Position driven sit-to-stand simulation using human body motion and force capture

Sit to stand (STS) motion in the context of dynamic variables and their relation to the Body Segment Parameters (BSP) used for human biomechanical modeling is presented. The experimental part of our scheme comprises kinematic data collection of STS transfer using reflective markers and multiple infra-red camera setup. Kinetic data are simultaneously recorded using a 2-axis force plate. In the analytical part, a generalized human biomechanical model in Simulink's SimMechanics environment is realized. To obtain a model that closely matches and replicates the actual motion, the demographic data of each subject are first converted into BSP. The anthropometric methods available in the literature may lead to an error of up to 40% of actual BSP. To minimize the error, a hybrid technique is used to develop a biomechanical model using experimental motion data and BSP values. Simulated joint angles, motion trajectories, Ground Reaction Forces (GRF) and joint torques are compared with real subjects' experimental results. Our analyses show a close match of the two sets of results; having 0.74 to 0.99 correlation. This validates the reliability of both the marker-based motion capture technique and the weighting coefficient based anthropometry in the human biomechanical modeling perspective. This paper is a part of an ongoing study that is aimed to evaluate the role of various kinematic variables as feedback elements to CNS in controlling STS motion. Our findings have the scope to understand human motion mechanism in terms of diagnosis, rehabilitation and design of force augmentation / robotic devices.