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cagdastopcu/README.md

Hi there, I am Cagdas. I develop neural signal processing methods in MATLAB and Python 👋

I have 8 papers in biomedical engineering and neuroscience journals, 2 patent applications on cognitive brain modulation with electrical stimulation, more than 15 conference presentations and talks and 2 book chapters.

  • 🔭 I’m currently working on human verbal memory.
  • 🌱 I’m currently learning Pytorch.
  • 💬 Ask me about neuroscience, data science and signal processing.
  • 📫 How to reach me (twitter): @cagdastopcu
  • ⭐ Papers: Google scholar
  • 😄 Pronouns: he/him

👾 Languages and Tools :

Matlab  Python  Pytorch  Numpy  pandas  GIT  networkx 

🛠️ Technical skills :

Collecting and processing electrocorticography (ECoG), intracranial electroencephalography (iEEG), stereoelectroencephalography (sEEG), electromyogram (EMG), mechanomyogram (MMG), electrocardiogram (ECG), respiration and pulse data from healthy individuals and patients. Neurolynx, and ADInstruments PowerLab recording systems. Human verbal memory. Biomarkers for memory effect. Functional electrical stimulation. Muscle synergies and muscle networks with intermuscular coherence and non-negative matrix factorization (NNMF) and principal component analysis (PCA). Muscle onset detection with Fuzzy entropy. Brain plasticity. Synchronization and Kuramoto model of complex networks. Coupled oscillatory systems and coupling functions. Hilbert Transform. Statistical, frequency domain and nonlinear heart rate variability measures. Multiresolution signal processing aka wavelets. Nonlinear signal processing (fractal dimension, approximate entropy, sample entropy, wavelet entropy, wavelet packet entropy, fuzzy entropy). Dynamical functional connectivity from iEEG data. Classification with k-nearest neighbor (KNN), linear discriminant analysis (LDA), Gaussian mixture model (GMM), k-means clustering, feedforward neural networks, radial basis function (RBF) neural networks, support vector machine (SVM), autoencoder.


Top Langs


GitHub Streak Github Mastodon

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  1. PhysioFeat PhysioFeat Public

    PhysioFeat is a collection of feature extraction methods. These signal processing methods can be applied on non-stationary physiological signals such as electromyography (EMG), electrocardiography …

    MATLAB 9 1

  2. EMG_Processing_ECCN2019 EMG_Processing_ECCN2019 Public

    I uploaded tools for EMG processing and neurorehabilitation engineering problems

    MATLAB 1

  3. Disentangling-Respiratory-Sinus-Arrhythmia-in-Heart-Rate-Variability-Records Disentangling-Respiratory-Sinus-Arrhythmia-in-Heart-Rate-Variability-Records Public

    Algorithm to Disentangle RSA from HRV based on the theory of coupled systems

    Jupyter Notebook

  4. FacialExpressionsofFullFaceTransplantationsExperimentUserInterface FacialExpressionsofFullFaceTransplantationsExperimentUserInterface Public

    This user interface was developed to collect videos and facial EMG data for facial expressions and primary facial movements after full-face transplantation. It shows muscle contraction times to pat…

    MATLAB 1

  5. dbs-wavelet-packet-energy-macro dbs-wavelet-packet-energy-macro Public

    Python

  6. convolutional-wavelet-packet-autoencoder-for-dbs-recordings convolutional-wavelet-packet-autoencoder-for-dbs-recordings Public

    Wavelet packet CNN autoencoder for deep brain stimulation recordings during a memory task in pytorch

    Jupyter Notebook