An Inverse Kinematic Approach Using Groebner Basis Theory Applied to Gait Cycle Analysis

Abstract

Kinematics of the human body was researched for the purposes of this study. The force protection issues of today was the motivation to research pattern recognition in the human gait cycle to identify individuals carrying a concealed load on their body. The goal of this research was to identify gait signatures of human subjects and distinguish between subjects carrying a concealed load to subjects without load. Thus, this research was focused on studying the human gait cycle as well as methods used in identifying gait signatures. The main focus hearin is concerned with the movement of the lower extremities, in particular, the placement of the foot and how the joint angles area affected with carrying extra load on the body. A method of Inverse Kinematics (IK) using Groebner Basis (GB) Theory is developed to a model of the lower extremities to determine all the solutions of the joint angles, given the position and orientation of the foot. The human gait cycle was captured and analyzed using an VICON Motion capture system. This research highlights the results obtained from applying the method of IK, using GB, to the lower limbs of a human gait cycle to extract and identify gait signatures.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2013
Accession Number
ADA582260

Entities

People

  • Anum Barki

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Biomedical
  • C4I
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Biomechanical Phenomena
  • Computers
  • Data Analysis
  • Graphical User Interface
  • Improvised Explosive Devices
  • Joints (Anatomy)
  • Man Borne Improvised Explosive Devices
  • Medical Personnel
  • Military Research
  • Motion Capture
  • Operating Systems
  • Spreadsheet Software
  • Statistics
  • Three Dimensional
  • United States Government
  • Upper Extremity

Readers

  • Exercise and Sports Science.
  • Robotics and Automation.
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML