  Robotic-assisted medical systems (RAMS) have gained significant attention for
their advantages in alleviating surgeons' fatigue and improving patients'
outcomes. These systems comprise a range of human-computer interactions,
including medical scene monitoring, anatomical target planning, and robot
manipulation. However, despite its versatility and effectiveness, RAMS demands
expertise in robotics, leading to a high learning cost for the operator. In
this work, we introduce a novel framework using mixed reality technologies to
ease the use of RAMS. The proposed framework achieves real-time planning and
execution of medical instruments by providing 3D anatomical image overlay,
human-robot collision detection, and robot programming interface. These
features, integrated with an easy-to-use calibration method for head-mounted
display, improve the effectiveness of human-robot interactions. To assess the
feasibility of the framework, two medical applications are presented in this
work: 1) coil placement during transcranial magnetic stimulation and 2) drill
and injector device positioning during femoroplasty. Results from these use
cases demonstrate its potential to extend to a wider range of medical
scenarios.
