This paper deals with the representation of the human user of a haptic system in the design process and investigates different fitting algorithms to find network representations and transfer functions. The user, represented by the mechanical impedance, serves as mechanical load to the system and influences the assessment of the quality of the haptic feedback. Due to large inter-personal variances, the mapping from measurements to concentrated network parameters is investigated in this paper.Three different fitting approaches are used and compared based on the model error. The results show lowest errors for fitting algorithms that incorporate both amplitude and phase information of the measurements despite a linearity assumption of the basic network model. Suggestions for the mapping of the transfer functions to parameter values of the network model are given.
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