Recent research suggests that brain-computer interfaces may have a potential impact on the reconstruction of upper limb function. However, grasping objects is a complex task, and the signals extracted from the brain do not stably drive these external devices. A visually guided auxiliary robotic device can improve the performance of the brain-computer interface system.
Dr. Downey from the University of Pittsburgh in the United States has a control method that is mainly used to control upper limb prostheses using a brain-computer interface system and to receive hand-assisted positioning information when the upper limb prosthesis is adequate. Their research is published in J Neuroeng Rehabil's March 2016 online journal.
The investigators included 2 patients with quadriplegia who could use the robotic arm to perform the task of object delivery. The main purpose of designing a shared control system is to establish a balance between brain-computer interface system drive intent and computer aid. The automated robotic gripping system identifies and tracks objects and defines a stable grip position. The system can determine when a user intends to take advantage of a robotic arm based on a brain-computer interface system. The application sharing control system, based on brain-computer interface actions and autonomous grip commands, can be combined to ensure accurate gripping.
For the two subjects included in the study, the shared control system was better able to accomplish the above tasks than when using the brain-computer interface system alone to complete the object delivery task. When using a shared control system, the completion of object delivery tasks is more accurate, more efficient, and less difficult. One subject attempted to complete the gripping task in two objects at similar distances with a success rate of 92%, which confirms that the user can accurately achieve his or her intention when applying the shared control system.
Operation mode diagram of shared control system
The results of this study indicate that combining brain-computer interface systems with vision-guided robotic assistance systems can effectively improve the completion of object delivery tasks. For the user, if the brain-computer interface system can provide auxiliary support while maintaining its universality, the system will be more popular with users.
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