A review on the computational methods for emotional state estimation from the human EEG

MK Kim, M Kim, E Oh, SP Kim - … and mathematical methods in …, 2013 - Wiley Online Library
A growing number of affective computing researches recently developed a computer system
that can recognize an emotional state of the human user to establish affective human …

Kernel methods on spike train space for neuroscience: a tutorial

IM Park, S Seth, ARC Paiva, L Li… - IEEE Signal Processing …, 2013 - ieeexplore.ieee.org
Over the last decade, several positive-definite kernels have been proposed to treat spike
trains as objects in Hilbert space. However, for the most part, such attempts still remain a …

Point-process nonlinear models with laguerre and volterra expansions: Instantaneous assessment of heartbeat dynamics

G Valenza, L Citi, EP Scilingo… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
In the last decades, mathematical modeling and signal processing techniques have played
an important role in the study of cardiovascular control physiology and heartbeat nonlinear …

Neural control of a tracking task via attention-gated reinforcement learning for brain-machine interfaces

Y Wang, F Wang, K Xu, Q Zhang… - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn
from the environment through interactions to complete the task without desired signals …

Quantized attention-gated kernel reinforcement learning for brain–machine interface decoding

F Wang, Y Wang, K Xu, H Li, Y Liao… - IEEE transactions on …, 2015 - ieeexplore.ieee.org
Reinforcement learning (RL)-based decoders in brain-machine interfaces (BMIs) interpret
dynamic neural activity without patients' real limb movements. In conventional RL, the goal …

New perspectives on neuroengineering and neurotechnologies: NSF-DFG workshop report

CT Moritz, P Ruther, S Goering, A Stett… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
Goal: To identify and overcome barriers to creating new neurotechnologies capable of
restoring both motor and sensory function in individuals with neurological conditions …

Binless kernel machine: Modeling spike train transformation for cognitive neural prostheses

C Qian, X Sun, Y Wang, X Zheng, Y Wang… - Neural Computation, 2020 - direct.mit.edu
Modeling spike train transformation among brain regions helps in designing a cognitive
neural prosthesis that restores lost cognitive functions. Various methods analyze the …

Computational approaches to decode grasping force and velocity level in upper-limb amputee from intraneural peripheral signals

M Cracchiolo, A Panarese, G Valle… - Journal of Neural …, 2021 - iopscience.iop.org
Objective. Recent results have shown the potentials of neural interfaces to provide sensory
feedback to subjects with limb amputation increasing prosthesis usability. However, their …

Tracking fast neural adaptation by globally adaptive point process estimation for brain-machine interface

S Chen, X Zhang, X Shen, Y Huang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Brain-machine interfaces (BMIs) help the disabled restore body functions by translating
neural activity into digital commands to control external devices. Neural adaptation, where …

Nonlinear modeling of neural interaction for spike prediction using the staged point-process model

C Qian, X Sun, S Zhang, D Xing, H Li, X Zheng… - Neural …, 2018 - direct.mit.edu
Neurons communicate nonlinearly through spike activities. Generalized linear models
(GLMs) describe spike activities with a cascade of a linear combination across inputs, a …