NDLI: Robust perception-based data reduction and transmission in telehaptic systems

Content Provider	IEEE Xplore Digital Library
Author	Sakr, N. Jilin Zhou Georganas, N.D. Jiying Zhao Petriu, E.M.
Copyright Year	2009
Description	Author affiliation: School of Information Technology and Engineering, University of Ottawa, Ontario, Canada (Sakr, N.; Jilin Zhou; Georganas, N.D.; Jiying Zhao; Petriu, E.M.)
Abstract	In this paper, two robust perception-based haptic data reduction and transmission techniques are presented to reduce data traffic in telehaptic systems. A prediction approach that relies on the least-squares method and median filtering is exploited in order to reduce the number of packets transmitted, and efficiently reconstruct unsuccessfully received data samples. Knowledge from human haptic perception is also used and incorporated into the general data reduction architecture. The techniques are initially evaluated in a basic experimental setting in order to validate their performance. Their application in a haptic-enabled telementoring surgery simulation is also demonstrated. The experimental results prove the proposed approach's effectiveness as haptic data packets can be reduced by as much as 96% in normal network conditions and up to 93% in the presence of significant communication delay and packet loss, while preserving the overall quality of the telehaptic environment.
Starting Page	214
Ending Page	219
File Size	339724
Page Count	6
File Format	PDF
ISBN	9781424438587
DOI	10.1109/WHC.2009.4810839
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Teleoperators E.4 [Coding and Information Theory]: Formal Models of Communication Filtering Virtual environment Humans Cities and towns Data engineering Robustness Haptic interfaces Communication networks H.5.2 [User Interfaces]: Haptic I/O Information technology
Content Type	Text
Resource Type	Article

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