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The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities. Although there are a few examples of exoskeletons, they need manual operations due to the…
Non-invasive brain-computer interface (BCI) has been developed for understanding users' intentions by using electroencephalogram (EEG) signals. With the recent development of artificial intelligence, there have been many developments in the…
The loss of limb motion arising from damage to the spinal cord is a disability that could effect people while performing their day-to-day activities. The restoration of limb movement would enable people with spinal cord injury to interact…
The paper presents a study of two novel visual motion onset stimulus-based brain-computer interfaces (vmoBCI). Two settings are compared with afferent and efferent to a computer screen center motion patterns. Online vmoBCI experiments are…
This paper presents an Artificial Intelligence (AI) integrated approach to Brain-Computer Interface (BCI)-based wheelchair development, utilizing a motor imagery right-left-hand movement mechanism for control. The system is designed to…
This study presents a multi-modal mechanism for recognizing human intentions while diving underwater, aiming to achieve natural human-robot interactions through an underwater superlimb for diving assistance. The underwater environment…
Efficient control of prosthetic limbs via non-invasive brain-computer interfaces (BCIs) requires advanced EEG processing, including pre-filtering, feature extraction, and action prediction, performed in real time on edge AI hardware.…
Decoding multiple movements from the same limb using electroencephalographic (EEG) activity is a key challenge with applications for controlling prostheses in upper-limb amputees. This study investigates the classification of four hand…
Employing skin-like tactile sensors on robots enhances both the safety and usability of collaborative robots by adding the capability to detect human contact. Unfortunately, simple binary tactile sensors alone cannot determine the context…
A scalp-recording electroencephalography (EEG)-based brain-computer interface (BCI) system can greatly improve the quality of life for people who suffer from motor disabilities. Deep neural networks consisting of multiple convolutional,…
One of the current issues in Brain-Computer Interface is how to deal with noisy Electroencephalography measurements organized as multidimensional datasets. On the other hand, recently, significant advances have been made in multidimensional…
Brain-computer interface (BCI) technology enables direct communication between the brain and external devices, allowing individuals to control their environment using brain signals. However, existing BCI approaches face three critical…
Based on recent health statistics, there are several thousands of people with limb disability and gait disorders that require a medical assistance. A robot assisted rehabilitation therapy can help them recover and return to a normal life.…
For machines to effectively assist humans in challenging visual search tasks, they must differentiate whether a human is simply glancing into a scene (navigational intent) or searching for a target object (informational intent). Previous…
Classification of EEG-based motor imagery (MI) is a crucial non-invasive application in brain-computer interface (BCI) research. This paper proposes a novel convolutional neural network (CNN) architecture for accurate and robust EEG-based…
This study describes and evaluates i-GRIP, a novel movement intention estimator designed to facilitate the control of assistive devices for grasping tasks in individuals with upper limb impairments. Operating within a collaborative grasping…
The Brain-Computer Interface system is a profoundly developing area of experimentation for Motor activities which plays vital role in decoding cognitive activities. Classification of Cognitive-Motor Imagery activities from EEG signals is a…
Brain-Computer Interfaces (BCIs) enable converting the brain electrical activity of an interface user to the user commands. BCI research studies demonstrated encouraging results in different areas such as neurorehabilitation, control of…
The integration of brain-computer interfaces (BCIs) into the realm of smart wheelchair (SW) technology signifies a notable leap forward in enhancing the mobility and autonomy of individuals with physical disabilities. BCIs are a technology…
Mindfulness is the state of paying attention to the present moment on purpose and meditation is the technique to obtain this state. This study aims to develop a robot assistant that facilitates mindfulness training by means of a Brain…