An improved alphanumeric input algorithm using gloves Jeong-Hoon Shin and Kwang-Seok Hong School of Information and Communication Engineering, Sungkyunkwan University, Suwon, 440-746 Rep. Of Korea Email:
[email protected],
[email protected]
Abstract This paper describes an alphanumeric input algorithm using gloves. We list and discuss traditional algorithms and methods using a glove, then describe an improved algorithm using gloves. An efficiency test was conducted and the results were compared with other glove based devices and algorithms.
1.
Introduction
In this paper, a new glove-based text input device and improved algorithm are introduced to provide a text input for a wearable computer. Wearable computers are the next generation of portable machine. When worn, they provide constant access to various computing and communication resources. Wearable computers are generally composed of small sized PCs, display mounted on the head with wireless communication between hardware and input devices. Thus, input to small sized devices is becoming an increasingly crucial factor in development for the ever-more powerful embedded market. The purpose of this paper is to introduce the text input device for the wearable computers using gloves and an improved algorithm, and to assess its performance. Because of their device independent characteristics, proposed devices could be applied to all kinds of electronic applications. It could be applied to all kinds of wearable computers as well as desktop computers. In section 2, several devices for wearable computers using gloves are introduced. In section 3, we suggest an improved devices and key-in algorithm for wearable computers. Discussion and conclusion are given in section 4.
2.
Traditional glove based text input devices
The following subsections explain the main characteristics of traditional glove based text input devices. In these sections, we describe the features of each method, and compare between methods. - 206 -
2.1 Chording glove The Chording Glove employs pressure sensors for each finger of the right hand in a glove to implement chording input device. There is one key for each finger. Multiple keys are pressed simultaneously in various combinations to enter characters. A chord can be made by pressing the fingers against any surface. Almost all possible finger combinations are mapped to symbols, making it potentially hard to type them. Additional buttons, located along the index finger, are used to produce more than the 25 distinct characters. Figure 1 shows the external appearance of Chording Glove and Table 1 shows the key map of the Chording Glove for the English language.
Figure 1.External appearance of Chording Glove.
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Table 1. Key map of the Chording Glove for the English language. Chord
Shifts
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Index
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Little
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A weak point of this method is its difficulty to use. It needs more than 80 minutes to learn the entire chord set. After 11 hours of training, word input speed reached approximately 18 words per minute (wpm) whereas the character error rate amounted to 17%.
2.2 Finger-Joint gesture wearable keypad The Finger-Joint Gesture Wearable Keypad suggests viewing the phalanges of the fingers (besides the thumb) of one hand as the keys on phone keypad. Figure 2 shows the FingerJoint Gesture (FJG) Keypad glove.
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Figure 2.The Finger-Joint Gesture (FJG) Keypad glove. By holding the inside of the hand in front of you, and bending the fingers toward you and aligning the fingertips of the four fingers, a 4X3 matrix is similar in shape to the traditional telephone keypad. And FJG keypad employs the same layout as that encountered on any traditional mobile telephone. Nothing else has to be learned. The FJG concept is a generic way of combining the 12 keys of the keypad with 4+1 different functions. It can be used in a variety of different interfaces. A weak point of this method is the limited number of alphabets that can be aligned on the phalanges. To overcome this weak point, if the multiple numbers of alphabets are mapped on the same phalanges (one-to-many characters mapping) in the same mode (EX: ABC, DEF…), the user has to use multiple successive keystrokes on the same phalanx of the fingers. To generate the alphabet L, the thumb depresses the medial phalanx of the middle finger three times consecutively (see Figure 2).
