Natural movements in animals almost always occur in 3-D and often are very fast. Take the kangaroo. They hop using long tendons in their legs that appear to act as springs. To quantify rapid skeletal movement in 3-D, scientists have developed a 3-D imaging technology called X-ray reconstruction of moving morphology (XROMM).

This imaging approach allows scientists to study many different animals, including extinct species, analyzing their locomotion in ways never before possible. Research groups worldwide have adopted XROMM hardware and software, which was developed with NSF support.

Previous X-ray motion analysis was limited to 2-D studies and lacked crisp agreement between skin movement and underlying bone movement. However, XROMM combines accurate bone shape and movement. Biomechanics researchers can now study true 3-D motion of joints and how joint surfaces interact during natural movements such as swimming, running, jumping and flying.

The Research Coordination Network for X-ray Motion Analysis enabled the XROMM team, led by Elizabeth Brainerd, to coordinate additional XROMM hardware and software development, and train students and researchers from diverse institutions for XROMM work. Key XROMM partnerships include Brown University, the W.M. Keck Foundation, the Rhode Island Hospital Orthopedic Foundation, and the Bushnell Research and Graduate Education Fund.

The vast amount of data collected by the XROMM team has spawned development of new tools to quickly process the data gathered and open up the XROMM and its results to a much broader user base. If successful, these innovations will substantially increase the throughput of the XROMM animation process and substantially enhance the infrastructure for comparative biomechanics research.

Learn more about the project.

The following are video examples of XROMM analysis:

http://www.youtube.com/watch?v=J1T6FOptVpQ&feature=player_embedded

http://www.youtube.com/watch?v=oJE5eHJaET8&feature=player_embedded

http://www.youtube.com/watch?v=Zgc6lKeLSsE&feature=player_embedded