About this Research Topic
Brain-Computer Interfaces (BCIs) have become an increasingly popular research area in recent years due to their potential to help people with motor impairments. BCIs enable direct communication between the human brain and an external device, bypassing traditional motor pathways, and offering a new means for people to interact with their environment. BCIs can have an enormous impact on the lives of people with motor impairments, as they can help restore their ability to perform daily tasks, increase their independence, and improve their quality of life. Among the various applications of BCIs, movement control has emerged as one of the most promising ones. Movement control refers to the use of BCIs to control prosthetic limbs, exoskeletons, wheelchairs, or assistive devices, allowing users to perform a variety of tasks that were previously impossible. However, despite the progress made in this area, many challenges still need to be addressed to make BCI-based movement control systems more efficient, user-friendly, and accessible.
Motor impairments due to various neurological conditions such as stroke, spinal cord injury, and cerebral palsy significantly affect an individual's daily activities, independence, and quality of life. Traditional rehabilitation methods may not always be effective in restoring motor function in such individuals. Brain-computer interfaces (BCIs) provide a promising solution to this problem by enabling individuals to control external devices directly through their thoughts. However, despite the significant progress made in BCI technology, many challenges still need to be addressed to make BCI-based movement control systems more efficient, user-friendly, and accessible. These challenges include the development of more accurate and reliable signal processing techniques, the design of user-friendly and ergonomic BCI interfaces, and the optimization of training protocols for effective motor skill acquisition.
Please note that Frontiers in Neuroinformatics welcomes all articles related to exploring the development of more accurate and reliable signal processing techniques. All the articles focused on the design of user-friendly and ergonomic BCI interfaces and the optimization of training protocols for effective motor skill acquisition should be submitted through the Brain-Computer Interfaces section (Frontiers in Human Neuroscience).
This Research Topic aims to present the latest research on BCI for movement control, providing a comprehensive overview of the state-of-the-art in this field. The main objectives of this special issue are:
• To explore the current challenges and limitations of BCI-based movement control systems, and to propose solutions to overcome them. Articles to be submitted through the Brain-Computer Interfaces section (Frontiers in Human Neuroscience)
• To present the latest developments in BCI technology, such as new signal acquisition techniques, machine learning algorithms, and user interfaces. Articles to be submitted to Frontiers in Neuroinformatics
• To showcase successful applications of BCI-based movement control in various domains, including wheelchairs, prosthetics, exoskeletons, and assistive devices. Articles to be submitted through the Brain-Computer Interfaces section (Frontiers in Human Neuroscience)
Motor impairments due to various neurological conditions such as stroke, spinal cord injury, and cerebral palsy significantly affect an individual's daily activities, independence, and quality of life. Traditional rehabilitation methods may not always be effective in restoring motor function in such individuals. Brain-computer interfaces (BCIs) provide a promising solution to this problem by enabling individuals to control external devices directly through their thoughts. However, despite the significant progress made in BCI technology, many challenges still need to be addressed to make BCI-based movement control systems more efficient, user-friendly, and accessible. These challenges include the development of more accurate and reliable signal processing techniques, the design of user-friendly and ergonomic BCI interfaces, and the optimization of training protocols for effective motor skill acquisition.
Please note that Frontiers in Neuroinformatics welcomes all articles related to exploring the development of more accurate and reliable signal processing techniques. All the articles focused on the design of user-friendly and ergonomic BCI interfaces and the optimization of training protocols for effective motor skill acquisition should be submitted through the Brain-Computer Interfaces section (Frontiers in Human Neuroscience).
This Research Topic aims to present the latest research on BCI for movement control, providing a comprehensive overview of the state-of-the-art in this field. The main objectives of this special issue are:
• To explore the current challenges and limitations of BCI-based movement control systems, and to propose solutions to overcome them. Articles to be submitted through the Brain-Computer Interfaces section (Frontiers in Human Neuroscience)
• To present the latest developments in BCI technology, such as new signal acquisition techniques, machine learning algorithms, and user interfaces. Articles to be submitted to Frontiers in Neuroinformatics
• To showcase successful applications of BCI-based movement control in various domains, including wheelchairs, prosthetics, exoskeletons, and assistive devices. Articles to be submitted through the Brain-Computer Interfaces section (Frontiers in Human Neuroscience)
Keywords: Neuroplasticity, Motor impairment Assistive Devices, Wheelchair Prosthetics, Exoskeletons, Signal processing, Machine learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
