Yazar "Tekin, Ramazan" seçeneğine göre listele
Listeleniyor 1 - 7 / 7
Sayfa Başına Sonuç
Sıralama seçenekleri
Öğe Classification of Hand Opening/Closing and Fingers by Using Two Channel Surface EMG Signal(Ieee, 2017) Sezgin, Necmettin; Ertugrul, Omer Faruk; Tekin, Ramazan; Tagluk, Mehmet EminIn this study, two-channel surface electromyogram (sEMG) signals were used to classify hand open/close with fingers. The bispectrum analysis of the sEMG signal recorded with surface electrodes near the region of the muscle bundles on the front and back of the forearm was classified by extreme learning machines (ELM) based on phase matches in the EMG signal. EMG signals belonging to 17 persons, 8 males and 9 females, with an average age of 24 were used in the study. The fingers were classified using ELM algorithm with 94.60% accuracy in average. From the information obtained through this study, it seems possible to control finger movements and hand opening/closing by using muscle activities of the forearm which we hope to lead to control of intelligent prosthesis hands with high degree of freedom.Öğe Complexity and Irregularity Analysis of the Output Data of a Cortical Network(Ieee, 2013) Tekin, Ramazan; Tagluk, M. Emin; Ertugrul, Omer Faruk; Sezgin, NecmettinDepending on the complex interconnection of billions of neurons forming cortical network excitation times and the emergence of action potentials or spike trains becomes complex and irregular. The effect of various parameters such as synaptic connections, conductivity and voltage dependent channels on the output of the network has become of research issues. In this study, based on Hodgkin-Huxley neuron model an artificial cortical network that simulates a local region of cortex was designed and the effect of probabilistic values of network parameters used in this model on irregularity and complexity of the spike trains at the neurons' output were investigated. Approximation Entropy, Spectral Entropy and Magnitude Squared Coherence methods were used for irregularity analysis.Öğe Effects of Small-World Rewiring Probability and Noisy Synaptic Conductivity on Slow Waves: Cortical Network(Mit Press, 2017) Tekin, Ramazan; Tagluk, Mehmet EminPhysiological rhythms play a critical role in the functional development of living beings. Many biological functions are executed with an interaction of rhythms produced by internal characteristics of scores of cells. While synchronized oscillations may be associated with normal brain functions, anomalies in these oscillations may cause or relate the emergence of some neurological or neuropsychological pathologies. This study was designed to investigate the effects of topological structure and synaptic conductivity noise on the spatial synchronization and temporal rhythmicity of the waves generated by cells in the network. Because of holding the ability of clustering and randomizing with change of parameters, small-world (SW) network topology was chosen. The oscillatory activity of network was tried out by manipulating an insulated SW, cortical network model whose morphology is very close to real world. According to the obtained results, it was observed that at the optimal probabilistic rates of conductivity noise and rewiring of SW, powerful synchronized oscillatory small waves are generated in relation to the internal dynamics of cells, which are in line with the network's input. These two parameters were observed to be quite effective on the excitation-inhibition balance of the network. Accordingly, it may be suggested that the topological dynamics of SW and noisy synaptic conductivity may be associated with the normal and abnormal development of neurobiological structure.Öğe EMG Signal Classification by Extreme Learning Machine(Ieee, 2013) Ertugrul, Omer Faruk; Tagluk, M. Emin; Kaya, Yilmaz; Tekin, RamazanFrom disease detection to action assessment EMG signals are used variety of field. Miscellaneous studies have been conducted toward analysis of EMG signals. In this study some statistical features of signal were derived, the best evocative features were selected via Linear Discriminant Analysis (LDA) and feature vectors were constructed. This analytic feature vectors were classified through Extreme Learning Machine (ELM). 8 channel EMG signals recorded from 10 normal and 10 aggressive actions were used as an example. By cross-comparison of the obtained results to the ones obtained via various feature identifying methods (AR coefficients, wavelet energy and entropy) and classification methods (NB, SVM, LR, ANN, PART, Jrip, J48 and LMT) the success of the proposed method was determined.