Passive brain-computer interfaces for enhanced human-robot interaction
M Alimardani, K Hiraki - Frontiers in Robotics and AI, 2020 - frontiersin.org
Brain-computer interfaces (BCIs) have long been seen as control interfaces that translate
changes in brain activity, produced either by means of a volitional modulation or in response …
changes in brain activity, produced either by means of a volitional modulation or in response …
[图书][B] Brain–computer interfaces handbook: technological and theoretical advances
Brain–Computer Interfaces Handbook: Technological and Theoretical Advances provides a
tutorial and an overview of the rich and multi-faceted world of Brain–Computer Interfaces …
tutorial and an overview of the rich and multi-faceted world of Brain–Computer Interfaces …
[HTML][HTML] Intrinsic interactive reinforcement learning–Using error-related potentials for real world human-robot interaction
Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in
dynamic environments based on feedback. Explicit human feedback during robot RL is …
dynamic environments based on feedback. Explicit human feedback during robot RL is …
EEG and EMG dataset for the detection of errors introduced by an active orthosis device
Exoskeletons and orthoses are frequently used to facilitate limb movements in humans with
motor impairments as they can integrate classical therapy approaches such as mirror …
motor impairments as they can integrate classical therapy approaches such as mirror …
[HTML][HTML] A survey on design and control of lower extremity exoskeletons for bipedal walking
Exoskeleton robots are electrically, pneumatically, or hydraulically actuated devices that
externally support the bones and cartilage of the human body while trying to mimic the …
externally support the bones and cartilage of the human body while trying to mimic the …
Teleoperated mobile robot with two arms: the influence of a human-machine interface, VR training and operator age
A Grabowski, J Jankowski, M Wodzyński - International Journal of Human …, 2021 - Elsevier
The article presents a method of supporting work by using virtual reality techniques to
control a two-armed mobile robot's movement. The robot developed for the study can carry a …
control a two-armed mobile robot's movement. The robot developed for the study can carry a …
Rotational data augmentation for electroencephalographic data
Motivation: For deep learning on image data, a common approach is to augment the training
data by artificial new images, using techniques like moving windows, scaling, affine …
data by artificial new images, using techniques like moving windows, scaling, affine …
An adaptive spatial filter for user-independent single trial detection of event-related potentials
Goal: Current brain-computer interfaces (BCIs) are usually based on various, often
supervised, signal processing methods. The disadvantage of supervised methods is the …
supervised, signal processing methods. The disadvantage of supervised methods is the …
Embedded multimodal interfaces in robotics: applications, future trends, and societal implications
In the past, robots were primarily used to perform work that was either too hard, too
dangerous or simply too repetitive for humans, eg, assembly line work, or work that could be …
dangerous or simply too repetitive for humans, eg, assembly line work, or work that could be …
A hybrid FPGA-based system for EEG-and EMG-based online movement prediction
A current trend in the development of assistive devices for rehabilitation, for example
exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality …
exoskeletons or active orthoses, is to utilize physiological data to enhance their functionality …