Human in the collaborative loop: a strategy for integrating human activity recognition and non-invasive brain-machine interfaces to control collaborative robots
Human activity recognition (HAR) and brain-machine interface (BMI) are two emerging
technologies that can enhance human-robot collaboration (HRC) in domains such as …
technologies that can enhance human-robot collaboration (HRC) in domains such as …
Single trial detection of error-related potentials in brain–machine interfaces: a survey and comparison of methods
Objective. Error-related potential (ErrP) is a potential elicited in the brain when humans
perceive an error. ErrPs have been researched in a variety of contexts, such as to increase …
perceive an error. ErrPs have been researched in a variety of contexts, such as to increase …
Machine learning techniques for effective pathogen detection based on resonant biosensors
We describe a machine learning (ML) approach to processing the signals collected from a
COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine …
COVID-19 optical-based detector. Multilayer perceptron (MLP) and support vector machine …
[HTML][HTML] Design of a brain-machine interface for reducing false activations of a lower-limb exoskeleton based on error related potential
Abstract Background and objective Brain-Machine Interfaces (BMIs) based on a motor
imagination paradigm provide an intuitive approach for the exoskeleton control during gait …
imagination paradigm provide an intuitive approach for the exoskeleton control during gait …
A generic error-related potential classifier based on simulated subjects
Error-related potentials (ErrPs) are brain signals known to be generated as a reaction to
erroneous events. Several works have shown that not only self-made errors but also …
erroneous events. Several works have shown that not only self-made errors but also …
A deep neural network and transfer learning combined method for cross-task classification of error-related potentials
Background Error-related potentials (ErrPs) are electrophysiological responses that
naturally occur when humans perceive wrongdoing or encounter unexpected events. It …
naturally occur when humans perceive wrongdoing or encounter unexpected events. It …
Yes or no? A study of ErrPs in the “guess what I am thinking” paradigm with stimuli of different visual content
A Berkmush-Antipova, N Syrov, L Yakovlev… - Frontiers in …, 2024 - frontiersin.org
Error-related potentials (ErrPs) have attracted attention in part because of their practical
potential for building brain-computer interface (BCI) paradigms. BCIs, facilitating direct …
potential for building brain-computer interface (BCI) paradigms. BCIs, facilitating direct …
Generative neural spike prediction from upstream neural activity via behavioral reinforcement
It is quite challenging to predict dynamic stimulation patterns on downstream cortical regions
from upstream neural activities. Spike prediction models used in traditional methods are …
from upstream neural activities. Spike prediction models used in traditional methods are …
Hyper-accelerated learning for brain-computer interfaces via partial target-aware optimal transport
Brain-computer interfaces (BCIs) have surfaced as a powerful modality in human-machine
interaction and wearable technology with powered futuristic applications like virtual reality …
interaction and wearable technology with powered futuristic applications like virtual reality …
Combining brain-computer interfaces with deep reinforcement learning for robot training: a feasibility study in a simulation environment
M Vukelić, M Bui, A Vorreuther… - Frontiers in …, 2023 - frontiersin.org
Deep reinforcement learning (RL) is used as a strategy to teach robot agents how to
autonomously learn complex tasks. While sparsity is a natural way to define a reward in …
autonomously learn complex tasks. While sparsity is a natural way to define a reward in …