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Network Representation of User’s Mechanical Impedance as Design and Evaluation Basis for Task-Specific Haptic Systems

Hatzfeld, Christian and Kern, Thorsten Alexander and Neupert, Carsten and Lotichius, Jan and Werthschützky, Roland Technische Universität Darmstadt, Continental Corporation (Corporate Creators) (2013):
Network Representation of User’s Mechanical Impedance as Design and Evaluation Basis for Task-Specific Haptic Systems.
In: Sensor 2013, Nürnberg, [Online-Edition: http://dx.doi.org/10.5162/sensor2013/B2.2],
[Conference or Workshop Item]

Abstract

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.

Item Type: Conference or Workshop Item
Erschienen: 2013
Creators: Hatzfeld, Christian and Kern, Thorsten Alexander and Neupert, Carsten and Lotichius, Jan and Werthschützky, Roland
Title: Network Representation of User’s Mechanical Impedance as Design and Evaluation Basis for Task-Specific Haptic Systems
Language: English
Abstract:

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.

Uncontrolled Keywords: haptic system design, network representation, user impedance, vector fitting, system identification
Divisions: Study Areas
18 Department of Electrical Engineering and Information Technology > Institute for Electromechanical Design
18 Department of Electrical Engineering and Information Technology > Institute for Electromechanical Design > Measurement and Sensor Technology
18 Department of Electrical Engineering and Information Technology
Event Title: Sensor 2013
Event Location: Nürnberg
Date Deposited: 15 May 2013 07:53
Official URL: http://dx.doi.org/10.5162/sensor2013/B2.2
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