Advanced human-machine interfaces render robotic devices applicable to study and enhance human cognition. This turns robots into formidable neuroscientific tools to study processes such as the adaptation between a human operator and the operated robotic device and how this adaptation modulates human embodiment and embodied cognition. We analyze bidirectional human-machine interface (bHMI) technologies for transparent information transfer between a human and a robot via efferent and afferent channels. Even if such interfaces have a tremendous positive impact on feedback loops and embodiment, advanced bHMIs face immense technological challenges. We critically discuss existing technical approaches, mainly focusing on haptics, and suggest extensions thereof, which include other aspects of touch. Moreover, we point out other potential constraints such as limited functionality, semi-autonomy, intent-detection, and feedback methods. From this, we develop a research roadmap to guide understanding and development of bidirectional human-machine interfaces that enable robotic experiments to empirically study the human mind and embodiment. We conclude the integration of dexterous control and multisensory feedback to be a promising roadmap towards future robotic interfaces, especially regarding applications in the cognitive sciences. This article is categorized under: Computer Science > Robotics Psychology > Motor Skill and Performance Neuroscience > Plasticity.
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http://dx.doi.org/10.1002/wcs.1486 | DOI Listing |
Adv Mater
March 2025
Department of Biomedical Engineering, Guangdong Provincial Key Laboratory of Advanced Biomaterials, Institute of Innovative Materials, Southern University of Science and Technology, Shenzhen, 518055, P. R. China.
The effective and precise processing of visual information by the human eye primarily relies on the diverse contrasting functions achieved through synaptic regulation of ion transport in the retina. Developing a bio-inspired retina that uses ions as information carriers can more accurately replicate retina's natural signal processing capabilities, enabling high-performance machine vision. Herein, an ion-confined transport strategy is proposed to construct a bio-inspired retina by developing artificial synapses with inhibitory and excitatory contrasting functions.
View Article and Find Full Text PDFFront Robot AI
February 2025
Neuroinformatics and Cognitive Robotics Lab, Department of Computer Science and Automation, Institute for Technical Informatics and Engineering Informatics, Technische Universität Ilmenau, Ilmenau, Germany.
Mobile service robots for transportation tasks are usually restricted to a barrier-free environment where they can navigate freely. To enable the use of such assistive robots in existing buildings, the robot should be able to overcome closed doors independently and operate elevators with the interface designed for humans while being polite to passers-by. The integration of these required capabilities in an autonomous mobile service robot is explained using the example of a SCITOS G5 robot equipped with differential drive and a Kinova Gen II arm with 7 DoF.
View Article and Find Full Text PDFSci Rep
March 2025
Institute of Robotics and Mechatronics, German Aerospace Center (DLR), Oberpfaffenhofen, Wessling, 82234, Germany.
Mobile manipulation aids aim at enabling people with motor impairments to physically interact with their environment. To facilitate the operation of such systems, a variety of components, such as suitable user interfaces and intuitive control of the system, play a crucial role. In this article, we validate our highly integrated assistive robot EDAN, operated by an interface based on bioelectrical signals, combined with shared control and a whole-body coordination of the entire system, through a case study involving people with motor impairments to accomplish real-world activities.
View Article and Find Full Text PDFStroke is a leading cause of disability worldwide, driving the need for advanced rehabilitation strategies. The integration of Artificial Intelligence (AI) into stroke rehabilitation presents significant advancements across the continuum of care, from acute diagnosis to long-term recovery. This review explores AI's role in stroke rehabilitation, highlighting its impact on early diagnosis, motor recovery, and cognitive rehabilitation.
View Article and Find Full Text PDFACS Appl Mater Interfaces
March 2025
AECC Hunan Aviation Powerplant Research Institute, Zhuzhou, Hunan 412000, China.
Achieving large-scale and facile manufacturing for diverse small-scale robots is critical in the field of small-scale robots. At present, conventional manufacturing methods have limitations in terms of efficiency, environmental friendliness, and operability. In particular, it is difficult to facilely process multiform small-scale robots through a single processing technology only.
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