Biosignal-based human–machine interfaces for assistance and rehabilitation: A survey
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 …
Starting from elementary equipment, the recent development of novel techniques and …
Recent progress in wearable brain–computer interface (BCI) devices based on electroencephalogram (EEG) for medical applications: a review
J Zhang, J Li, Z Huang, D Huang, H Yu, Z Li - Health Data Science, 2023 - spj.science.org
Importance: Brain–computer interface (BCI) decodes and converts brain signals into
machine instructions to interoperate with the external world. However, limited by the …
machine instructions to interoperate with the external world. However, limited by the …
Synchronization in fractional-order neural networks by the energy balance strategy
Z Yao, K Sun, S He - Cognitive Neurodynamics, 2024 - Springer
Considering the individual differences between neurons, the fractional-order framework is
introduced, and the neurons with various orders denote the individual differences during the …
introduced, and the neurons with various orders denote the individual differences during the …
Eye-Gaze controlled wheelchair based on deep learning
J Xu, Z Huang, L Liu, X Li, K Wei - Sensors, 2023 - mdpi.com
In this paper, we design a technologically intelligent wheelchair with eye-movement control
for patients with ALS in a natural environment. The system consists of an electric wheelchair …
for patients with ALS in a natural environment. The system consists of an electric wheelchair …
Eye-movement-controlled wheelchair based on flexible hydrogel biosensor and wt-svm
X Wang, Y Xiao, F Deng, Y Chen, H Zhang - Biosensors, 2021 - mdpi.com
To assist patients with restricted mobility to control wheelchair freely, this paper presents an
eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and …
eye-movement-controlled wheelchair prototype based on a flexible hydrogel biosensor and …
BCI wheelchair control using expert system classifying EEG signals based on power spectrum estimation and nervous tics detection
D Pawuś, S Paszkiel - Applied Sciences, 2022 - mdpi.com
The constantly developing biomedical engineering field and newer and more advanced BCI
(brain–computer interface) systems require their designers to constantly develop and search …
(brain–computer interface) systems require their designers to constantly develop and search …
The application of integration of EEG signals for authorial classification algorithms in implementation for a mobile robot control using movement imagery—Pilot study
D Pawuś, S Paszkiel - Applied Sciences, 2022 - mdpi.com
This paper presents a new approach to the issue of recognition and classification of
electroencephalographic signals (EEG). A small number of investigations using the Emotiv …
electroencephalographic signals (EEG). A small number of investigations using the Emotiv …
Application of EEG signals integration to proprietary classification algorithms in the implementation of mobile robot control with the use of motor imagery supported by …
D Pawuś, S Paszkiel - Applied Sciences, 2022 - mdpi.com
This article is a continuation and extension of research on a new approach to the
classification and recognition of EEG signals. Their goal is to control the mobile robot …
classification and recognition of EEG signals. Their goal is to control the mobile robot …
Vision-Based Eye Image Classification for Ophthalmic Measurement Systems
The accuracy and the overall performances of ophthalmic instrumentation, where specific
analysis of eye images is involved, can be negatively influenced by invalid or incorrect …
analysis of eye images is involved, can be negatively influenced by invalid or incorrect …
Assessment of Model Accuracy in Eyes Open and Closed EEG Data: Effect of Data Pre-Processing and Validation Methods
Eyes open and eyes closed data is often used to validate novel human brain activity
classification methods. The cross-validation of models trained on minimally preprocessed …
classification methods. The cross-validation of models trained on minimally preprocessed …