Preliminary evaluation of electroencephalographic entrainment using thalamocortical modelling

Abstract: The concept of linked oscillators in biological control systems has long been established. Frequency entrainment is a predominant explanation behind many biological rhythms. In this paper a preliminary examination of electroencephalographic entrainment is made to survey the possibility and methods of achieving signal entrainment at the highest level of neurological organization and function. A model of the thalamocortical system is employed to generate simulated electroencephalographic signals and is tested in various configurations in the search for entrainment under very simple conditions. Additionally, an analysis of the coupled Van der Pol model of the circadian rhythm controller is performed to identify the possibility of affecting that system with a drastically different coupling input signal. We were able to conclude that overall signal shape can have a significant impact on the entrainment characteristics of the system. Due to the nature of the underlying mathematical structure of the model, by examining the circadian rhythm controller, we found that it is unsuitable for entrainment to an incident entraining signal of much higher frequency.     

Investigating the Interaction Between Oncogene and Tumor Suppressor Protein

It is known that cancer develops when cells in a part of the body begin to grow out of control. Because cancer cells continue to grow and divide with no order, they never differentiate into the specific tissue, and thus, they are functionally different from normal cells. However, there are some genes that help to prevent cells' malignant behavior, and therefore, are referred to as tumor suppressor genes. Here, we have investigated the structural and functional relationships of p53, oncogene and interleukin 2 (IL2) proteins using the resonant recognition model (RRM), a physico-mathematical approach based on digital signal processing methods. In addition, using the RRM concepts, we have designed the peptide analoges that would exhibit tumor-suppression-like activity and be used in anticancer vaccine development.     

Investigation of the applicability of dielectric relaxation properties of amino acid solutions within the resonant recognition model

The resonant recognition model (RRM) is a physicomathematical approach used to analyze the interactions of a protein and its target, using digital signal processing methods. The RRM is based on the finding that there is a significant correlation between the spectra of numerical presentation of protein sequences and their biological activities. Initially, the electron-ion interaction potential was used to represent each amino acid in the protein sequences. In this paper, the dielectric constant (/spl epsiv/') and dielectric loss tangent (tan /spl delta/) parameters have been determined for their possible use in the RRM. These parameters are based on the values of capacitance and conductance obtained experimentally for 20 amino acid solutions using dielectric spectroscopy for the case of the real component of dielectric permittivity; the parameter used is the dielectric increment (/spl Delta//spl epsiv/'), the difference between dielectric constant of the amino acid solution and that of the solvent alone. The results of multiple cross-spectral analyses have shown that parameters analyzed generate in the consensus spectrum one dominant peak corresponding to the common biological activity of proteins studied, allowing the conclusion that these new parameters are suitable for use in the RRM approach.     

Is it Possible to Analyze DNA and Protein Sequences by the Methods of Digital Signal Processing?

Informational content of linear macromolecules (DNA, RNA, and proteins) is analyzed by the method of digital signal processing. Each element (amino acid or nucleotide) of macromolecules is represented by the corresponding value of electron-ion interaction potential. This numerical representation of the primary structure of macromolecules is subjected to digital signal processing in order to extract the information corresponding to biological function. It is shown that the multiple cross spectrum of functionally related sequences exhibits significant peak frequencies. In the case of functionally unrelated sequences such peaks were not found. Peak frequencies are different for different biological functions. Based on this, we conjecture that the peak frequencies in the multiple cross spectrum of sequences with the same boilogical function are related to this biological function.     

Adaptive neuro-fuzzy inference system employing wavelet coefficients for detection of alterations in sleep EEG activity during hypopnoea episodes

The Obstructive Sleep Apnoea Hypopnoea Syndrome (OSAH) means “cessation of breath” during the sleep hours and the sufferers often experience related changes in the electrical activity of the brain and heart. This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for automatic detection of alterations in the human electroencephalogram (EEG) activities during hypopnoea episodes. Decision making was performed in two stages: feature extraction by computation of wavelet coefficients and classification by the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. The EEG signals (pre and during hypopnoea) from three electrodes (C3, C4 and O2) were used as input patterns of the three ANFIS classifiers. To improve diagnostic accuracy, the fourth ANFIS classifier (combining ANFIS) was trained using the outputs of the three ANFIS classifiers as input data. The proposed ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the saliency of features on detecting any possible changes in the human EEG activity due to hypopnoea (mild case of cessation of breath) occurrences were drawn through analysis of the ANFIS. The performance of the ANFIS model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed ANFIS model has potential in detecting changes in the human EEG activity due to hypopnoea episodes.     

