Stroke is an acute cerebrovascular disease in which sudden interruption of blood supply to the brain or rupture of cerebral blood vessels cause damage to brain cells and consequently impair the patient's motor and cognitive abilities. A novel rehabilitation training model integrating brain-computer interface (BCI) and virtual reality (VR) not only promotes the functional activation of brain networks, but also provides immersive and interesting contextual feedback for patients. In this paper, we designed a hand rehabilitation training system integrating multi-sensory stimulation feedback, BCI and VR, which guides patients' motor imaginations through the tasks of the virtual scene, acquires patients' motor intentions, and then carries out human-computer interactions under the virtual scene. At the same time, haptic feedback is incorporated to further increase the patients' proprioceptive sensations, so as to realize the hand function rehabilitation training based on the multi-sensory stimulation feedback of vision, hearing, and haptic senses. In this study, we compared and analyzed the differences in power spectral density of different frequency bands within the EEG signal data before and after the incorporation of haptic feedback, and found that the motor brain area was significantly activated after the incorporation of haptic feedback, and the power spectral density of the motor brain area was significantly increased in the high gamma frequency band. The results of this study indicate that the rehabilitation training of patients with the VR-BCI hand function enhancement rehabilitation system incorporating multi-sensory stimulation can accelerate the two-way facilitation of sensory and motor conduction pathways, thus accelerating the rehabilitation process.
The master manipulator is a crucial component in enabling interactive perception between the physician and the guidewire/catheter; however, the lack of real-time haptic feedback increases the difficulty of hand–eye coordination. This paper designed and developed a master manipulator for a vascular interventional surgery robot with haptic feedback to provide the physician with high-accuracy force feedback. Using a two-degree-of-freedom decoupling mechanism combining key transmission and bearings, the master manipulator captured the physician’s push–pull and rotational actions accurately and synchronously. The haptic feedback module adopted dual-channel independent control: axial resistance was generated by three springs evenly distributed at 120° and driven by a linear motor, while circumferential resistance was produced directly by a brushed direct current motor. To enhance the fidelity and accuracy of force feedback, inherent friction within the mechanical structure was identified as a critical non-negligible factor. Consequently, a feedforward compensation strategy grounded in the Stribeck friction model was developed and implemented to proactively counteract friction forces. The performance of the axial force module and the circumferential torque module was evaluated, and the displacement acquisition resolutions reached 1 μm and 0.087 9°, respectively. The average error for axial force feedback was 0.11 N, and that for circumferential torque feedback was 0.154 mN·m. The master manipulator was constructed using a combination of custom 3D-printed photosensitive resin parts and machined aluminum alloy, resulting in a lightweight, low-friction structure. It provides an immersive force-interaction experience for the physician, improving operational precision and radiation safety in vascular interventional surgery and enabling coordinated “vision–hand–force perception”.
