Human reach posture prediction based on psychophysical discomfort

doi:10.1016/0169-8141(95)00080-1

International Journal of Industrial Ergonomics

Volume 18, Issues 2–3, September 1996, Pages 173-179

https://doi.org/10.1016/0169-8141(95)00080-1 Get rights and content

Abstract

A man model is a useful design tool for the evaluation of man — machine systems and products with less time delay and cost specifically at the early stage of design. For a man model to be truly useful, it must be integrated with a proper posture prediction model, especially, an arm reach prediction model. In this study, a regression model to predict the perceived discomfort with respect to the joint movement was developed using a central composite design based on the response surface method. Joint angles of the upper body with seven degrees of freedom and the weight of a load were treated as independent variables while the perceived discomfort measured using a magnitude estimation technique was used for the response variable. The perceived discomfort in the category scale and the normalized EMG of six muscles were also collected. A three-dimensional reach posture prediction model using an inverse kinematics technique was then developed, based on the prediction of perceived discomfort. The model predicts the posture by selecting the minimum discomfort configuration among feasible body postures to reach a target point. The reach posture prediction model developed in this study was found to simulate human arm reach posture accurately and the discomfort prediction model will help understand the human arm reach movement.

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A numerical tool to simulate the kinematics of the ingress movement in variably-dimensioned vehicles for elderly and/or persons with prosthesis
2015, International Journal of Industrial Ergonomics
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Minimization of the jerk (Hogan and Flash, 1987; Schneider and Zernicke, 1989), Other criteria issued from robotics such maximization of dexterity (Lepoutre, 1993; Jung and Choe, 1996). Very attractive (Wang, 2008), this class of methods indeed offers the advantage of being generic.
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Simulations involving elderly people and/or people with prostheses made it possible to validate the proposed method for the two ingress strategies. Despite the differences with the measured movements, the simulated movements conform to the sub-strategies adopted by the subjects during the experiments. Furthermore, the simulations made it possible to partially explain the shifts in strategy of some subjects when they changed vehicles during the experiments. Finally, simulations on fictitious vehicles highlighted some of the limitations of our simulation tool. This study opens several perspectives for future research. For example, we could improve the simulation tool by considering the subjects' intra-individual differences.
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The relevant literature on these topics will be reviewed in the following sections. Jung et al. [10–12] suggested a psychophysical cost function to describe the joint discomfort. This cost function indicated that the farther from the center angle, the more discomfort human feels.
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Digital human modeling provides a valuable tool for designers when implemented early in the design process. Motion capture experiments offer a means of validation of the digital human simulation models. However, there is a gap between the motion capture experiments and the simulation models, as the motion capture results are marker positions in Cartesian space and the simulation model is based on joint space. Therefore, it is necessary to map the motion capture data to simulation models by employing a posture reconstruction algorithm. Posture reconstruction is an inherently redundant problem where the collective distance error between experimental joint centers and simulation joint centers is minimized. This paper presents an optimization-based method for determining an accurate and efficient solution to the posture reconstruction problem. The procedure is used to recreate 120 experimental postures. For each posture, the algorithm minimizes the distance between the simulation model joint centers and the corresponding experimental subject joint centers which is called the mean measurement error.
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Citation Excerpt :
For the optimization-based method, the key point is to find the minimum value of a cost function by meeting all the constraint requirements. There are some performance measurements which act as cost functions; for example, discomfort (Jung & Choe, 1996) and joint displacement (Jung & Park, 1994; Zou, Zhang, Yang, Boothby et al., 2011; Zou, Zhang, Yang, Cloutier et al., 2011) can be used as cost function when formulating multi-objective optimization (Howard, Cloutier, Yang, accepted; Yang, Marler, Kim, Arora, & Abdel-Malek, 2004). Determining the relative importance for different human performance measures is a key issue in multi-objective optimization.
This paper presents a nonlinear inverse optimization approach to determine the weights for the joint displacement function in standing reach tasks. This inverse optimization problem can be formulated as a bi-level highly nonlinear optimization problem. The design variables are the weights of a cost function. The cost function is the weighted summation of the differences between two sets of joint angles (predicted posture and the actual standing reach posture). Constraints include the normalized weights within limits and an inner optimization problem to solve for joint angles (predicted standing reach posture). The weight linear equality constraints, obtained through observations, are also implemented in the formulation to test the method. A 52 degree-of-freedom (DOF) human whole body model is used to study the formulation and visualize the prediction. An in-house motion capture system is used to obtain the actual standing reach posture. A total of 12 subjects (three subjects for each percentile in stature of 5th percentile female, 50th percentile female, 50th percentile male and 95th percentile male) are selected to run the experiment for 30 tasks. Among these subjects one is Turkish, two are Chinese, and the rest subjects are Americans. Three sets of weights for the general standing reach tasks are obtained for the three zones by averaging all weights in each zone for all subjects and all tasks. Based on the obtained sets of weights, the predicted standing reach postures found using the direct optimization-based approach have good correlation with the experimental results. Sensitivity of the formulation has also been investigated in this study. The presented formulation can be used to determine the weights of cost function within any multi-objective optimization (MOO) problems such as any types of posture prediction and motion prediction.

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View full text

Human reach posture prediction based on psychophysical discomfort

Abstract

International Journal of Industrial Ergonomics

Robot Analysis and Control

Application of SAMMIE and the development of man modelling

SAMMIE: A man and workplace modelling system

On the cost functions for the control of the human arm movement

Biological Cybernetics

Anthropometric modelling program — A survey

IEEE Computer Graphics and Applications