Earticle

The purpose of this study is to find the standard value of hand width, of grip strength and of pinch strength by age, sex, and by left hand and right hand and also to find how the general characteristics influences grip strength and pinch strength. Martin Vigorimeter (List No. 17-27-01) was used for measuring grip strength, and the pinch gauge (0∼30 lbs) of B&L engineering for measuring pinch strength. The subjects of this study are the children at the age of three to seven years, who attending the babies' play room, kindergarten and the primary school in Seoul and the Kyungki province area. They all were normally developed without any significant neurology problem. wo hundred girls and two hundred boys were partifipated in this study. They were divided into ten subgroups according to the age of six month interval. Each group consisted of forty children of twenty boys and twenty girls. Analysis of data presents the technical statistics upon the hand width of right and left hand and the grip strength and pinch strength according to the age and sex. Multiple regression analysis using mixed liner model was operated in order to find how the general characteristics (of the age, sex, and side of hand) influence hand width, grip strength, and pinch strength individually. Also, we calculated the correlation among hand width, grip strength and pinch strength under the condition of controlling general characteristics; and to find correlation between the right hand and the left hand of the age and sex, we carried out paired t-test and came to the conclusion as follows: 1.　Hand width is significantly increased with the increase of age (p<0.01). The increase of hand width according to age, boy is wider than that of girl significantly (p<0.01), and the right hand is wider than that of the left hand significantly (p<0.01). 2.　Grip strength is significantly increased as the age and hand width increased (p<0.01). The increase of grip strength according to the age, boy is stronger than that of girl significantly (p<0.01), and grip strength of the right hand is stronger than that of the left hand(p<0.01). 3.　Three-jaw pinch strength is increased as the age, hand width and grip strength are increased(p<0.01). But there is no significant difference of three-jaw pinch strength according to sex and the side of hand(p>0.05). 4.　Tip pinch strength is significantly increased as the age and grip strength are increased(p<0.05). The increase of tip pinch strength according to the age, boy is stronger than that of girl significantly (p<0.05), but there is no significant difference between the right hand and the left hand(p>0.05). 5.　Lateral pinch strength is significantly increased as the age and grip strength are increased(p<0.01). But the increase of lateral pinch strength, there is no significant difference according to the hand width, sex and the side of hand(p>0.05). 6.　The test of correlation among hand width, grip strength and pinch strength showed the correlation between grip strength and pinch strength was stronger than the correlation between hand width and pinch strength(0.3<r<0.7). There was strong correlation between each pinch strength(0.3<r<0.7). Above all, the correlation of three-jaw pinch strength and tip pinch strength was strongest(0.7<r<1.0). 7.　The test of hand width according to the age and sex, and the difference between the right hand and the left hand in grip strength and pinch strength showed that there was significant difference against all the test of hand width, of grip strength, and of pinch strength in the age group from seven years and six months to seven years and eleven months than the age group under six years, specially in girls group(p<0.05).

HCI 분야에서 대표적인 손 제스처 인식은 IT기기의 개발과 더불어 사용자와 기기 간의 상호작용 및 정보교환을 위한 방법으로 주목받고 있다. 영상 처리를 통한 손 제스처 인식에서 손바닥 영역 검출은 처리속도 및 인식률 향상에 기여하는 핵심 처리 과정이다. 본 논문에서는 손바닥 영역 검출(palm area detection)을 위해 손과 손목을 영상 분할(image segmentation) 하는 새로운 방법을 제안한다. 손의 해부학적 특성으로 가장 넓은 폭이 발생하는 엄지와 소지의 장골 간격을 손 영상의 수평 투사 히스토그램으로 계산 후 이 간격을 지름으로 하는 원을 그려 손바닥 영역을 검출한다. 이 방법의 우수성을 검증하기 위하여 다단 형판정합(multiple stage template matching)을 사용해 10가지 손 제스처에 대해 기존 방법 4가지와 인식 성능을 비교 평가한다. 손 제스처 인식에 관련한 연구가 다양하나 손바닥 영역 검출에 특화된 성능 비교 문헌이 저조함을 강조한다.

In the HCI, hand gesture recognition is attracting attention as a method for interaction and information exchange between users and devices along with the development of IT devices. In hand gesture recognition through image processing, palm region detection is a key process contributing to improvement of processing speed and recognition rate. In this paper, we propose a new method for image segmentation between the hand and wrist for palm area detection. The anatomical characteristics of the hand are used to calculate the distance between the iliac bones of the thumb and little finger, which have the widest width, by the horizontal projection histogram of the hand image, and then the palm area is detected by drawing a circle having the width as the diameter. In order to verify the superiority of this method, multiple stage template matching is used to compare and evaluate recognition performance against the four conventional methods for 10 hand gestures. Note that the literatures to offer palm area detection performance evaluation are few although there are many studies on hand gesture recognition.

Purpose: The purpose of this study was to investigate the most effective exercise position of Latissimus dorsi's activities during Pull up, Push up and Lat pull down among few positions of hand grips(pronation, Supination and neutral grip) and grip widths(30cm, 60cm) based on EMG activities. Method: 10 healthy adults were participated in this study and the surface EMG activities of the Latissimus dorsi were measured during Pull up, Push up and Lat pull down exercise according to specific hand grip and grip width positions. The maximum and mean value of Latissimus dorsi's EMG activities at all positions were recorded and analysed by ONE-WAY REAPTED ANOVA. Results: The showed that the most Latissimus dorsi's activities is during Pull up exercise. Main results are as follows 1)maximum value: For Pull up, among all studied positions, Rt Latissumus dorsi, position of Supinated grip and 60cm grip width showed strongest muscle activation based on maximum EMG value. Statistical significance was assumed at p<.05. 2)mean value: For Pull up, among all studied positions, Both Latissimus dorsi, position of pronated grip and 60cm grip width showed strongest muscle activation based on mean EMG value. Statistical significance was assumed at p<.05. Conclusion: Therefore, taking the results of this study, Pull up exercise would be the best exercise of Latissimus dorsi's activation. It is recommended to do in pronated grip position and 60cm grip width during Pull up to make body fit.