Recently, Neuro-Robots that utilize the Neural-Machine Interface (NMI) technique have demonstrated their potential impact on multiple areas, such as assistive and rehabilitative devices for individuals with motor dysfunction, Telerobotics, and good Human robot interaction with prosthetics.
Typically, human movement intentions are decoded from neurophysiological signals such as the ElectroEncephaloGram (EEG), the ElectroCardioGram (ECG), the ElectroMyoGram (EMG), the functional Near InfraRed Spectroscopy (fNIRS) and the Force-Sensing Resistor (FSR) and then translated into the control command of the device, exoskeleton, prosthesis or tele-controlled robot.
In order to realize the intuitive and precise control of Neuro-Robots, efforts have been predominantly made in investigating the feasibility and validity of integrating the haptic feedback to construct a close-loop system, mainly referring to the control mechanism of human limbs, for example, the hand with tactile sensing to adjust force output when grasping different objects. Several works have already shown the feasibility of improving the control intuitiveness and precision of Neuro-Robots by inducing haptic feedback with peripheral nerve electrical stimulation and other physical/mechanical forms of stimulation. However, how to provide accurate haptic sensing and vivid haptic feedback without excessively increasing system complexity and cost is still an important question that needs to be answered.
From a different perspective, the Neuro-Robots community is also exploring novel algorithms to increase the robustness and the reliability of decoding the human end-user’s intentions. However, despite the great progress, the performance of the movement intention decoding still needs to be improved, especially considering the accuracy of decoding in the typical case of complex dexterous movements which are performed in daily life.
This Research Topic seeks original contributions that take into account all the cross-cutting aspects in haptic feedback for NMI-based neurorobotics research. We welcome the submissions in form of Original Research, Review, Systematic Review, Brief Research Report, Case Report, and Clinical Trial. Topics of interest include but are not limited to:
• Novel experimental designs, clinical protocols, and applications involving haptic feedback and neural decoding
• New techniques to induce tactile sensing for Neuro-Robotics control
• Novel modalities of haptic feedback for neurorobotics
• Control strategies for the Neuro-Robotics with haptic feedback
• Bidirectional neural prosthesis
• Novel neural decoding methods based on EEG/EMG, fNIRS, FSR et.al.
• Evaluation of haptic feedback for Neuro-Robotics in real-world scenarios
• EMG prosthetics
• Low energy-consumption hardware and mobile computing technology for NMI
Recently, Neuro-Robots that utilize the Neural-Machine Interface (NMI) technique have demonstrated their potential impact on multiple areas, such as assistive and rehabilitative devices for individuals with motor dysfunction, Telerobotics, and good Human robot interaction with prosthetics.
Typically, human movement intentions are decoded from neurophysiological signals such as the ElectroEncephaloGram (EEG), the ElectroCardioGram (ECG), the ElectroMyoGram (EMG), the functional Near InfraRed Spectroscopy (fNIRS) and the Force-Sensing Resistor (FSR) and then translated into the control command of the device, exoskeleton, prosthesis or tele-controlled robot.
In order to realize the intuitive and precise control of Neuro-Robots, efforts have been predominantly made in investigating the feasibility and validity of integrating the haptic feedback to construct a close-loop system, mainly referring to the control mechanism of human limbs, for example, the hand with tactile sensing to adjust force output when grasping different objects. Several works have already shown the feasibility of improving the control intuitiveness and precision of Neuro-Robots by inducing haptic feedback with peripheral nerve electrical stimulation and other physical/mechanical forms of stimulation. However, how to provide accurate haptic sensing and vivid haptic feedback without excessively increasing system complexity and cost is still an important question that needs to be answered.
From a different perspective, the Neuro-Robots community is also exploring novel algorithms to increase the robustness and the reliability of decoding the human end-user’s intentions. However, despite the great progress, the performance of the movement intention decoding still needs to be improved, especially considering the accuracy of decoding in the typical case of complex dexterous movements which are performed in daily life.
This Research Topic seeks original contributions that take into account all the cross-cutting aspects in haptic feedback for NMI-based neurorobotics research. We welcome the submissions in form of Original Research, Review, Systematic Review, Brief Research Report, Case Report, and Clinical Trial. Topics of interest include but are not limited to:
• Novel experimental designs, clinical protocols, and applications involving haptic feedback and neural decoding
• New techniques to induce tactile sensing for Neuro-Robotics control
• Novel modalities of haptic feedback for neurorobotics
• Control strategies for the Neuro-Robotics with haptic feedback
• Bidirectional neural prosthesis
• Novel neural decoding methods based on EEG/EMG, fNIRS, FSR et.al.
• Evaluation of haptic feedback for Neuro-Robotics in real-world scenarios
• EMG prosthetics
• Low energy-consumption hardware and mobile computing technology for NMI
