Application of Higuchi fractal dimension and indepenedent component method in analysis of garden snail Br neuron bursting activity modulated by static magnetic field and ouabain.

Nelinearne i napredne statističke metode, pored linearnih metoda, zauzimaju sve značajnije mesto u analizi fizioloških signala, posebno u svetlu nelinearnog i haotičnog ponašanja bioloških sistema. Stoga je zajednička upotreba Higučijeve fraktalne dimenzije i analize nezavisnih komponentata (ICA), značajan i nov pristup u analizi signala a posebno u analizi aktivnosti jednog neurona. Najprepoznatljiviji tip spontane bioelektrične aktivnosti neurona beskičmenjaka i kičmenjaka jeste pojava akcionih potencijala u paketićima. U radu je po prvi put primenjen, jedinstven i inovativan pristup u razdvajanju komponenata spontane bioelektrične aktivnosti Br neurona vinogradskog puža i to na akcione potencijale (AP), intervale između akcionih potencijala (ISI) i tihe intervale bez aktivnosti (IBI) uz pomoć Higučijeve fraktalne dimenzije i aproksimacije Gausovim funkcijama. Taj metodološki pristup je omogućio praćenje uticaja konstantnog magnetnog polja i uabaina inhibitora Na+/K+ pumpe na promene u kompleksnosti spontane bioelektrične aktivnosti Br neurona. Sa druge strane, po prvi put je testirana upotreba ICA metode u različitim eksperimentalnim uslovima po AP, ISI i IBI komponentama spontane bioelektrične aktivnosti. Na taj način, u ovom radu demonstrirana je snaga zajedničke upotrebe navedenih metoda uz predlog da se proširi njihova upotreba za potrebe analize spontano aktivnih neurona različitih vrsta u fiziološkim i patološkim stanjima.Nonlinear and advanced statistical methods, in addition to linear methods, occupy a prominent place in the analysis of physiological signals, especially in light of the non-linear and chaotic behavior of biological systems. Therefore, the use of Higuchi fractal dimension and independent component analysis (ICA), reperesents a new approach to signal analysis, especially regarding the activities of one neuron. The most recognizable type of spontaneous bioelectric activity in neurons of invertebrates as well as vertebrates is the appearance of bursting activity. This study presents a unique and innovative approach to the separation of the components of spontaneous bioelectric activity of the garden snail Br neuron - action potential (AP), interspike interval (ISI) and interburst interval (IBI), by using Higuchi’s fractal dimension and Gaussian fitting functions. This methodological approach allows monitoring of the effect of static magnetic field and the inhibitor of the Na+/K+ pump, ouabain, on the changes in the complexity of the spontaneous bioelectric activity of the Br neuron. On the other hand, for the first time ICA method was tested in different experimental conditions on AP, ISI and IBI components of spontaneous bioelectric activity. This study demonstrates the power of the common use of the above mentioned methods and proposes to extend their use for the purpose of analyzing spontaneously active neurons of different species in physiological and patological conditions

Multifractal techniques for analysis and classification of emphysema images

This thesis proposes, develops and evaluates different multifractal methods for detection, segmentation and classification of medical images. This is achieved by studying the structures of the image and extracting the statistical self-similarity measures characterized by the Holder exponent, and using them to develop texture features for segmentation and classification. The theoretical framework for fulfilling these goals is based on the efficient computation of fractal dimension, which has been explored and extended in this work. This thesis investigates different ways of computing the fractal dimension of digital images and validates the accuracy of each method with fractal images with predefined fractal dimension. The box counting and the Higuchi methods are used for the estimation of fractal dimensions. A prototype system of the Higuchi fractal dimension of the computed tomography (CT) image is used to identify and detect some of the regions of the image with the presence of emphysema. The box counting method is also used for the development of the multifractal spectrum and applied to detect and identify the emphysema patterns. We propose a multifractal based approach for the classification of emphysema patterns by calculating the local singularity coefficients of an image using four multifractal intensity measures. One of the primary statistical measures of self-similarity used in the processing of tissue images is the Holder exponent (α-value) that represents the power law, which the intensity distribution satisfies in the local pixel neighbourhoods. The fractal dimension corresponding to each α-value gives a multifractal spectrum f(α) that was used as a feature descriptor for classification. A feature selection technique is introduced and implemented to extract some of the important features that could increase the discriminating capability of the descriptors and generate the maximum classification accuracy of the emphysema patterns. We propose to further improve the classification accuracy of emphysema CT patterns by combining the features extracted from the alpha-histograms and the multifractal descriptors to generate a new descriptor. The performances of the classifiers are measured by using the error matrix and the area under the receiver operating characteristic curve (AUC). The results at this stage demonstrated the proposed cascaded approach significantly improves the classification accuracy. Another multifractal based approach using a direct determination approach is investigated to demonstrate how multifractal characteristic parameters could be used for the identification of emphysema patterns in HRCT images. This further analysis reveals the multi-scale structures and characteristic properties of the emphysema images through the generalized dimensions. The results obtained confirm that this approach can also be effectively used for detecting and identifying emphysema patterns in CT images. Two new descriptors are proposed for accurate classification of emphysema patterns by hybrid concatenation of the local features extracted from the local binary patterns (LBP) and the global features obtained from the multifractal images. The proposed combined feature descriptors of the LBP and f(α) produced a very good performance with an overall classification accuracy of 98%. These performances outperform other state-of-the-art methods for emphysema pattern classification and demonstrate the discriminating power and robustness of the combined features for accurate classification of emphysema CT images. Overall, experimental results have shown that the multifractal could be effectively used for the classifications and detections of emphysema patterns in HRCT images

Application of Higuchi fractal dimension and indepenedent component method in analysis of garden snail Br neuron bursting activity modulated by static magnetic field and ouabain.

