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Widget Connector
urlhttps://www.youtube.com/watch?v=l52s1VRyenw

 

Software:

Matlab Scripting:

View file
nameMatlab Scripting Software.zip
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Description

This project focuses on using inertial measurement units (IMUs) in the "wild," meaning using IMUs to capture state-specific data in a non-laboratory and non-controlled environment. IMUs are generally used to capture linear acceleration and angular velocity data using gyroscopes and accelerometers. Through some integration, these linear accelerations and angular velocities can then be used to determine the position of the IMU,which provides a useful way to capture biomechanical data such as joint angles and body positions. However, one of the largest issues with capturing real-time position data is the noise apparent not only in the environment, but also in the sensors themselves. Using the integration method to determine positions and joint angles introduces drift error - a systemic artifact due to the integration that causes the data to shift towards one direction. Existing studies have shown that applying a Kalman filter could ameliorate the effects of this drift. 

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 Vasavada, Li, and Delp. "Influence of muscle morphometry and moment arms on the moment-generating capacity of human neck muscles." Spine, 1998.

 Young, Alexander D. "Wireless realtime motion tracking system using localised orientation estimation." (2010).

 

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Home: BIOE-ME 485 Spring 2017

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