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This study was motivated by the simulation of the muscular forces developed during a clutch pedal operation. Fifteen subjects took part in the experiment. Four design parameters (seat height, pedal travel, pedal travel inclination, pedal resistance) were controlled. 28 configurations were tested. For each trial the subjects were asked to rate the perceived discomfort. Individual muscular forces of the left leg for each trial were simulated using motion reconstruction, inverse dynamics and static optimization. The analysis of these simulated muscular forces gave an insight into the way a clutch pedal operation is performed in terms of muscular exertion and coordination. Similarities in muscular force patterns of different subjects were found. The way a change in conception parameters of a car interior affected this muscular exertion was also investigated. This last point revealed that some conception parameters did affect muscular forces significantly.

Recently, we proposed a unified data based approach which aimed at predicting both reach envelopes and reach discomfort for a digital human model [1]. In this approach, four reach surfaces, from half-flexed arm distance to maximum reach with torso participation, need to be defined. The discomfort associated with a point on each surface is defined at first. Then, the discomfort of an intermediate distance between two reach distances is interpolated. The proposed approach was demonstrated on a reaching task corresponding to push a toggle switch from a seated posture without seat back. As data were collected in an environment which is different from the driving situation, these data can not be directly applied to driver's reach capacity and discomfort. In this study, we will apply this approach for in-car driver's reach for predicting different reach envelopes and discomfort.

Improvement in the accessibility assessment of the seatbelts using a Digital Human Model requires a precise description of driver belt donning movement and of the associated discomfort. In order for automotive designers to be able to simulate seatbelt reaching movement, a general approach of motion simulation for complex and specific tasks has been proposed in this paper. It consists of three steps: constitution of a structured database, selection of an appropriate movement and its adaptation to meet new constraints. From an experiment, a database of 644 movements of automotive seatbelt reaching movements has been built-up. In order to structure the database, the temporal and spatial characteristics of the trajectories of main markers (e.g. markers attached to the hand and the torso) as well as joint movements were analysed, allowing us to identify motion control strategies.

Driving posture study is essential for the evaluation of the occupant packaging. This paper presents a method of reconstructing driver’s postures in a real vehicle using a 3D laser scanner and Human Builder (HB), the digital human modeling tool under CATIA. The scanning data was at first converted into the format readable by CATIA, and then a personalized HB manikin was generated mainly using stature, sitting height and weight. Its pelvis position and joint angles were manually adjusted so as to match the manikin with the scan envelop. If needed, a fine adjustment of some anthropometric dimensions was also preceded. Finally the personalized manikin was put in the vehicle coordinate system, and joint angels and joint positions were extracted for further analysis.

A new experimental seat was designed to investigate sitting biomechanics. Previous literature suggested links between sitting discomfort and shear force, however, research on this topic is limited. The evaluation of sitting discomfort derived from past research has been primarily associated with seat pressure distribution. The key innovative feature of the experimental seat is not only pressure distribution evaluation but shear forces as well. The seat pan of the experimental seat compromises of a matrix of 52 cylinders, each equipped with a tri-axial force sensor, enabling us to measure both normal and tangential forces. The position of each cylinder is also adjustable permitting a uniform pressure distribution underneath the soft tissue of the buttocks and thighs. Backrest, armrests, seat pan and flooring are highly adjustable and equipped with forces sensors to measure contact forces.

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.

In addition to three main commercial human models (Ramsis, Jack, Safework), there exists also many non-commercial ones used in research laboratories. Sometimes, it becomes necessary to convert motion data from one model to another. This occurs in the case of the European research project REALMAN. In this project, three models (Ramsis, Jack and Man3D) are used by different partners. As they have different kinematic architectures, we have to write converters allowing collected motion data to be used by all three human models. In this paper, we present the method developed for converting the data from the Human Solution's Ramsis to Man3D, a noncommercial model developed at INRETS. We have shown that it is possible to convert motion data from one manikin to another using a method based on skeleton model comparison.

This paper presents the first experiment managed within the framework of the regional French project ST2 (French acronym for Sciences and Technologies for Safety in Transports). This program aims to study human pre-crash behavior in order to improve the efficiency of passive safety protection systems. An experiment was carried out using a driving simulator of LAMIH for investigating drivers frontal pre-crash postural changes. A scenario of an unavoidable crash was designed. To increase the level of realism during the crash, a real impact was added between the windscreen and a foam rubber block in addition to a truck horn sound. Risk car driver postures just before a frontal crash have been determined. The results have shown that none of the subjects adopted the standardized driving position during the collision and 30% of the subjects adopted a position with the left hand placed in front of steering wheel which can be considered as a risk position.

Both motion simulation and discomfort evaluation are needed for a design engineer when using a digital human model. Thanks to recent progress on motion capture and motion modeling, simulating complex motions in industrial application oriented becomes possible. However, how to evaluate the discomfort associated with such complex motions is another challenge for digital human modeling researchers. In collaboration with French car makers, we have investigated the issue of how to build generic predictive discomfort models of highly environment-constrained motions such as car ingress/egress motions. The purpose of this paper is to present a novel concept called ‘neutral movement’ and to show how it can be used for discomfort modeling of environment-constrained motions. In this paper, the discomfort of car ingress/egress movements will be analyzed with help of the concept of neutral movement. The advantages and limitations of the proposed discomfort modeling approach will also be discussed.

Realistic motion reconstruction is the first step for ‘human like’ motion simulation by a digital human. In a recent European research project REALMAN (IST 2000-29357), a model-based motion reconstruction method from external marker trajectories was developed. It consists of two steps. The first one is to define a digital twin of a real subject using the technique of superimposing a digital human model upon at least two photos of different view, and identifying marker positions on it. In a second step, joint angles are estimated by using a kinematic model of the human body which is described using natural coordinates: coordinates of points and components of unit vectors for defining the joint locations. The model includes a detailed description of the torso, arms and legs, with simplified hands and feet. A total of 26 joints are used, connecting 27 rigid links, among them 6 located on the spine.

Numerical models are used more and more to visualize a human operator within a work environment and simulate his movements. Many models are limited in their ability to simulate complex activities like prehension and objects manipulation. The hand models proposed in the literature are relatively simple, especially assuming the palm as a rigid body, which leads to unrealistic representations of complex attitudes. The objective of the present study is to develop a more advanced hand model, able to properly simulate prehension postures. A 25 degrees of freedom (DOF) hand model has been proposed including 2 DOF for representing the palm arch. Compared to the model without palm arch, the proposed model has made significant improvement of the hand posture representation, suggesting the need of including palm arch for simulating complex hand grasping attitudes.