Öğe The influence of ion concentrations on the dynamic behavior of the Hodgkin-Huxley model-based cortical network(Springer, 2014) Tagluk, M. Emin; Tekin, RamazanAction potentials (APs) in the form of very short pulses arise when the cell is excited by any internal or external stimulus exceeding the critical threshold of the membrane. During AP generation, the membrane potential completes its natural cycle through typical phases that can be formatted by ion channels, gates and ion concentrations, as well as the synaptic excitation rate. On the basis of the Hodgkin-Huxley cell model, a cortical network consistent with the real anatomic structure is realized with randomly interrelated small population of neurons to simulate a cerebral cortex segment. Using this model, we investigated the effects of Na+ and K+ ion concentrations on the outcome of this network in terms of regularity, phase locking, and synchronization. The results suggested that Na+ concentration does slightly affect the amplitude but not considerably affects the other parameters specified by depolarization and repolarization. K+ concentration significantly influences the form, regularity, and synchrony of the network-generated APs. No previous study dealing directly with the effects of both Na+ and K+ ion concentrations on regularity and synchronization of the simulated cortical network-generated APs, allowing for the comparison of results obtained using our methods, was encountered in the literature. The results, however, were consistent with those obtained through studies concerning resonance and synchronization from another perspective and with the information revealed through physiological and pharmacological experiments concerning changing ion concentrations or blocking ion channels. Our results demonstrated that the regularity and reliability of brain functions have a strong relationship with cellular ion concentrations, and suggested the management of the dynamic behavior of the cellular network with ion concentrations.Öğe Influence of Rewiring on Spike Activity and Phase Coherence in a Small-World Cortical Network(Ieee, 2016) Tekin, Ramazan; Tagluk, M. EminSubthreshold spike activities have a critical importance in synchronization of neuronal activity. In nonlinear systems, low level signals, depending on topologic structure and noise level, can increase the activity of the systems. Whether similar effects are valid for normal brain function or not is an important question need to be addressed. So, the objective of this study was to investigate for the influence of rewiring in a cortical network with Small-World (SW) topology on spike coherency. The investigation showed that SW rewiring rate (p) has an effect on synchronization of subthreshold activities and therefore increasing spike activity and increased discharges synchronized to the input of network.Öğe Small-World modelinde yeniden yapılandırma ve gürültülü sinaptik iletkenliğin talamokortikal yavaş dalgalar üzerindeki etkileri(İnönü Üniversitesi, 2015) Tekin, RamazanBeyin, farklı durum ve davranışlara bağlı olarak birçok frekans bileşenden oluşan çeşitli salınımlar ortaya çıkarabilmektedir. Normal beyin fonksiyonları birçok beyin bölgesinin eş zamanlı oluşturduğu senkronize salınımlar ile ilintilidir. Bu senkronizasyonun bozulması durumunda beyin fonksiyonlarında anormallikler oluşmaktadır. Bu salınımların bozulması birtakım nörolojik ve nöropsikolojik rahatsızlıkların oluşması ile ilişkilendirilmiştir. Birçok doğal ve biyolojik sistemde olduğu gibi, sinir hücrelerinde de önemli olgular olan topolojik yapı ve sinaptik gürültünün normal beyin fonksiyonlarında kritik bir öneme sahip olduğu bilinmekte, ancak senkronize yavaş salınımlı beyin dalgaları üzerinde nasıl bir etkiye sahip oldukları cevaplanması gereken önemli bir sorudur. Bu çalışmada, derin uyku ve anestezi sırasında ortaya çıkan ve günlük hayatta edinilen deneyimlerin hafızada kalıcı hale gelmesine yardımcı olduğu düşünülen yavaş dalga ritimleri incelenmiştir. Korteks ve alt kortikal bir bölge olan talamus ile ilişkili bu salınımların Small-World (SW) ağ modelinde yeniden yapılandırma ve sinaptik iletkenlik gürültüsüne bağlı olarak yavaş dalga aktivitesinde oluşan değişimler öncelikle bu beyin bölgeleri izole edilerek analiz edilmiştir. Daha sonra bu iki beyin bölgesinin karşılıklı projeksiyonlar ile bağlandığı talamokortikal sistem üzerinde analizler yapılmıştır. Bu analizler aracılığıyla toplam ağ aktivitesi karakterize edilmiş ve ağın spektral içeriği belirlenmiştir. Elde edilen sonuçlara göre, SW'nin topolojik yapısındaki yeniden yapılandırma ve sinaptik iletkenlik gürültüsünün hücrelerin içsel ritmik spike aktivitelerinin eşevresel ve senkronize oluşumunda kritik bir önemi olduğu görülmüştür. Talamokortikal ağlarda, uygun SW yeniden yapılandırma olasılık ve gürültülü sinaptik iletkenliğin standart sapma değerlerinde uzaysal senkronizasyon ve zamansal ritmik aktivitenin yüksek seviyede olduğu salınımların oluştuğu görülmüştür.
