C-MoRe
making stroke recovery easier to see, track, and guide.
C-MoRe is a collaboration between UC Davis and UC Irvine to
assist physicians in the stroke recovery assessment "Box and Blocks"
using computer-vision. With fine-tuned [model], [model], [model],
we track patient hand and block interactions, counting valid passes
and flagging inconsistencies.
Special thanks to [] at [] for testing opportunities and guidance.
Walkthrough
Recording a new session
- Starting in the library view, press the "add" button at the bottom of the screen to enter the recording studio.
- Use the white box guide to orient the camera. Once in a valid position, [valid indication].
- Press the red record button, and choose new recording.
- Recording will automatically end at the 1 minute mark. To end early, press the recording button again.
Naming your session
The C-MoRe App offers multiple naming options:
- In recording studio, on record: a custom or default name can be entered. If default is chosen, the session will be labeled with time of creation.
- In recording studio, on end of record: the session can be renamed through the [] option.
- In library view, on left swipe: the session can be renamed through the blue pencil widget.
Accessing your session
In library view:
- To see the video result, simply select the desired session.
- To share, swipe left on the session and select the share icon. An mp4 video and JSON will be sent to the selected location.
About Us
C-MoRe (Clinical Motor Recovery assessment tool) was developed by UC Davis computer science researchers Ziqiang "Joe" Zhu and Jun Min Kim, alongside project lead Andria Farrens and UC Irvine's Department of Mechanical and Aerospace Engineering. The project began when Farrens, while researching robotic hand rehabilitation for stroke survivors, saw an opportunity to combine smartphone camera footage with motion-tracking software to quantify recovery more precisely than a clinician's eye alone. Today, C-MoRe uses computer vision to analyze patients performing the Box and Blocks Test, giving physicians objective, detailed data — like grasp duration and movement velocity — to personalize rehabilitation and move toward more precise, data-driven stroke care.