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.

Grip strength provides a quick and objective index of the functional integrity of the upper extremities. It is widely used as an assessment measure in physical and rehabilitation medicine. In this study, maximum voluntary grip strength of 20 college students wearing 5 different gloves were measured using Jamar hand dynamometer. The results show that maximum voluntary grip strength was generally reduced when wearing gloves as compared to bare-handed. More specifically, the grip strength was highest when wearing PVC coated glove or bare-handed and getting lowered as wrist band, rubber, leather, and cotton glove in these order. Depending on the measuring posture of grip strength, shoulder height with arm extended forward was higher than the elbow was flexed 90 degree. Moreover, subjects' demographic factors and hand dimensions were not closely related to the grip strength. It is thus recommended that the proper glove should be provided to reduce the negative consequences including dropping a tool, poorer control of a tool. lower quality work, and increased muscle fatigue and in turn to increase the user safety and satisfaction.

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.