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Hand Force-Dependent Modeling Of The Hand-Arm Under Zh-Axis Vibration - Introduction; Proceedings Of The First American Conference On Human Vibration
  • Published Date:
    6/1/2006
Filetype[PDF - 181.89 KB]


Details:
  • Description:
    A number of biodynamic models of the hand-arm system have evolved on the basis of measured driving-point mechanical impedance (DPMI) responses to facilitate analyses of the coupled hand-tool system [1]. The parameter identifications in such models are based upon minimization of an error function of the model and the target impedance data, which may not yield a unique solution. Consequently, a number of model structures and parameter sets could be realized that would equally satisfy the target curve. Moreover, the vast majority of the reported models exhibit acute deficiencies due to excessive static deflections of model masses, presence of a low frequency mode and very light masses in the order of 1.2- 4.8 grams. The models also do not characterize the dependency of the biodynamic responses on many factors, namely the hand forces, hand-arm posture and vibration intensity. This study aims at development of a hand-arm biodynamic model with considerations of the hand forces, and both the DPMI and power absorption measures, to enhance the uniqueness of the model. Methods Two different model structures are chosen for identifying the model parameters on the basis of measured DPMI and absorbed power characteristics of the hand-arm system under zh-axis vibration over a range of hand-grip and push forces. Owing to the strong influence of the hand-handle coupling forces, the models were initially derived for fixed hand forces, namely 30 N grip and 50 N push forces, as suggested in the ISO 10068 standard [2]. The equations of motion for the model are formulated and solved to compute both the DPMI and absorbed power responses. A constrained minimization function comprising weighted errors of both the DPMI and absorbed power is formulated and solved to identify the parameters. Alternate functions corresponding to different combinations of hand forces are then applied to identify hand-force dependent model parameters. Variations in the model parameters are investigated as functions of the grip, push and coupling forces through linear regression analysis. Regression-based models are formulated for deriving the hand-handle forces dependent model parameters. The validity of the model is also examined under selected combinations of hand forces. [ ]

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