A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers
Brain signals refer to the biometric information collected from the human brain. The research
on brain signals aims to discover the underlying neurological or physical status of the …
on brain signals aims to discover the underlying neurological or physical status of the …
10 years of EPOC: A scoping review of Emotiv's portable EEG device
BACKGROUND Commercially-made low-cost electroencephalography (EEG) devices have
become increasingly available over the last decade. One of these devices, Emotiv EPOC, is …
become increasingly available over the last decade. One of these devices, Emotiv EPOC, is …
Cross-platform implementation of an SSVEP-based BCI for the control of a 6-DOF robotic arm
Robotics has been successfully applied in the design of collaborative robots for assistance
to people with motor disabilities. However, man-machine interaction is difficult for those who …
to people with motor disabilities. However, man-machine interaction is difficult for those who …
An eye tracking and brain–computer interface-based human–environment interactive system for amyotrophic lateral sclerosis patients
Amyotrophic lateral sclerosis (ALS) patients suffer a great inconvenience in their daily lives
due to the gradual loss of their motion abilities. In order to help ALS patients regain their self …
due to the gradual loss of their motion abilities. In order to help ALS patients regain their self …
An adaptive SSVEP-based brain-computer interface to compensate fatigue-induced decline of performance in practical application
Brain-computer interfaces based on steadystate visual evoked potentialsare promising
communication systems for people with speech and motor disabilities. However, reliable …
communication systems for people with speech and motor disabilities. However, reliable …
Mental fatigue level detection based on event related and visual evoked potentials features fusion in virtual indoor environment
The purpose of this work is to set up a model that can estimate the mental fatigue of users
based on the fusion of relevant features extracted from Positive 300 (P300) and steady state …
based on the fusion of relevant features extracted from Positive 300 (P300) and steady state …
Can I think of something else when using a BCI? Cognitive demand of an SSVEP-based BCI
BCIs are presumably supposed to require the full attention of their users and to lose
accuracy if they pay attention to another task. This assertion has been verified with several …
accuracy if they pay attention to another task. This assertion has been verified with several …
[图书][B] Deep Learning for EEG-Based Brain–Computer Interfaces: Representations, Algorithms and Applications
X Zhang, L Yao - 2021 - World Scientific
In this chapter, the foundations of deep learning models including concepts, architectures,
and techniques commonly used in the brain signal field will be formally introduced. Deep …
and techniques commonly used in the brain signal field will be formally introduced. Deep …
Influence of error rate on frustration of BCI users
Brain-Computer Interfaces (BCIs) are still much less reliable than other input devices. The
error rates of BCIs range from 5% up to 60%. In this paper, we assess the subjective …
error rates of BCIs range from 5% up to 60%. In this paper, we assess the subjective …
Effect of UX Design Guideline on the information accessibility for the visually impaired in the mobile health apps
WJ Kim, IK Kim, MJ Kim, E Lee - 2018 IEEE international …, 2018 - ieeexplore.ieee.org
WHO recommends that patient participation is a necessary to enhance patient-safety and
patient participation is only possible when patient are knowledgeable by accessing health …
patient participation is only possible when patient are knowledgeable by accessing health …