Optimization Based Dynamic Human Motion Prediction with Modular Exoskeleton Robots as Interactive Forces: The Case of Weight Lifting Motion

The optimization-based dynamics model is formulated for the weight lifting motion with human and exoskeleton model as interactive force term in this chapter. In the optimization algorithm, the human motion is defined as variables so that the motion which we want to generate (box lifting motion in this case) can be predicted. The objective function or cost function is defined as performance measure which can be switched by developer. In this paper we use the summation of each joint torque square which is considered as the dynamic effort for the motion. Constraints are defined as joint limits, torque limits, hand position, dynamic balance, exoskeleton assistive points, etc. Interaction force form exoskeleton robot can be derived as generalized coordinates and generalized force which are related to inertial reference frame and human body frame. The results can show how effective the exoskeleton robots are according to their assistive force.

Preliminary Analysis of StrongArm® Ergoskeleton on Knee and Hip Kinematics and User Comfort

This study was constructed to assess the influence of wearing semi-soft exoskeletons on hip and knee kinematics when engaging in a box lifting task. Six healthy college aged students (age: 21.7 ± 2.3; gender: 4 males, 2 females; height: 177.0 ± 3.4 cm; weight: 77.1 ± 17.9 kg; hand dominance: all right) completed box lifting tasks (at 10% and 20% of their body weight) while wearing no exoskeleton and two exoskeleton designs. Lifting a box at 20% body weight increased perceived exertion and was associated with poor hip and knee kinematics in some conditions. Wearing the StrongArm® V22 ERGOSKELETON without hand cables may diminish some of the poor kinematics associated with lifting objects.