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Bioelectrical and Neuroengineering Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Bioelectrical and Neuroengineering
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
College of Graduate Studies: Theses & Dissertations
Electroencephalogram (EEG) has been used in a wide array of applications to study mental disorders. Due to its non-invasive and low-cost features, EEG has become a viable instrument in Brain-Computer Interfaces (BCI). These BCI systems integrate user's neural features with robotic machines to perform tasks. However, due to EEG signals being highly dynamic in nature, BCI systems are still unstable and prone to unanticipated noise interference. An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to implement …
Applying Spiking Neural Network Simulation To Neuromodulatory Autonomous Robot Control, Cameron Muhammad
Applying Spiking Neural Network Simulation To Neuromodulatory Autonomous Robot Control, Cameron Muhammad
Phi Kappa Phi Research Symposium (Archived)
In this paper, simulation of the brain based on an artificial spiking neuron model is used to create a self-learning algorithm. The spiking neuron simulation is used to demonstrate a neuromodulation program in which the reward seeking properties of dopamine, the risk-adverse effects of serotonin, and the attention-focusing effects of the cholinergic and noradrenergic systems are applied to a mobile robotic platform as it moves autonomously throughout an environment. External stimuli is recorded by the program as spiking “events” that result in corresponding amounts of dopamine and serotonin influenced spiking patterns. These spiking patterns affect how the robot adapts to …
Neuromodulation Based Control Of Autonomous Robots On A Cloud Computing Platform, Cameron Muhammad
Neuromodulation Based Control Of Autonomous Robots On A Cloud Computing Platform, Cameron Muhammad
College of Graduate Studies: Theses & Dissertations
In recent years, the advancement of neurobiologically plausible models and computer networking has resulted in new ways of implementing control systems on robotic platforms. The work presents a control approach based on vertebrate neuromodulation and its implementation on autonomous robots in the open-source, open-access environment of robot operating system (ROS). A spiking neural network (SNN) is used to model the neuromodulatory function for generating context based behavioral responses of the robots to sensory input signals. The neural network incorporates three types of neurons- cholinergic and noradrenergic (ACh/NE) neurons for attention focusing and action selection, dopaminergic (DA) neurons for rewards- and …