Abstract
Hand signs are considered as one of the important ways to enter information into computers for certain tasks. Computers receive sensor data of hand signs for recognition. When using hand signs as computer inputs, we need to (1) train computer users in the sign language so that their hand signs can be easily recognized by computers, and (2) design the computer interface to avoid the use of confusing signs for improving user input performance and user satisfaction. For user training and computer interface design, it is important to have a knowledge of which signs can be easily recognized by computers and which signs are not distinguishable by computers. This paper presents a data- mining technique to discover distinct patterns of hand signs from sensor data. Based on these patterns, we derive a group of indistinguishable signs by computers. Such information can in turn assist in user training and computer interface design.
Original language | English (US) |
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Pages (from-to) | 188-196 |
Number of pages | 9 |
Journal | Ergonomics |
Volume | 46 |
Issue number | 1-3 |
DOIs | |
State | Published - Jan 15 2003 |
Keywords
- Computer interface design
- Data mining
- Hand signs
- User training
ASJC Scopus subject areas
- Human Factors and Ergonomics
- Physical Therapy, Sports Therapy and Rehabilitation