216 citations · 816 across the 46 of their papers we have counts for
9 papers · 1 filter
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…
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…
Time-Series Prediction of Proximal Aggression Onset in Minimally-Verbal Youth with Autism Spectrum Disorder Using Physiological Biosignals
Ozan Ozdenizci, Catalina Cumpanasoiu, Carla Mazefsky +4
It has been suggested that changes in physiological arousal precede potentially dangerous aggressive behavior in youth with autism spectrum disorder (ASD) who are minimally verbal…
Hierarchical Graphical Models for Context-Aware Hybrid Brain-Machine Interfaces
Ozan Ozdenizci, Sezen Yagmur Gunay, Fernando Quivira +1
We present a novel hierarchical graphical model based context-aware hybrid brain-machine interface (hBMI) using probabilistic fusion of electroencephalographic (EEG) and electromyo…
Context-Aware Recursive Bayesian Graph Traversal in BCIs
Seyed Sadegh Mohseni Salehi, Mohammad Moghadamfalahi, Hooman Nezamfar +2
Noninvasive brain computer interfaces (BCI), and more specifically Electroencephalography (EEG) based systems for intent detection need to compensate for the low signal to noise ra…
Decoding Complex Imagery Hand Gestures
Seyed Sadegh Mohseni Salehi, Mohammad Moghadamfalahi, Fernando Quivira +3
Brain computer interfaces (BCIs) offer individuals suffering from major disabilities an alternative method to interact with their environment. Sensorimotor rhythm (SMRs) based BCIs…
An Active RBSE Framework to Generate Optimal Stimulus Sequences in a BCI for Spelling
Mohammad Moghadamfalahi, Murat Akcakaya, Hooman Nezamfar +2
A class of brain computer interfaces (BCIs) employs noninvasive recordings of electroencephalography (EEG) signals to enable users with severe speech and motor impairments to inter…
Fast Switch Scanning Keyboards: Minimal Expected Query Decision Trees
Matt Higger, Mohammad Moghadamfalahi, Fernando Quivira +1
Augmentative and Alternative Communication (AAC) systems allow people with disabilities to provide input to devices which empower them to more fully interact with their environment…