MFPT2019 has ended
Mobile App sponsored by Poseidon Systems, LLC
Thursday, May 16 • 8:30am - 9:00am
Monitoring Center of Mass Movement as an Indicator of Efficiency in Pre-Planned versus Reactive Agility Drills

Log in to save this to your schedule and see who's attending!

Feedback form is now closed.
In looking into the components of a human monitoring system, there are three main elements that comprise the system: sensors; data acquisition and communication; and data processing and analytics. Sensors that function with the purpose of sensing body movements or collecting specific physiological or biological parameters of an individual are typically known as wearables. Wearables used for capturing body movements are primarily inertial measurement units (IMUs) which utilize sensor fusion to combine the technology of an accelerometer, gyroscope, and magnetometer. Data obtained from these wearables may provide important insight into subtle differences in body movements that influence performance outcomes. The long-term goal of our work is to develop approaches that enable the prediction of an individual’s performance in an open-skilled environment. The specific aim of this research was to determine how data from a full body IMU-based system could be used in detecting subtle movement differences in the execution of a pre-planned agility test versus a reactive agility test._x000D_
Ten healthy young adult males who were regularly physically active and had played on a sports team within the past four years participated in this study. An Xsens Awinda 17 sensor suit was used to capture body movement data during the two agility tests. In both the pre-planned and reactive agility test, study participants stood facing six programmable illuminating lights, arranged in a 3 meter arc, 1.5 meters apart from each other, with the center being the starting position. For the pre-planned test the participant was informed which three lights in order they would run to, with the requirement that they return to the center before advancing to the next light. For the reactive agility test, the participant was informed that all 6 lights would turn on, but the light they must run to and turn off would not have a color pair (ex. 3 red, 2 blue, 1 green). Participants were also asked to remember the color sequence of the three lights they turned off for an additional stressor._x000D_
Throughout the tests, each participant’s center of mass (CoM) was tracked and compared to the direct path to the light with deviations calculated using standard sums of squares error (SSE). Study participants were broken into two groups for comparison: faster individuals and slower individuals based off of their completion time on the pre-planned agility test. Results from the pre-planned agility assessment indicated that the mean SSE for the CoM deviations to the light averaged 1.66 ± 1.43 meters for the faster performers and then 2.96 ± 2.05 meters for the slower performers. For the reactive agility tasks, the CoM deviations were higher with an average SSE of 5.82 ± 4.16 meters for the faster performers and 6.97 ± 7.60 meters for the slower performers. This suggests that the slower individuals were not just slow, but were likely slow because they were inefficient. Additionally, these findings indicate the notable increase in inefficiency generated by the uncertain scenario of the reactive agility test which corresponds to the 84% time increase from the pre-planned test.


Amanda Delaney

Master's Student, University of Dayton

Thursday May 16, 2019 8:30am - 9:00am
Freedom Ballroom II