216 citations · 816 across the 46 of their papers we have counts for
46 papers
A Multi-label Classification Approach to Increase Expressivity of EMG-based Gesture Recognition
Niklas Smedemark-Margulies, Yunus Bicer, Elifnur Sunger +5
Objective: The objective of the study is to efficiently increase the expressivity of surface electromyography-based (sEMG) gesture recognition systems. Approach: We use a problem t…
User Training with Error Augmentation for Electromyogram-based Gesture Classification
Yunus Bicer, Niklas Smedemark-Margulies, Basak Celik +7
We designed and tested a system for real-time control of a user interface by extracting surface electromyographic (sEMG) activity from eight electrodes in a wrist-band configuratio…
Corticomorphic Hybrid CNN-SNN Architecture for EEG-based Low-footprint Low-latency Auditory Attention Detection
Richard Gall, Deniz Kocanaogullari, Murat Akcakaya +2
In a multi-speaker "cocktail party" scenario, a listener can selectively attend to a speaker of interest. Studies into the human auditory attention network demonstrate cortical ent…
Variation is the Norm: Brain State Dynamics Evoked By Emotional Video Clips
Ashutosh Singh, Christiana Westlin, Hedwig Eisenbarth +7
For the last several decades, emotion research has attempted to identify a "biomarker" or consistent pattern of brain activity to characterize a single category of emotion (e.g., f…
Cubature Kalman Filter Based Training of Hybrid Differential Equation Recurrent Neural Network Physiological Dynamic Models
Ahmet Demirkaya, Tales Imbiriba, Kyle Lockwood +5
Modeling biological dynamical systems is challenging due to the interdependence of different system components, some of which are not fully understood. To fill existing gaps in our…
Efficient Modeling of Morphing Wing Flight Using Neural Networks and Cubature Rules
Paul Ghanem, Yunus Bicer, Deniz Erdogmus +1
Fluidic locomotion of flapping Micro Aerial Vehicles (MAVs) can be very complex, particularly when the rules from insect flight dynamics (fast flapping dynamics and light wings) ar…
Circular-Symmetric Correlation Layer based on FFT
Bahar Azari, Deniz Erdogmus
Despite the vast success of standard planar convolutional neural networks, they are not the most efficient choice for analyzing signals that lie on an arbitrarily curved manifold,…
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction Networks
Ozan Ozdenizci, Deniz Erdogmus
Feature ranking and selection is a widely used approach in various applications of supervised dimensionality reduction in discriminative machine learning. Nevertheless there exists…
From Hand-Perspective Visual Information to Grasp Type Probabilities: Deep Learning via Ranking Labels
Mo Han, Sezen Ya{ğ}mur Günay, İlkay Yıldız +5
Limb deficiency severely affects the daily lives of amputees and drives efforts to provide functional robotic prosthetic hands to compensate this deprivation. Convolutional neural…
HANDS: A Multimodal Dataset for Modeling Towards Human Grasp Intent Inference in Prosthetic Hands
Mo Han, Sezen Ya{ğ}mur Günay, Gunar Schirner +2
Upper limb and hand functionality is critical to many activities of daily living and the amputation of one can lead to significant functionality loss for individuals. From this per…
EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks
Ozan Ozdenizci, Safaa Eldeeb, Andac Demir +2
During daily activities, humans use their hands to grasp surrounding objects and perceive sensory information which are also employed for perceptual and motor goals. Multiple corti…
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals
Ozan Ozdenizci, Deniz Erdogmus
Recent promises of generative deep learning lately brought interest to its potential uses in neural engineering. In this paper we firstly review recently emerging studies on genera…
NetCut: Real-Time DNN Inference Using Layer Removal
Mehrshad Zandigohar, Deniz Erdogmus, Gunar Schirner
Deep Learning plays a significant role in assisting humans in many aspects of their lives. As these networks tend to get deeper over time, they extract more features to increase ac…
Towards Creating a Deployable Grasp Type Probability Estimator for a Prosthetic Hand
Mehrshad Zandigohar, Mo Han, Deniz Erdogmus +1
For lower arm amputees, prosthetic hands promise to restore most of physical interaction capabilities. This requires to accurately predict hand gestures capable of grabbing varying…
Universal Physiological Representation Learning with Soft-Disentangled Rateless Autoencoders
Mo Han, Ozan Ozdenizci, Toshiaki Koike-Akino +2
Human computer interaction (HCI) involves a multidisciplinary fusion of technologies, through which the control of external devices could be achieved by monitoring physiological st…
Disentangled Adversarial Autoencoder for Subject-Invariant Physiological Feature Extraction
Mo Han, Ozan Ozdenizci, Ye Wang +2
Recent developments in biosignal processing have enabled users to exploit their physiological status for manipulating devices in a reliable and safe manner. One major challenge of…
Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry
Aziz Kocanaogullari, Murat Akcakaya, Deniz Erdogmus
Systems that are based on recursive Bayesian updates for classification limit the cost of evidence collection through certain stopping/termination criteria and accordingly enforce…
AutoBayes: Automated Bayesian Graph Exploration for Nuisance-Robust Inference
Andac Demir, Toshiaki Koike-Akino, Ye Wang +1
Learning data representations that capture task-related features, but are invariant to nuisance variations remains a key challenge in machine learning. We introduce an automated Ba…
Prediction of Epilepsy Development in Traumatic Brain Injury Patients from Diffusion Weighted MRI
Md Navid Akbar, Marianna La Rocca, Rachael Garner +2
Post-traumatic epilepsy (PTE) is a life-long complication of traumatic brain injury (TBI) and is a major public health problem that has an estimated incidence that ranges from 2%-5…
Disentangled Adversarial Transfer Learning for Physiological Biosignals
Mo Han, Ozan Ozdenizci, Ye Wang +2
Recent developments in wearable sensors demonstrate promising results for monitoring physiological status in effective and comfortable ways. One major challenge of physiological st…
Active recursive Bayesian inference using Rényi information measures
Yeganeh M. Marghi, Aziz Kocanaogullari, Murat Akcakaya +1
Recursive Bayesian inference (RBI) provides optimal Bayesian latent variable estimates in real-time settings with streaming noisy observations. Active RBI attempts to effectively s…
Mapping Motor Cortex Stimulation to Muscle Responses: A Deep Neural Network Modeling Approach
Md Navid Akbar, Mathew Yarossi, Marc Martinez-Gost +6
A deep neural network (DNN) that can reliably model muscle responses from corresponding brain stimulation has the potential to increase knowledge of coordinated motor control for n…
User-Adaptive Text Entry for Augmentative and Alternative Communication
Matt Higger, Fernando Quivira, Deniz Erdogmus
The viability of an Augmentative and Alternative Communication device often depends on its ability to adapt to an individual user's unique abilities. Though human input can be nois…
Adversarial Feature Learning in Brain Interfacing: An Experimental Study on Eliminating Drowsiness Effects
Ozan Ozdenizci, Barry Oken, Tab Memmott +2
Across- and within-recording variabilities in electroencephalographic (EEG) activity is a major limitation in EEG-based brain-computer interfaces (BCIs). Specifically, gradual chan…