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Balanced among the disciplines

A computational knee model is validated by comparing motion to an identically-loaded cadaver knee.
A computational knee model is validated by comparing motion to an identically-loaded cadaver knee.

UMKC Human Motion Laboratory supports interdisciplinary research

In the third-floor Human Motion Laboratory at the UMKC School of Computing and Engineering (SCE), a research subject adorned with reflective body markers and electromyography (EMG) sensors walks across four metal plates as cameras record his movements. Assistant Professors of Mechanical Engineering Trent Guess and Greg King watch as the subject’s movements are projected onto a computer screen.

This state-of-the-art equipment exists thanks to a $263,685 grant from the National Science Foundation (NSF) titled “Major Research Instrumentation: Acquisition of an Experimental Platform to Support Research and Educational Activities in Human Motion”. Each year, the National Science Foundation receives about 44,000 competitive requests for funding, and accepts only 11,500.

King, co-principal investigator, said he believes SCE received the competitive grant for several reasons.

“The multidisciplinary nature of this project had a lot to do with it,” King said. “Our Human Motion Laboratory can support research in electrical engineering, mechanical engineering, psychology, nursing, criminology, dance and more.”

Area high school students and teachers learn about the UMKC Human Motion Laboratory.

Area high school students and teachers learn about the UMKC Human Motion Laboratory.

The NSF grant enabled King and Guess, co-principal investigators; Reza Derakhshani, co-principal investigator and assistant professor of Electrical Engineering; and Walter D. Leon-Salas, co-principal investigator and assistant professor of Electrical Engineering, to purchase force plates for measuring ground reaction forces, electromyography sensors for measuring muscle activations, a motion capture system for measuring body segment kinematics, a high-speed high-resolution camera for measuring ocular and body motion and instrumentation to characterize body area sensor nodes.

Planned projects within the laboratory include capturing real-world human activities for multi-scale computational knee model simulations, predicting and eliminating fall risk among balance-impaired older adults, finding gait characteristics for biometric identification and validating sensor networks used in mobile motion capture applications.

Other applications include:

  • Teaching high school students and teachers engineering principles through summer programs, such as ARROWS (Achieving Recruitment, Retention and Outreach with Science, Technology, Engineering and Math)
  • Studying dance movements and injury prevention with the Conservatory of Music and Dance
  • Studying startle responses with the Department of Psychology
  • Collaborating with the School of Dentistry to build computational models of bones
  • Studying geriatric movement with the School of Nursing

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