Abstract
We report on a structured light-scanning system, the OGX|4DSCANNER, capable of capturing the surface of a human body with 2 mm spatial resolution at a 60 Hz frame-rate. The performance of modeling the human lower body dynamics is evaluated by comparing the system with the current gold standard, i.e., the VICON system. The VICON system relies on the application of reflective markers on a person's body and tracking their positions in three-dimensional space using multiple cameras [optical motion capture (OMC)]. For the purpose of validation of the 4DSCANNER, a set of "virtual" markers was extracted from the measured surface. A set of musculoskeletal models was built for three subjects based on the trajectories of real and virtual markers. Next, the corresponding models were compared in terms of joint angles, joint moments, and activity of a number of major lower body muscles. Analyses showed a good overall agreement of the modeling outcome. We conclude that the 4DSCANNER within its limitations has the potential to be used in clinical gait analysis instead of optical marker-based systems. The advantage of the 4DSCANNER over OMC solutions is that it does not burden patients with time-consuming marker application. This study demonstrates the versatility of this measurement technique.
Highlights
The need of acquiring kinematic information of human motion is given in numerous applications in both the entertainment industry and clinical environment
In the current paper we present the OGX|4DSCANNER, which is an implementation of the markerless motion capture (MMC) concept using the structured light technique that is able to capture 3-D shape of human lower body surface at 60 Hz
The analysis described above is applied to every frame in the sequence resulting in a virtual markerset that is estimated for every point cloud
Summary
The need of acquiring kinematic information of human motion is given in numerous applications in both the entertainment industry and clinical environment. Clinicians and researchers are able to evaluate person’s locomotive capabilities and disabilities based on a subject’s recorded 3-D motion. In the TLEMsafe project[1] we develop, validate, and clinically implement an ICT-based patient-specific surgical navigation system that integrates modeling, simulation and visualization tools. This system will help surgeons safely reach the optimal functional results for patients that are undergoing major surgical intervention of the lower extremity. The starting point is the Twente Lower Extremity Model (TLEM),[2] based on the first comprehensive and consistent anatomical dataset, in which
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