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This paper focuses on full body dynamical analysis of car ingress/egress motion. It aims at proposing an experimental protocol adapted for analysing joint loads using inverse dynamics. Two preliminary studies were first performed in order to 1/ define the main driver/car interactions so as to allow measuring the contact forces at all possible contact zones and 2/ identify the design parameters that mainly influence the discomfort. In order to verify the feasibility of the protocol, a laboratory study was carried out, during which two subjects tested two car configurations. The experimental equipment was composed of a variable car mock-up, an optoelectronic motion tracking system, two 6D-force plates installed on the ground next to the doorframe and on the car floor, a 6D-Force sensor between the steering wheel and the steering column, and two pressure maps on the seat. Motions were reconstructed from measured surface markers trajectories using inverse kinematics.

This paper presents a pilot study aimed to carry out a method for prehension movement recording. This method consists of using, simultaneously, a motion analysis system (Vicon®) and a sensitive glove (Cyber Glove®). The objective is to be able to give a set of complete data to our hand model in order to simulate the human prehension movement. In a first study, only a data glove was used to record grasping movement. Many problems appeared when analysing the output of this system: 1. the hand model considered in the glove software is different from our model, 2. the arch degree of freedom does not exist in the glove model, despite the existence of the corresponding sensor, 3. the output from ab duction and flexion sensors are linked, 4. the calibration of the thumb is not efficient. From these technical constraints, another movement recording system - motion analysis system - is used and data glove completes the data recorded with motion analysis system.

This paper investigates the feasibility of calculating joint forces and moments during a whole body truck cabin ingress/egress motion. For such a task, it is difficult to evaluate a future truck instep as the influences of the architecture parameters are complex over the motion and the discomfort feeling. In order to evaluate the future product at an early stage of the design process, Digital Human Models (DHMs) are interesting tools. However, most existing DHM simulation packages can only efficiently evaluate the kinematics of postures where the dynamics of the whole motion is necessary for such a task. The enhancement of DHMs towards a dynamic analysis and modeling is therefore necessary. In this study, the motions of subjects entering and exiting an adjustable truck cabin were measured by mean of an opto-electronic motion capture system and six load sensors. The joint angles were then calculated using an inverse kinematics method.