2.3 Thumbcode “Thumbcode” method defines the touch of the thumb onto the fingers’ phalanges of the same hand as key strokes. Characters are signed or thumbed by pressing the tip of the thumb against one of the phalanges. This defines the twelve thumb states of Thumbcode. In combination with the twelve thumb states this gives a total of 96 basic Thumbcode. Figure 3 shows Thumbcode assignments. Each of the eight 3X4 arrays in Figure 3 should be visualized as being superimposed on the fingers of the right hand. In Figure 3, the four vertical bars mean four fingers of right-hand. Narrow space means that the adjacent fingers are closed. And regular space means that the adjacent fingers are opened. The four fingers can touch each other in eight different ways, each basically representing a mode, or modifier key that affects the mapping for the thumb touch. A weak point of this method also can be described as complexity of combining fingers. The user has to combine their fingers to generate Thumbcode in complex ways. As a result of this complexity, this method also needs training time to use fluently.
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Figure 3.Thumbcode Assignments view of right-hand palm.
3.
An improved glove based alphanumeric input algorithm
Key-to-symbol mapping methods can be divided into two classes. Exactly one key to one symbol (character) mapping (1 degree of freedom, DOF) method and one-to-many characters mapping (1.5 degree of freedom, DOF) method are typical key-to-symbol mapping methods. In a one-to-many characters mapping method, the user has to use multiple successive keystrokes to produce some characters. In this article, we propose an improved one-to-many characters mapping method. We can produce any character using a keystroke. If the user wants to produce a character “C” in a traditional one-to-many characters mapping method, the user has to use multiple successive keystrokes on the medial phalanx of the index finger. But, in the proposed method, the user can produce a character “C” using a keystroke on the medial phalanx of the index finger with a specific operator (third operator). First of all, we could decide the number of discrete operators and the layout of the key-tosymbol mapping according to the use of applications. In the proposed text input device, maximum number of the symbols can be mapped on a key depends on the number of using operators (the maximum number of used operators not exceeds 5). If we use 3 operators, we can map 3 characters on a key. Thus, the maximum number of characters can be mapped on the phalanges of the 4 fingers is 30. We can produce 30 different characters using a keystroke with a specific operator. This process could be finished up using the control unit in Figure 4.
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Figure 4.Key-to-Symbol mapping and the operators. If the user depresses the tip phalanx of the middle finger with a first operator, then the character “M” will be produced. And, if the user depresses the tip phalanx of the middle finger with a second operator, then the character “N” will be produced. And, if the user depress the tip phalanx of the middle finger, then character “O” will be produced, and so on. Key-to-symbol mapping method is very easy and simple. Thus, nothing else has to be learned.
4.
Discussion and conclusion
Nowadays, many systems adapt multi-modal human computer interfaces. The reason for using multi-modal HCI system is to create a more natural experience for the user by allowing him/her to use other methods of communication than just speech or just mouse, and aid the computer in understanding what the user wants by providing multiple modality streams that can disambiguate each other. In this paper, we proposed an improved alphanumeric input algorithm using gloves for the purpose of using as a human computer interface method. Although there are several benefits of using one-handed text input devices, there are clear-cut lines of input speed and error rate. To overstep these limits, we proposed the method and the device using two hands. The proposed method and experiment gave us the possibility of using gloves as a text input device. For the purposes of achieving popular use of the glove as a text input device, more convenient and swifter methods should be proposed.
References Markus Eisenhauer, Britta Hoffman, Doro Kretschmer. (2002), State of the Art Human-Computer Interaction, Giga Mobile project D2.7.1. Pratt, V. R. (1998), Thumbcode, http://boole.stanford.edu/thumbcode
A
Device-Independent
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Digital
Sign
Language,
URL:
Goldstein, M. and Chincholle, D. (1999), Finger-Joint Gesture Wearable Keypad, in Second Workshop on Human Computer Interaction with Mobile Devices. J. Noyes. (1983), The QWERTY keyboard: A review, Int. J. Man-Mach Studies 18(3): 265-281. Robert Rosenberg and Mel Slater. (1999), The Chording Glove: A Glove-Based Text Input Device, IEEE Transactions on systems, Man, And Cybernetics-Part C: Applications and reviews. K. M. Potosnak. (1988), Keys and keyboards,. Handbook of Human-Computer Interaction: 475-494
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