Intelligent Knee Brace

As part of an intelligent knee brace project for a start-up company, I was responsible for all proof of concept design programs integrated with virtual product development (VPD) simulations to predict knee brace function and performance in a typical NFL game environment for both contact and non-contact anterior cruciate ligament (ACL) injury mechanisms prior to building a physical prototype.  The research program included the following steps:

  1. Performed an epidemiologic study of anterior cruciate ligament (ACL) inuries in the National Football League (NFL), I analyzed both contact and non-contact injury mechanisms using video replays of in-game NFL ACL injuries over a 2 year period.
  2. Conducted 3D motion capture studies using a passive optical motion capture system with synchronized force plate and EMG data for single-leg high acceleration/deceleration movement patterns (cutting and jumping) representative of the non-contact NFL ACL injury mechanism, as well as for a typical quarterback (QB) throwing motion representative of a contact NFL ACL injury mechanism also in support of the knee brace project.  These studies were performed on 10 different subjects for each activity and also included a detailed subject calibration phase for subsequent forward dynamics modeling.
  3. Kinematic studies were performed on the cutting and jumping motion capture data to determine angular velocity ranges at the knee joint for inertial sensor technical specifications as well as player characterization studies.
  4. Created and developed a macro level forward dynamics body simulation model and a micro level detailed knee simulation model to analyze knee ligament injury mechanisms for both contact and non-contact simulations for the intelligent prototype knee brace and shoe system.
  5. Responsible for the design and development of a knee brace prototype including ultra-lightweight, optimized exoskeleton structure and a shear thickening fluid (STF) outer sleeve.  The exoskeleton was used for both dynamic performance and MEMS inertial sensor incorporation for measuring and predicting the onset of ACL injury.
  6. I was also responsible for researching and providing technical specification requirements on angular rate sensors and accelerometers for the inertial sensor prototype system.  The results from the kinematic analysis phase of the motion capture system studies for jumping and cutting activities were used to help define the sensor specifications.
  7. In conjunction with the inertial sensor prototype phase, I was responsible for development of a 6 DOF pose estimation algorithm for both position and orientation using an extended Kalman filter to fuse the inertial sensors housed in the knee brace exoskeleton.
  8. In order to calibrate the inertial system, I used a passive optical motion capture system and the inertial sensor prototype to verify measurements between the motion tracking systems were the same for angular velocity and acceleration measurements for typical NFL cutting motions.


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