This project explores a new direction to analyze human gait. The project obtains high accurate gait data, movement and high resolution ground reaction forces on different terrains, which has not been possible to measure and acquire previously. The project enables to produce the first ever detailed and multimodal gait database that can be used for research and education. It can assist computer scientists and biomedical researchers in addressing complex questions such as understanding, analyzing and simulating the kinematics and dynamics of walking in natural settings. The resulting research and datasets can be incorporated in the curriculum of many fields such as computer science, biomedical engineering and medicine and will result in significantly better educated future researchers, professors, and employees in gait analytics.

The project focus on collecting novel, accurate, multi-modal gait data on unconstrained terrains and developing a novel approach to analyze the gait data. The research team develops predictive models to create realistic simulations of human gait, which is important for many industries such as healthcare, sports, footwear, and entertainment. This requires accurate human movement data and ground reaction forces on different terrains. Currently the most common method to collect the gait data is to put surface markers on human subjects. Due to the skin movement, surface marker data collected by this method contain a significant error. Gait kinematics estimated from the surface markers are not accurate and may be quite off from the real human movement. Moreover, the most common methods to collect the ground reaction forces use a simple force plate. However, a simple force plate can only measure the ground reaction forces on one simple type of terrain and cannot measure the ground force close to real daily life. The ground reaction forces on the terrains similar to real life are unknown. This exploration project enables many new studies and applications.

Project Start
Project End
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
Fiscal Year
2014
Total Cost
$150,000
Indirect Cost
Name
Rutgers University
Department
Type
DUNS #
City
Piscataway
State
NJ
Country
United States
Zip Code
08854