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Immersive environment

Haptic data is a kind of immersidata that is used to describe the movement, rotation,

and force associated with user-directed objects in an immersive environment. We use the

CyberGlove as a haptic user interface to an immersive environment. The CyberGlove consists

of several sensory devices that generate data at a continuous rate. The acquired data can

be stored, queried, and analyzed for several applications.

In this chapter, we focus our attention on the analysis of haptic data with the objective

of modeling these data in a database. A large number of diverse applications use haptic data.

Each such application may need haptic data stored and modeled at different levels of abstraction.

For now, we consider three levels of abstraction. First, in Shahabi, Barish, Kolahdouzan,

Yao, Zimmermann, and Zhang (2001), we made our first attempt to model haptic

data at the lowest level of abstraction. There, we dealt with raw haptic data conceptualized

as time-series data sets. Such a modeling approach can be used for training applications such

as comparing a teacher’s and a student’s session with the CyberGlove, to measure the student’s

proficiency at following the teacher. Second, in this chapter we move a level up from

Some topics in this essay:
Neural Networks, , Zimmermann Zhang, Language ASL, Bayesian Classifier, Decision Tree, haptic data, Immersion Corporation, Environments Chapter, raw haptic data, raw haptic, Sign Language, Decision Trees, neural networks, sign recognition, level abstraction, bayesian classifier, classification technique, analysis haptic, analysis haptic data, levels abstraction, data stored, sign language recognition, american sign language, classification haptic data,

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Approximate Word count = 863
Approximate Pages = 3 (250 words per page double spaced)

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