Noninvasive electroencephalography equipment for assistive, adaptive, and rehabilitative brain–computer interfaces: a systematic literature review

N Jamil, AN Belkacem, S Ouhbi, A Lakas - Sensors, 2021 - mdpi.com
Humans interact with computers through various devices. Such interactions may not require
any physical movement, thus aiding people with severe motor disabilities in communicating …

Classifying human emotions in HRI: applying global optimization model to EEG brain signals

M Staffa, L D'Errico, S Sansalone… - Frontiers in …, 2023 - frontiersin.org
Significant efforts have been made in the past decade to humanize both the form and
function of social robots to increase their acceptance among humans. To this end, social …

Enhancing affective robotics via human internal state monitoring

M Staffa, S Rossi - 2022 31st IEEE International Conference on …, 2022 - ieeexplore.ieee.org
During the last years, many solutions have been proposed to achieve a natural Human-
Robot Interaction (HRI) and Communication paving the way to new paradigms of under …

Development and testing of a virtual simulator for a myoelectric prosthesis prototype–the prisma hand ii–to improve its usability and acceptability

A Leccia, M Sallam, S Grazioso, T Caporaso… - … Applications of Artificial …, 2023 - Elsevier
Artificial limbs can help people missing body parts to restore some of their daily-life activities.
However, the user should spend up to a few months to intuitively control the new device …

MST-DGCN: A Multi-Scale Spatio-Temporal and Dynamic Graph Convolution Fusion Network for Electroencephalogram Recognition of Motor Imagery

Y Chen, P Liu, D Li - Electronics, 2024 - mdpi.com
The motor imagery brain-computer interface (MI-BCI) has the ability to use
electroencephalogram (EEG) signals to control and communicate with external devices. By …

Portable Fabric-Based Soft Glove Controlled with Single-Channel Electroencephalography

JD Setiawan, M Ariyanto, FT Putri… - Journal of Robotics …, 2024 - journal.umy.ac.id
Brain-computer interface (BCI) has been widely used to capture electrical signals generated
from the brain. One of the most commonly used methods in the BCI system is the …

[PDF][PDF] EEG-based brain computer interface prosthetic hand using Raspberry Pi 4

HA Ali, D Popescu, A Hadar, A Vasilateanu… - International Journal of …, 2021 - academia.edu
Accidents, wars, or different diseases can affect upper limbs in such a manner so their
amputation is required, with dramatic effects on people's ability to perform tasks such as …

Enhancing Tire Condition Monitoring through Weightless Neural Networks Using MEMS‐Based Vibration Signals

S Arora, S Naveen Venkatesh… - Journal of …, 2024 - Wiley Online Library
Tire pressure monitoring system (TPMS) has a critical role in safeguarding vehicle safety by
monitoring tire pressure levels. Keeping the accurate tire pressure is necessary for …

A 3D-CNNs Approach to Classify Users' Emotion through EEG-based Topographical Maps in HRI

L D'Errico, E Di Nardo, A Ciaramella… - Companion of the 2024 …, 2024 - dl.acm.org
Recent research has demonstrated the use of socially assistive robotics (SAR) in a variety of
operational contexts where facilitating human-robot interaction and building rapport depend …

Analyzing data augmentation methods for convolutional neural network-based brain-computer interfaces

G Faria, GH de Souza, H Bernardino… - … Joint Conference on …, 2022 - ieeexplore.ieee.org
Brain-computer interfaces (BCI) are systems that use brain signals to communicate with and
control devices, with applications ranging over multiple domains. In healthcare, one of the …