Recent advances in non-invasive Brain-Machine Interfaces (BMIs) have demonstrated the potential impact of the technology. The ultimate translational goal of BMI systems is to enable people suffering from severe motor disabilities to control a new generation of neuroprostheses and, thus, (re)gain their own independence.
Several works have already shown the feasibility of BMI technology with different kinds of assistive devices, designed to restore communication (e.g., virtual keyboard) or to enable the control of robotic applications (e.g., wheelchairs, telepresence robots, robotic arms and drones). However, despite the great progress, the integration between BMI and robotics is still in its infancy and translational impact is low.
The BMI community has predominantly focused on exploring novel algorithms to decode a BMI user’s intentions from neural patterns with a focus on enhancing the robustness and the reliability of the BMI system. However, the process of how the estimated intentions of the user are translated by the intelligent robotic device into real and daily-based situations is often neglected. This largely affects the translational impact of the BMI technology. The latest advances in the field of robotics may help to address this challenge by exploiting novel human-robot interaction theories as well as by providing insights and solutions from a new and different perspective.
This call seeks original contributions that explicitly take into account all the cross-cutting aspects in BMIs and robotics research. We welcome methodological papers, review and theoretical articles. All typologies of closed-loop BMI systems (e.g., based on exogenous stimulation or self-paced paradigms) are welcome as long as they are focused on the integration of BMI and robotics devices.
Topics of interest include but are not limited to:
- BMI control of navigation robots
- BMI control of robotic prosthetic limbs
- BMI driven assistive technology for end-users
- Translational aspects in BMI controlled devices
- Shared-control strategies for BMI
- Contextualized robotic behaviors
- Long-term human-robot interaction (BMI-robot interaction)
- Semi-autonomous robot behaviors
- Evaluation of BMI driven robotics in real world scenarios
- Real-time detection of possible targets in real world scenarios
Recent advances in non-invasive Brain-Machine Interfaces (BMIs) have demonstrated the potential impact of the technology. The ultimate translational goal of BMI systems is to enable people suffering from severe motor disabilities to control a new generation of neuroprostheses and, thus, (re)gain their own independence.
Several works have already shown the feasibility of BMI technology with different kinds of assistive devices, designed to restore communication (e.g., virtual keyboard) or to enable the control of robotic applications (e.g., wheelchairs, telepresence robots, robotic arms and drones). However, despite the great progress, the integration between BMI and robotics is still in its infancy and translational impact is low.
The BMI community has predominantly focused on exploring novel algorithms to decode a BMI user’s intentions from neural patterns with a focus on enhancing the robustness and the reliability of the BMI system. However, the process of how the estimated intentions of the user are translated by the intelligent robotic device into real and daily-based situations is often neglected. This largely affects the translational impact of the BMI technology. The latest advances in the field of robotics may help to address this challenge by exploiting novel human-robot interaction theories as well as by providing insights and solutions from a new and different perspective.
This call seeks original contributions that explicitly take into account all the cross-cutting aspects in BMIs and robotics research. We welcome methodological papers, review and theoretical articles. All typologies of closed-loop BMI systems (e.g., based on exogenous stimulation or self-paced paradigms) are welcome as long as they are focused on the integration of BMI and robotics devices.
Topics of interest include but are not limited to:
- BMI control of navigation robots
- BMI control of robotic prosthetic limbs
- BMI driven assistive technology for end-users
- Translational aspects in BMI controlled devices
- Shared-control strategies for BMI
- Contextualized robotic behaviors
- Long-term human-robot interaction (BMI-robot interaction)
- Semi-autonomous robot behaviors
- Evaluation of BMI driven robotics in real world scenarios
- Real-time detection of possible targets in real world scenarios
