The goal of this project is to vastly improve the way musculosketal modeling is performed and utilized by creating a data driven model that builds on the product of exponentials formulation for joints. By using parameter fitting, a kinematic chain of joints can be fitted the individual rather than scaling a generic template which does not take into account the large diversity in body shapes and sizes. The team will look at a structured, yet data driven approach to modeling a person, making it possible to compare joint ranges and muscular limitations both contralaterally, as well as against their peers. It is also possible to compare a patient and against their past history allowing for better understanding and diagnosis within a specified patient groups (scoliosis, the elderly, hip replacement recovery) as well as with the general population. The PI proposes a hybrid optimal control approach for determining muscular activation based on segmenting different dynamical modes. These modes can take into account changes in mass or geometric constraints such as assistive devices (e.g. crutches walkers or exoskeletons). They propose to apply these methods of musculoskeletal modeling to the upper limbs in the elderly group who experiences muscle weakness, joint damage and may have artificial prostheses.
The tools developed under this proposal can be used to analyze any number of biological creatures by modeling their joints in a similar manner. It expands to a wider robotic community where robotic kinematic chains can be directly compared to biological chains. This can be used for teleoperation of robotic devices where particular joints can be mapped between each other. It also adds to the tools that can be used to design assistive exoskeletons and prosthetic devices, as it allows biological and mechanical joints to be modeled in together- potentially improving the methods of controlling these devices. The project team consists of a PI from Computer Science and two consultants, one from Mechanical Engineering (UC Berkeley) and a MD from UCDMC who have extensive experience in workspace assessment techniques, human modeling, human-machine interaction, and control. Research findings will also be outreached to K-12 students and their parents though various official events at the University. The Center for Information Technology Research in the Interest of Society (CITRIS) at UC Berkeley provides a unique environment and opportunity for the investigators to interact and share research findings with other researchers, students, and broader public.
