Most people don’t think about their thumbs very often. But for people living with advancing arthritis, the simplest thumb movements — from grasping a cup to sending a text message — can be painful and incredibly challenging.
That’s why Michigan State University researchers set out to see if they could use motion capture technology to screen for differences between healthy hand movements and those in patients with osteoarthritis, or OA. This method could potentially detect arthritis earlier, possibly delaying and preventing the loss of thumb function. In turn, that could save arthritis patients from surgery and even being forced into assisted living.
The team’s research is published in Clinical Biomechanics.
“Our work suggests that three-dimensional motion tasks may be able to identify OA-associated motion deficits earlier than the two-dimensional motion tasks typically used in a clinical setting,” said Amber Vocelle, co-author on the research and a DO/PhD student in the College of Osteopathic Medicine. “By identifying the disease earlier, we can treat OA earlier in the disease process.”
According to Vocelle, therapists and clinicians traditionally use goniometers, simple two-dimensional measurement tools, along with basic movements to screen for reduced hand function due to OA. But the results can vary depending on who’s doing the measuring, making it hard to track reliably over time.
“There are pieces of information that aren't being gathered right now that could be useful for early prediction of OA of the thumb, or setting up thresholds to define when people should consider doing therapy before they're in severe pain,” said Tamara Reid Bush, an associate professor of mechanical engineering in the College of Engineering who also worked on the research.
In contrast, motion capture technology records precise, objective measurements in three dimensions.