Nelinearne i napredne statističke metode, pored linearnih metoda, zauzimaju sve značajnije mesto u analizi fizioloških signala, posebno u svetlu nelinearnog i haotičnog ponašanja bioloških sistema. Stoga je zajednička upotreba Higučijeve fraktalne dimenzije i analize nezavisnih komponentata (ICA), značajan i nov pristup u analizi signala a posebno u analizi aktivnosti jednog neurona. Najprepoznatljiviji tip spontane bioelektrične aktivnosti neurona beskičmenjaka i kičmenjaka jeste pojava akcionih potencijala u paketićima. U radu je po prvi put primenjen, jedinstven i inovativan pristup u razdvajanju komponenata spontane bioelektrične aktivnosti Br neurona vinogradskog puža i to na akcione potencijale (AP), intervale između akcionih potencijala (ISI) i tihe intervale bez aktivnosti (IBI) uz pomoć Higučijeve fraktalne dimenzije i aproksimacije Gausovim funkcijama. Taj metodološki pristup je omogućio praćenje uticaja konstantnog magnetnog polja i uabaina inhibitora Na+/K+ pumpe na promene u kompleksnosti spontane bioelektrične aktivnosti Br neurona. Sa druge strane, po prvi put je testirana upotreba ICA metode u različitim eksperimentalnim uslovima po AP, ISI i IBI komponentama spontane bioelektrične aktivnosti. Na taj način, u ovom radu demonstrirana je snaga zajedničke upotrebe navedenih metoda uz predlog da se proširi njihova upotreba za potrebe analize spontano aktivnih neurona različitih vrsta u fiziološkim i patološkim stanjima.Nonlinear and advanced statistical methods, in addition to linear methods, occupy a prominent place in the analysis of physiological signals, especially in light of the non-linear and chaotic behavior of biological systems. Therefore, the use of Higuchi fractal dimension and independent component analysis (ICA), reperesents a new approach to signal analysis, especially regarding the activities of one neuron. The most recognizable type of spontaneous bioelectric activity in neurons of invertebrates as well as vertebrates is the appearance of bursting activity. This study presents a unique and innovative approach to the separation of the components of spontaneous bioelectric activity of the garden snail Br neuron - action potential (AP), interspike interval (ISI) and interburst interval (IBI), by using Higuchi’s fractal dimension and Gaussian fitting functions. This methodological approach allows monitoring of the effect of static magnetic field and the inhibitor of the Na+/K+ pump, ouabain, on the changes in the complexity of the spontaneous bioelectric activity of the Br neuron. On the other hand, for the first time ICA method was tested in different experimental conditions on AP, ISI and IBI components of spontaneous bioelectric activity. This study demonstrates the power of the common use of the above mentioned methods and proposes to extend their use for the purpose of analyzing spontaneously active neurons of different species in physiological and patological conditions

Effect of age and gender on sEMG signals and force steadiness

Challenges encountered during daily activities are easily overcome by young adults but may be potential risk for falls and injuries among the elderly due to age-associated sensorimotor deficits. To mitigate these risks, early detection of neuromuscular changes is essential and it is important for these to be cost-efficient, non-invasive, high throughput and non-hazardous. Electromyogram (EMG) is a non-invasive recording of the muscle activity that uses inexpensive equipment and hence may be considered for this purpose. However, it is a gross non-specific signal and thus there is need for careful investigation to identify its suitability for studying age-associated changes to the muscles. This research has investigated non-invasive, superficially recorded EMG signals to identify the differences between young healthy adults (20-35 years) and older (60-80 years) subjects of both genders while they were performing isometric ankle plantar flexion and dorsiflexion. The study also studied age and gender differences in the maximal voluntary force, its steadiness, the time to reach steadiness and modulus of the force output prior to steadiness as measured at the foot plate during dorsi- and plantar-flexion. This study has experimentally demonstrated the significant increase in co-activation index around the ankle joint, decrease in the agonistic activity and increase in antagonistic activity in the major lower leg muscles due to ageing. Female participants were noted to have a higher co-activation index in comparison to the males of corresponding age group. From the analysis, it was observed that ageing causes an overall decline in muscle signal complexity affecting the whole muscle strength in both genders. Furthermore, it was also established that within the triceps surae muscle group, Soleus and the gastrocnemii showed varied effects of aging. Another key finding is the significant age and gender difference in the maximal force and its steadiness around the ankle joint during dorsiflexion. However, these differences are less significant during plantarflexion. Results of this study revealed that with age, there was an increase in the total modulus of the force used by the participant to stabilize the foot at a desired level of contraction, difference being more significant during dorsiflexion. This study highlights the age associated neuromuscular adaptations in plantarflexor and dorsiflexor muscles. This is reflected in the altered activity of agonistic and antagonistic muscles during isometric contractions, the reduction in the overall muscle signal complexity, and decreased strength and steadiness of the force exerted by the calf muscles. It has established gender differences in the reduction of the co-activation index and decreased force strength during ankle flexion movements