Hybrid Human-Machine Interfaces for Robot-Aided Rehabilitation and Assistance
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: closed (20 May 2023) | Viewed by 3208
Special Issue Editors
Interests: computational neuroscience; cognitive, affective, and behavioral neuroscience; circuits and cellular neuroscience; multimodal neuroimaging and analysis methods
Special Issue Information
Dear Colleagues,
An extensive body literature has demonstrated the benefits of using advanced robots for mediating rehabilitation therapy. Some of these robotic devices also have the potential for use at home by patients to provide daily assistance. In the last few years, a greater interest has been shown in interfacing the patient to these devices by means of neurophysiological signals extracted at different levels of the neuromuscular system. Brain-machine interfaces (BMIs) are especially of interest as they do not require any movement or muscular activity; however, their use in clinical practice is limited due to their low accuracy and reliability. Myoelectric systems provide more reliable control, but they can be unfeasible for people with severe disability. Following recent attempts to overcome these limitations, hybrid human-machine interface (h-HMI) technologies have been proposed to provide a more robust input to robotic devices and to extend their use to a wider population of patients. This call seeks original manuscripts describing new research in the field of h-HMIs for the control of rehabilitation or assistive devices. Papers should include at least one (neuro)physiological interface in their hybrid approach. All categories of medical devices—robotic (e.g., end-effector robots, exoskeletons) or non-robotic (e.g., electrical stimulations)—are welcome. Methodological papers, reviews, and theoretical contributions are also welcome.
Dr. Luca Tonin
Dr. Stefano Tortora
Guest Editors
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Keywords
- hybrid human-machine interface
- brain-machine interface
- electroencephalography
- electromyography
- electro-oculography
- rehabilitation robotics
- assistive robotics
- neurofeedback
- functional electrical stimulation
- multimodal classification
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