that illumination variations, e.g. those caused by a light source, lessen the benefits of super-resolution algorithms. The reduction of the quantity of such occurrences by stabilizing variations is important. An enhanced stabilization algorithm is proposed for purposes of reduction of variations in illumination. It is based on the energy contained in wavelet coefficients. In the proposed algorithm, energy plays a role of the memory buffer in memory-based techniques of illumination variation reduction. The benefits of the proposed image stabilization are the higher quality of images and better visualization. Possible applications are in surveillance, product quality control, engine monitoring, corrosion monitoring, micro/nano microscopy, etc.

Corrosion Monitoring in Marine Environment Using Wavelet Description

The paper proposes a method, the so-called wavelet description, for corrosion monitoring in marine environment which is based on taking the energy difference contained in energy from coefficients derived by applying complex wavelet transforms. Then the rms value of coefficients has been accounted that form an illumination-independent energy representation of corroded and corrosion-free parts. The robustness on illumination variations has been achieved because by applying the proposed algorithm the energy representation enables reduction of the noise, since getting the difference of two subsequent images leaves only greater values of differences.

Dielectric Material Selection Optimization Based on Relative Dielectric Constant Dependencies in Operating Environment

Selecting suitable material is an important issue in applied engineering. In this paper, an algorithm for optimum dielectric material identification is developed. Its scope covers general and specific requirements for the marine environment, using the parameters of influence to test whether the chosen material is suitable for use in the range of the parameters. The design of a parameter’s range is determined by the designer, and should be suited to the exact field of the specific application. The proposed algorithm is also location/application-dependent. It provides a framework for further development of self-turning devices, correcting itself by calculating the influence of environmental conditions.

Multiobjective Optimization of Dielectric Material’s Selection in Marine Environment

In this paper, a multiobjective approach to the optimal material’s selection for dielectrics in marine environment is proposed. The starting point is the definition of the Pareto optimal criteria for the material selection. The proposed method is visualized and the proposed algorithm is explained step by step. The dielectric material is identified from the lookup table by the relative permittivity. Dominant dependences are simulated through the influence to the relative permittivity.

Wind Disturbance Suppression in Autopilot Design

Environmental conditions affects ship’s course. Hence, it affects velocity, and efficiency of fuel consumption, which is an important research topic nowadays. Therefore, it is important to take it into account in the design of ship’s autopilots. In this paper a method is proposed to compensate for wind’s influence, which is based on wavelet transform by introducing the so called wavelet anti-filter. The anti-filter is added to the feed-forward branch of the classic autopilot design scheme, which consists of feedback loop and PID controller. The anti-filter branch represents a modification of the classic scheme.

Damage Detection in Materials Based on Computer Vision Wavelet Algorithm

Damage detection covers a wide range of different problems in a variety of technological, scientific and engineering fields. Solutions and reliability of results vary depending on the application and the field. This chapter explores the possibilities of application of computer vision in damage detection in materials. An example of damage detection in electronic components is presented, in which damage detection is based on the proposed computer vision wavelet algorithm. Furthermore, it proposes the incorporation of the algorithm in cloud service for industrial quality control. Results from the application of different wavelets are presented in the chapter.

Discontinuity Detection in the Vibration Signal of Turning Machines

The chapter deals with the detection of discontinuities in the vibration signal created by a turning machine in soft and hard processes. This chapter presents an experiment with two embedded piezo-electrical sensors on the turning machine tool tip. AISI 4140 steel workpieces are used in the experiments to obtain the analyzed signal. The purpose of the experiment is to identify the nature and position of rapid changes as a measure of compliance with surface roughness. A new algorithm for wavelet selection is developed and the procedure proved the Daubechies wavelet of the 6th order to be the best choice. The proposed algorithm is based on a new technique of energy matching for wavelets. Due to the algorithm’s efficiency, it is well suited for real time monitoring. Furthermore, it is possible to build a real time monitoring system based on the digital signal system.

Visualization of Global Illumination Variations in Motion Segmentation

Motion segmentation is the most important part in many applications, such as surveillance, security, monitoring, recognition, etc. The presented research deals with short-term illumination variations in video streams. Illumination variations influence values of pixels and greatly impact the segmentation mask obtained as a part of a motion detection algorithm. In order to subjectively visualize the extent of variations, these must be emphasized. The chapter presents a wavelet energy model based algorithm which detects and emphasizes illumination variations.