About this Research Topic
Neurotechnology, particularly through Brain-Computer Interface (BCI) systems, is revolutionizing the realm of robotics and artificial intelligence. This sophisticated interface between the human brain and machines harnesses technologies like fMRI, EEG, and EMG, converting brain signals into commands that direct robotic actions. The precision of signal decoding is critical, dictating the responsiveness of the system and ultimately determining the effectiveness of these interactions. As industries such as healthcare and automation increasingly adopt these technologies, there is a pressing need to address the technical challenges and explore new possibilities for their application.
This Research Topic aims to delve into the synergy between various BCI modalities like fMRI, EEG, EMG, and wearable sensors with robotic technology to push the boundaries of human-machine collaboration. The focus is on developing non-invasive, neuroimaging BCI systems that enable more natural, intuitive interactions with robots and AI. Through exploring innovative approaches and leveraging the strengths of these combined technologies, the goal is to enhance cognition recognition, streamline BCI setups for real-time application, and ultimately improve the dynamics of human-robot interaction.
To gather further insights within this innovative realm, we welcome articles addressing, but not limited to, the following themes:
- Effective integration of single and multi-modality BCI systems
- Challenges in real-time data processing and feedback mechanisms
- Design strategies for autonomous robotic behaviors that interact seamlessly with human operators
- Applications of BCI-driven robotics in sectors like healthcare and industrial automation
- Novel non-invasive techniques for better user engagement and control fidelity.
This Research Topic aims to delve into the synergy between various BCI modalities like fMRI, EEG, EMG, and wearable sensors with robotic technology to push the boundaries of human-machine collaboration. The focus is on developing non-invasive, neuroimaging BCI systems that enable more natural, intuitive interactions with robots and AI. Through exploring innovative approaches and leveraging the strengths of these combined technologies, the goal is to enhance cognition recognition, streamline BCI setups for real-time application, and ultimately improve the dynamics of human-robot interaction.
To gather further insights within this innovative realm, we welcome articles addressing, but not limited to, the following themes:
- Effective integration of single and multi-modality BCI systems
- Challenges in real-time data processing and feedback mechanisms
- Design strategies for autonomous robotic behaviors that interact seamlessly with human operators
- Applications of BCI-driven robotics in sectors like healthcare and industrial automation
- Novel non-invasive techniques for better user engagement and control fidelity.
Keywords: Brain-computer interface BCI, human machine collaboration, fMRI, EEG, fNIRS, EMG, hybrid-BCI, HCI, HMI, robotics, artificial intelligence, machine learning, deep learning, rehabilitation, assistive devices, exoskeletons, prosthetic, prosthesis, neurorobotics
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.
