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Part of book or chapter of book
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https://doi.org/10.1007/117527...
Part of book or chapter of book . 2006 . Peer-reviewed
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A Method for the Verification of Haptic Algorithms

Authors: DE BOECK, Joan; RAYMAEKERS, Chris; CONINX, Karin;

A Method for the Verification of Haptic Algorithms

Abstract

The number of haptic algorithms has been growing over the past few years. However, little research has been performed in evaluating these algorithms. This paper provides both a theoretical framework and a practical discussion of how the correctness and performance of force-feedback algorithms can be verified. The practical discussion is necessary as the theoretical framework proves that an infinite number of cases should be considered when evaluating a haptic algorithm. However, using statistical techniques, this evaluation can be performed within a reasonable frame of time. The evaluation method in this paper has itself been validated by evaluating two algorithms. From this test, we can conclude that the evaluation method is a reliable method for verifying if haptic algorithms are correct.

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Belgium
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green