Reconstructing the mechanics and determining the cause of a person falling from a height in the absence of witness observations or a statement from the victim can be quite challenging. Often there is little information available beyond the final resting position of the victim and the injuries they sustained. The mechanics of a fall must follow the physics of falling bodies and this physics provides an additional source of information about how the fall occurred. Computational, physics-based simulations can be utilized to model the free-fall portion of the fall kinematics and to analyze biomechanical injury mechanisms. However, an accurate determination of the overall fall kinematics, including the initial conditions and any specific contributions of the person(s) involved, must include the correct position and posture of the individual prior to the fall. Frequently this phase of the analysis includes voluntary movement on the part of the fall victim, which cannot be modeled with simulations using anthropomorphic test devices (ATDs). One approach that has been utilized in the past to overcome this limitation is to run the simulations utilizing a number of different initial conditions for the fall victim. While fall simulations allow the initial conditions of the fall to be varied, they are unable to include the active movement of the subject, and the resulting interaction with other objects in the environment immediately prior to or during the fall. Furthermore, accurate contact interactions between the fall victim and multiple objects in their environment can be difficult to model within the simulation, as they are dependent on the knowledge of material properties of these objects and the environment such as elasticity and damping. Motion capture technology, however, allows active subject movement and behaviors to be captured in a quantitative, three-dimensional manner. This information can then be utilized within the fall simulation to more accurately model the initial fall conditions.

This paper presents a methodology for reconstructing fall mechanics using a combination of motion capture, human body simulation, and injury biomechanics. This methodology uses as an example a fall situation where interaction between the fall victim and specific objects in the environment, as well as voluntary movements by the fall victim immediately prior to the accident, provided information that could not be otherwise obtained. Motion capture was first used to record the possible motions of a person in the early stages of the fall. The initial position of the fall victim within the physics based simulation of the body in free fall was determined utilizing the individual body segment and joint angles from the motion capture analysis. The methodology is applied to a real world case example and compared with the actual outcome.

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