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New math-based musculoskeletal model seeks to predict injuries

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Photo: angelhell/iStockphoto

Philadelphia — Seeking to gain insights on how an injury to one part of the body potentially can lead to other injuries, University of Pennsylvania and Haverford College researchers have developed a mathematical model for all human muscles and bones.

The network model is an attempt to simplify the musculoskeletal system by treating muscles as “springs” and bones as “balls.” In its “highly abstract form,” according to a press release, the network model intends to show the transmission of forces throughout the body.

Researchers stated that as they refine the model, they hope it will give physical therapists and clinicians opportunities to predict compensatory injuries and advise patients on how to avoid them.

“We can say, ‘If this is the muscle you injured, here are the other muscles we should be most worried about,” Danielle Bassett, lead researcher and associate professor at Penn’s School of Engineering and Applied Sciences, said in the release.

The researchers also looked at their network in relation to the “motor homunculus,” a method of mapping brain regions that control certain parts of the body.

“We saw that the more impact that a muscle has on the rest of the body, the more real estate we use in our brain to control it,” Bassett said in release. “We think it’s a way for us to maintain robustness in those muscles – if a muscle can have a massive impact on the rest of the body, you don’t want any error in controlling it.”

The researchers plan to continue revising their musculoskeletal model, namely updating for “more realistic” bone mass and “stretchiness” in muscles. They also will seek to improve modeling for tendons and for muscles that “have more complicated flexing behaviors.”

The study of the network model was published Jan. 18 in PLOS Biology.

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