• Journal of the Ergonomics Society of Korea
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• v.26 no.3
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• pp.59-65
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• 2007

In this study, six grip spans (45mm-65mm) were tested to evaluate the effects of handle grip span and user's hand size on maximum grip strength, individual finger force, and subjective ratings of comfort using a digital dynamometer with individual force sensors. Forty-six males were assigned into three hand size groups according to their hand lengths. Results showed that overall 55mm and 50mm grip spans were the most comfortable sizes and associated with the highest grip strength in the maximum grip force exertions, whereas 65mm grip span was rated as the least comfortable size as well as the lowest grip strength. In the interaction effect of grip span and hand size, small and middle hand sized participants rated the best preference and the least preference grip spans differently with large hand sized participants. With respect to the analysis of individual finger force, the middle finger force was the strongest and the highest contribution to the total finger force, followed by ring, index and little fingers. In addition, it was noted that each finger had a different optimal grip span for exerting maximum force resulting in a bowed contoured shaped handle for two-handle hand tools. Thus, the grip spans for two-handle hand tools might be designed according to the users' hand and finger anthropometrics to maximize performance and subjective perception of comfort.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.91-97
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• 2013

A finger-gesture remote controller using the single camera is implemented in this paper, which is base on the recognition of finger number and finger moving direction. Proposed method uses the transformed YCbCr color-difference information to extract the hand region effectively. The number and position of finger are computer by using a double circle tracing method. Specially, a user continuous-command can be performed repeatedly by recognizing the finger-gesture direction of single shape. The position information of finger enables a user command to amplify a same command in the User eXperience. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the our proposed method, after applying to the commercial video player software as a remote controller. As a result, the proposed method showed the average 89% recognition ratio by the user command-mode.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1686-1694
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• 2014

In this paper, a new scheme to recognize a finger shape in the depth image captured by Kinect is proposed. Rigid transformation of an input finger shape is pre-processed for its robustness against the shape angle of input fingers. After extracting contour map from hand region, observing the change of contour pixel location is performed to calculate rotational compensation angle. For the finger shape recognition, we first acquire three pixel points, the most left, right, and top located pixel points. In the proposed algorithm, we first acquire three pixel points, the most left, right, and top located pixel points for the finger shape recognition, also we use geometrical features of human fingers such as Euclidean distance, the angle of the finger and the pixel area of hand region between each pixel points to recognize the finger shape. Through experimental results, we show that the proposed algorithm performs better than old schemes.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.242-249
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• 2019

Forearm electromyography (EMG) generated by wrist movements has been widely used to develop an electrical prosthetic hand, but EMG generated by finger movements has been rarely used even though 20% of amputees lose fingers. The goal of this study is to improve the classification performance of different finger movements using a deep learning algorithm, and thereby contributing to the development of a high-performance finger-based prosthetic hand. Ten participants took part in this study, and they performed seven different finger movements forty times each (thumb, index, middle, ring, little, fist and rest) during which EMG was measured from the back of the right hand using four bipolar electrodes. We extracted mean absolute value (MAV), root mean square (RMS), and mean (MEAN) from the measured EMGs for each trial as features, and a 5x5-fold cross-validation was performed to estimate the classification performance of seven different finger movements. A long short-term memory (LSTM) model was used as a classifier, and linear discriminant analysis (LDA) that is a widely used classifier in previous studies was also used for comparison. The best performance of the LSTM model (sensitivity: 91.46 ± 6.72%; specificity: 91.27 ± 4.18%; accuracy: 91.26 ± 4.09%) significantly outperformed that of LDA (sensitivity: 84.55 ± 9.61%; specificity: 84.02 ± 6.00%; accuracy: 84.00 ± 5.87%). Our result demonstrates the feasibility of a deep learning algorithm (LSTM) to improve the performance of classifying different finger movements using EMG.

• Archives of Plastic Surgery
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• v.49 no.6
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• pp.760-763
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• 2022

The dorsal metacarpal artery perforator flap is a flap that rises from the hand dorsum. Owing to its reliability and versatility, this flap is used as a workhorse for finger defect. However, to cover the radial-volar defect of the proximal interphalangeal joint (PIPJ) of the index finger, a longer flap is required than before. Here, we introduce the oblique extended reverse first dorsal metacarpal artery (FDMA) perforator flap to cover the radial-volar aspect defect of the index finger. A 45-year-old man got injured to the radial-volar defect of PIPJ of the left index finger caused by thermal press machine. The wound was 2 × 1 cm in size, and the joint and bone were exposed. We used FDMA perforator from anastomosis with palmar metacarpal artery at metacarpal neck. Since the defect was extended to the volar side, the flap was elevated by oblique extension to the fourth metacarpal base level. The fascia was included to the flap, and the flap was rotated counterclockwise. Finally, PIPJ was fully covered by the flap. Donor site was primarily closed. After 12 months of operation, the flap was stable without complication and limitation of range of motion. The oblique extended reverse FDMA perforator flap is a reliable method for covering the radial-volar defect of the PIPJ of the index finger. This flap, which also has an aesthetic advantage, will be a good choice for hand surgeons who want to cover the PIPJ defect of the index finger using a nonmicrosurgical option.

• Journal of the Korean Wood Science and Technology
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• v.31 no.2
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• pp.84-91
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• 2003

In this study, the three species (Populus euramericana, Pinus densiflora and Quercus variabilis) were cut to difference (0, 0.15, 0.3, 0.45 mm) between the size of tip and that of root of the finger (DSTR) and jointed with poly vinyl acetate (PVA) and resorcinol-phenol resin (RPR). We described the relationship between the bending strength properties of finger DSTR and the acoustic emission (AE) generated during the bending test. The results were as follows: The AE generation time of finger-jointed specimens with RPR adhesive was earlier than that with PVA adhesive. The AE cumulative event count of finger-jointed specimens with RPR adhesive continuously increased with increasing load and the event count was much more than that with PVA adhesive. Also, the AE cumulative event count for resorcinol-phenol resin adhesive obtained from low load level was abundant. The AE wave in finger-jointed specimens with RPR adhesive could be detected in the below proportional limit load. Therefore, AE signals from bending test are useful for the estimation of strength in finger DSTR specimens.

• Proceedings of the Korean Biophysical Society Conference
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• 1998.06a
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• pp.11-11
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• 1998

Zinc fingers of Cys$_2$His$_2$ class constitute one of the most common DNA binding motifs in eukaryotes. Unlike other DNA binding motifs, zinc finger proteins recognize very diverse DNA sites, and their sequence specificities can be systematically changed by phage display.(omitted)

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.575-576
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.72-75
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• 2004

In this paper, a finger-click recognition method is proposed to improve the recognition performance for finger-clicking of a wearable input device, called $SCURRY^{TM}$. The proposed method is composed of three parts including feature extraction part, valid click discrimination part, and cross-talk avoidance part. Two types of MEMS inertial sensors are embedded into the wearable input device to measure the angular velocity of a hand (hand movement) and the acceleration rates at the ends of fingers (finger-click motion). The experiment applied to the $SCURRY^{TM}$ device shows the improved stability and performance.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.247-250
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• 2000

This paper proposes a finger crease pattern identification algorithm utilizing a clustering method. The algorithms has been developed for the use of biometric person identification system. Since the finger crease pattern may be well-imaged utilizing low cost imaging devices such as low-end CCD camera with LED lighting, the feasibility of commercialization of the algorithm and the system utilizing the algorithm may be well justified if the finger crease pattern is a reasonable choice for the biometric feature. In this paper, we exploit this possibility and show the potential of using the finger crease pattern as a feature for biometric person identification.