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Assessment of daily-life dynamic interactions between human body and environment using movement and force sensing on the interface

Kortier, H. (2010) Assessment of daily-life dynamic interactions between human body and environment using movement and force sensing on the interface.

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Abstract:This study describes different methods to evaluate the physical interaction between the human body and the environment during the performance of daily life tasks. Evaluation is performed by measuring forces and movement on the contact interface of both human body and environment. Concepts are presented for an ambulatory evaluation of task performances and estimation of body and load dynamics. Principles are demonstrated experimentally using a haptic robot, which is able to simulate loads according daily life situations. In addition, dynamics of physical mass and spring loads were estimated. Three different arm tasks have been proposed. The first task is a reaching task: subjects had to displace different masses over approximately 23 centimeters as fast as possible within a specified endpoint accuracy. Timing and endpoint position were measured to determine the subject’s task performance. Next the simulated masses were identified with an accuracy of ±4%. During the second and third task conditions, subjects had to maximize their arm velocity before the load dynamics were abruptly changed (Task 2: end effector inertia was lowered from a maximum of 25 kg to 2 kg. Task 3: Viscous damping was raised from 10 to 300 Ns/m ). Task performances were evaluated by the applied impulse, i.e. multiplication of simulated end-effector inertia with its velocity at the onset of change in load dynamics. Full identification of body dynamics was impossible as the duration of body perturbations was too short. However responses were visible when load dynamics suddenly changed. Condition 3 showed under-damped responses in the recorded interface forces which could be caused by a high muscle stiffness. Experiments with the haptic robot gave partially erroneous results in identified parameters which were probably caused by rendering limitations and wear in actuators and/or gearboxes. Estimation with physical loads were accurate within 5% for mass loads and 3% for spring loads. In contrast to simulated loads with the haptic robot, parameter estimations were successfully estimated by a recursive identification algorithm.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology
Programme:Electrical Engineering MSc (60353)
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