Studies of the human brain during natural activities, such as locomotion,
would benefit from the ability to image deep brain structures during these
activities. While Positron Emission Tomography (PET) can image these
structures, the bulk and weight of current scanners are not compatible with the
desire for a wearable device. This has motivated the design of a robotic system
to support a PET imaging system around the subject's head and to move the
system to accommodate natural motion. We report here the design and
experimental evaluation of a prototype robotic system that senses motion of a
subject's head, using parallel string encoders connected between the
robot-supported imaging ring and a helmet worn by the subject. This measurement
is used to robotically move the imaging ring (coarse motion correction) and to
compensate for residual motion during image reconstruction (fine motion
correction). Minimization of latency and measurement error are the key design
goals, respectively, for coarse and fine motion correction. The system is
evaluated using recorded human head motions during locomotion, with a mock
imaging system consisting of lasers and cameras, and is shown to provide an
overall system latency of about 80 ms, which is sufficient for coarse motion
correction and collision avoidance, as well as a measurement accuracy of about
0.5 mm for fine motion correction.Comment: 2023 IEEE/RSJ International Conference on Intelligent Robots and
Systems (IROS