We have designed a remotely-controlled robot which equipped with a 360 degree full HD camera. User’s postures are detected by measuring the accelerationrotation of changes of limb postures using inertial measurement units (IMU). User’s motion commands are wirelessly transmitted to actuate the remote robot in accordance with user’s posture. The 360 degree full scene camera keeps transmitting the real-time situation of the scene surrounding the robot back to the user, displayed on the VR headset.

We have developed a movement assistive system using EEG-controlled functional electric stimulation system. Users’ movement intentions are recognized by brain computer interface, implemented by deep learning network,the detected users’ intentions are then translated into commands to trigger a functional electric stimulation (FES) device to activate users’ particular movements, such as grasping, hand raising, holding a cup, etc. In our study, we have designed our own wireless dry-electrode EEG systemour own FES system.