A blind equalization algorithm for biological signals transmission

Direct transmission of biological signals such as electrocardiogram (ECG) and electroencephalogram (EEG) through mobile network provides practically unlimited movement of the patients and unlimited coverage area. However, transmission of such signals over a bandlimited channel or through a multipath propagation is subject to inter symbol interference (ISI), whereby adjacent symbols on the output of the channel smear and overlap each other causing degradation of error performance. Mitigation of such kind of distortion can be achieved through equalization filter. Recently an adaptive blind channel equalization using sinusoidally-distributed dithered signed-error constant modulus algorithm (DSE-CMA) has been proposed. In this paper we investigate the performance and the feasibility of this scheme for wireless ECG and EEG transmission. Also, this paper discusses the importance of adaptive blind equalizer for biological signals transmission over existing wireless networks such as Global System for Mobile Communications (GSM) and the Enhanced Data rates for GSM Evolution (EDGE). The geometrical-based hyperbolically distributed scatterers (GBHDS) channel model for macrocell environments was simulated with angular spreads (AS) taken from measurement data. Simulation results show that the low complexity of implementation and the fast convergence rate are the major advantages of deploying this scheme for telemedicine applications. It is also shown that the equalizer output signal is highly correlated with the original transmitted signal in time and joint time-frequency domains.     

Absorption in human body at 900 MHz for oblique incidence of plane wave

ICNIRP(1998) and IEEE C95.1-2005 limits for human exposure to radio-frequency fields are derived based on the condition of maximal coupling of the field to the body. In this study, at 900 MHz, the whole body average specific absorption rate (SAR_WB) for an adult's and a child's body is computed under these conditions and is shown to be also relatively uniform when explored over a range of oblique angles of incidence and polarisation of a constant amplitude plane wave. The SAR_WB in the body remains below the public limit of 80 mW/kg when the oblique field is maintained at the limit value of 41.1 V/m.     

Engineering geological evaluation of the conditions for constructing a bridge and a tunnel in the zone of the old Petrovaradin Fortress,Serbia

The paper discusses the geotechnical conditions related to the construction of a new bridge over the Danube and a tunnel passing beneath the Petrovaradin Fortress at Novi Sad, Serbia. Analyses showed that both the bridge and the tunnel could be built without causing damage to any of the historical structures and that it would better to build two 8 m wide tunnels than a single 16 m wide structure. One of the two tunnels will involve the widening of an existing one, whereas the other will be newly constructed. The evidence suggests that the new bridge can be built on the reinforced piers of a bridge which was destroyed in World War II.     

Protein sequence comparison based on the wavelet transform approach

A protein's chemical properties, the chain conformation, thefunction of the protein and its species specificity are determinedby the information contained in the amino acid sequence. Proteinsof similar functions have at some level sequential identicalamino acid sequences. The closer the phylogenetic relationship,the more similar are the sequences. To find the similaritiesbetween two or more protein sequences is of great importancefor protein sequence analysis. The differences in the aminoacid sequences permit the construction of a family tree of evolution.In this work, a comparison method was devised that is capableof analysing a protein sequence `hierarchically', i.e. it canexamine a protein sequence at different spatial resolutions.Based on a wavelet decomposition of protein sequences and across-correlation study, a sequence–scale similarity conceptis proposed for generating a similarity vector, which rendersthe comparison of two sequences feasible at different spatialresolutions (scales). This new similarity concept is an expansionof the conventional sequence similarity, which only takes intoaccount the local pairwise amino acid match and ignores theinformation contained in coarser spatial resolutions.     

A system for head-neck rehabilitation exercises based on serious gaming and virtual reality

Acute and chronic neck pain are common medical conditions, and the treatment typically includes physical therapy involving daily exercises. Insufficient motivation of people afflicted with neck pain to adhere to the prescribed exercise regimen may delay their recovery. Accordingly, in this work, we propose a system that motivates the users to perform neck exercises by engaging them in a serious exergame within virtual reality (VR) environment. The system measures the users’ neck movements via a few static and dynamic kinematic tests and a novel VR serious game, tailored to the neck range of motion of each individual user. The game is designed to make the users perform rehabilitative neck movements according to the prescribed exercise regimen while playing. The analysis of acquired data from VR hardware provides insight into flexibility of the neck during head movements and overall neck kinematics, which is valuable for assessment of pain-related stiffness, as well as for progress monitoring. In a user study performed with the proposed system and the Oculus Rift DK2 VR headset, we show that the users find exercising more interesting and engaging when using the proposed system, and that introducing visually rich VR environments makes the users more motivated to continue exercising.