Biosignal-based human–machine interfaces for assistance and rehabilitation: A survey

D Esposito, J Centracchio, E Andreozzi, GD Gargiulo… - Sensors, 2021 - mdpi.com
As a definition, Human–Machine Interface (HMI) enables a person to interact with a device.
Starting from elementary equipment, the recent development of novel techniques and …

Modeling and control of robotic manipulators based on artificial neural networks: a review

Z Liu, K Peng, L Han, S Guan - Iranian Journal of Science and Technology …, 2023 - Springer
Recently, robotic manipulators have been playing an increasingly critical part in scientific
research and industrial applications. However, modeling of robotic manipulators is …

Feature and classification analysis for detection and classification of tongue movements from single-trial pre-movement EEG

RL Kæseler, TW Johansson… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
Individuals with severe tetraplegia can benefit from brain-computer interfaces (BCIs). While
most movement-related BCI systems focus on right/left hand and/or foot movements, very …

Design of room-temperature infrared photothermoelectric detectors based on CNT/PEDOT: PSS composites

J Wang, Z Xie, JA Liu, JTW Yeow - Journal of Materials Chemistry C, 2022 - pubs.rsc.org
Self-powered, flexible, and uncooled mid-wavelength infrared (MWIR) detectors based on
the photothermoelectric (PTE) mechanism are promising for the next-generation wearable …

The design of a neural network-based adaptive control method for robotic arm trajectory tracking

K Xu, Z Wang - Neural Computing and Applications, 2023 - Springer
With the in-depth development of high-tech industries, especially in the fields of production,
manufacturing, aviation, and medical care, most of the work needs to be accomplished with …

Human–machine interface: multiclass classification by machine learning on 1D EOG Signals for the Control of an Omnidirectional Robot

FD Pérez-Reynoso, L Rodríguez-Guerrero… - Sensors, 2021 - mdpi.com
People with severe disabilities require assistance to perform their routine activities; a Human–
Machine Interface (HMI) will allow them to activate devices that respond according to their …

EOG signal classification with wavelet and supervised learning algorithms KNN, SVM and DT

SN Hernández Pérez, FD Pérez Reynoso… - Sensors, 2023 - mdpi.com
The work carried out in this paper consists of the classification of the physiological signal
generated by eye movement called Electrooculography (EOG). The human eye performs …

Quantifying attention in children with intellectual and developmental disabilities through multicenter electrooculogram signal analysis

S Qi, S Zhang, L Lin, Y Li, J Chen, Y Ni, X Du… - Scientific Reports, 2024 - nature.com
In a multicenter case–control investigation, we assessed the efficacy of the
Electrooculogram Signal Analysis (EOG-SA) method, which integrates attention-related …

Multi-scale Inception-based Deep Fusion Network for electrooculogram-based eye movements classification

Z Zeng, L Tao, J Hu, R Su, L Meng, C Chen… - … Signal Processing and …, 2025 - Elsevier
Classifying eye movements accurately is essential for various practical applications.
However, eye movement classification (EMC) based on electrooculogram (EOG) is still …

[HTML][HTML] A scoping review of gaze and eye tracking-based control methods for assistive robotic arms

A Fischer-Janzen, TM Wendt… - Frontiers in Robotics and …, 2024 - frontiersin.org
Background: Assistive Robotic Arms are designed to assist physically disabled people with
daily activities. Existing joysticks and head controls are not applicable for severely disabled …