The purpose of this study was to develop the pattern-making for Korean glove. To develop the pattern-making for glove this study comprehensive list of candidate hand data was reviewed and the manufacturers(career over th 15 years) were interviewed on the method of glove. The results of regression analysis(hand data) were as follows (unit: cm): wrist thumb tip length = middle finger length + 3.22, hand bread = 1.25 × middle finger length + 2.18, middle finger breadth at dist = 0.23 × index finger circumference + 0.4, maximum hand circumference = 3.15 × index finger circumference + 4.13, middle finger circumference = 0.91 × index finger circumference + 0.47, maximum hand thickness = 0.69 × index finger circumference －0.02. Hand measurements for glove pattern-making were developed: There were palmar hand length, hand circumference, index finger circumference and middle finger length.

In this paper, we present a wireless RFID glove in emotional learning method The Proposed wireless RFID glove consists of three parts RF wireless module, RFID reader, and RFID tags Objects tagged with a small passive RFID tag, can be sensed at short range

The purpose of this study was to develop the dimension of hand pattern-making for Korean glove. The glove pattern-making has difficult problem in combination of anthropometric and engineering aspects. In addition, existing dimension data are not enough for glove pattern-making. Therefore, to develop the dimension for glove this study comprehensive list of candidate hand data was reviewed and the manufacturers(career over the 15 years) were interviewed on the method of glove. The result of comparing between the structures in hand and existing glove pattern, there draw deduction from follows. Pattern-making for glove need size of hand length, thumb length, index finger length, middle finger length, ring finger length, hand circumference, thumb～ring finger circumference and maximum hand thickness.

The objective of this study was to analyse the antivibration characteristics of gloves by frequency band while operating light-weighted powered hand grinder. A methodology to estimate vibration isolation effectiveness of gloves was proposed on the basis of overall R.M.S. transmissibility characteristics. And overall R.M.S. transmissibilities of L-, M- and H-spectra were compared. Electric hand grinder was tested in the laboratory and attenuation performances of 3 different gloves(full finger antivibration glove, open finger antivibration glove, and cotton glove) were considered. Eight healthy male subjects were employed to polish metal plate with a tool. The results indicate that there was no significant difference among antivibration characteristics by frequency bands while operating light-weighted electric hand grinder.

This paper presents a novel knitted data glove system for pattern classification of hand posture. Several experiments were conducted to confirm the performance of the knitted data glove. To find better sensor materials, the knitted data glove was fabricated with stainless-steel yarn and silver-plated yarn as representative conductive yarns, respectively. The result showed that the signal of the knitted data glove made of silver-plated yarn was more stable than that of stainless-steel yarn according as the measurement distance becomes longer. Also, the pattern classification was conducted for the performance verification of the data glove knitted using the silver-plated yarn. The average classification reached at 100% except for the pointing finger posture, and the overall classification accuracy of the knitted data glove was 98.3%. With these results, we expect that the knitted data glove is applied to various robot fields including the human-machine interface.