UROP Poster copy (2)
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Nicole A. Johns, Arthur D. Kuo Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan Processing Inertial Measurement Data of Strides in Human Running Introduction Results Below are IMU results from the feet of a runner during a 10km (~6.2mi) race. Due to the way IMUs calculate data, they tend to “drift,” or gradually increase the difference be- tween the perceived orientation of the body and the actual orientation of the body. Drifting can cause some issues with calculations and plotting. IMUs also have sensors that have trouble captur- ing very large changes in high-paced activities such as running. This also causes miscalculations and incorrect plots, as shown below. Drawbacks IMUs (inertial measurement units) are devices used to measure velocities and accelerations of moving bodies. We use IMUs to study human movement during several different activities, including walking, running, and hiking. By at- taching these devices on the feet, arms, waist, and head, we are able to identify how specific parts of the body move during physical activity, including both aggregate information, such as number of steps, as well as movement trajecto- ries over time. This allows us to look for subtle changes in how an individual moves, such as how much a runner lifts his or her feet at the start of the race as opposed to later when they might begin to tire. The figures below show IMU results from the right foot of the same runner in the same race. Goals • Use MATLAB to convert raw data into movement data • Write code to divide data • Create plots to show gradual changes in body movement • Create programs with little human involvement Acknowledgements Special thanks to UROP for the opportunity to partic- ipate in summer research and selection for the Intel Semiconductor Research Corporation Fellowship. Thank you to Art Kuo and the Human Biomechanics and Control Lab (HBCL) for the support throughout the summer. We are currently working to integrate several separate programs for analyzing a specific physical activity into one program that can process data for that activity. Having one stan- dard program will give new researchers the means to process data in an easier and faster manner. Further Research Forward Distance vs. Foot Elevation Mile 1 Mile 6 Variance Mile 1 Mile 6 Forward Distance vs. Lateral Distance
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Transcript of UROP Poster copy (2)
Nicole A. Johns, Arthur D. Kuo Department of Mechanical Engineering, University of Michigan, Ann Arbor, Michigan
Processing Inertial Measurement Data of Strides in Human Running
Introduction Results
Below are IMU results from the feet of a runner during a 10km (~6.2mi) race. Due to the way IMUs calculate data, they tend to “drift,” or gradually increase the di�erence be-tween the perceived orientation of the body and the actual orientation of the body. Drifting can cause some issues with calculations and plotting.
IMUs also have sensors that have trouble captur-ing very large changes in high-paced activities such as running. This also causes miscalculations
and incorrect plots, as shown below.
Drawbacks
IMUs (inertial measurement units) are devices used to measure velocities and accelerations of moving bodies. We use IMUs to study human movement during several di�erent activities, including walking, running, and hiking. By at-taching these devices on the feet, arms, waist, and head, we are able to identify how speci�c parts of the body move during physical activity, including both aggregate information, such as number of steps, as well as movement trajecto-ries over time. This allows us to look for subtle changes in how an individual moves, such as how much a runner lifts his or her feet at the start of the race as opposed to later when they
might begin to tire. The �gures below show IMU results from the right foot of the same runner in the same race.
Goals
• Use MATLAB to convert raw data into movement data• Write code to divide data• Create plots to show gradual changes in body movement• Create programs with little human involvement
Acknowledgements
Special thanks to UROP for the opportunity to partic-ipate in summer research and selection for the Intel Semiconductor Research Corporation Fellowship. Thank you to Art Kuo and the Human Biomechanics and Control Lab (HBCL) for the support throughout
the summer.
We are currently working to integrate several separate programs for analyzing a speci�c physical activity into one program that can process data for that activity. Having one stan-dard program will give new researchers the means to process data in an easier and faster
manner.
Further Research
Forward Distance vs. Foot Elevation
Mile 1 Mile 6
Variance
Mile 1 Mile 6
Forward Distance vs. Lateral Distance
