• Title/Summary/Keyword: Mobile phone camera

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Effects of Wheelchair Back Support and Ischial Pad on Neck, Trunk Angle and Chest Expansion in Stroke Patients (휠체어 허리 지지대와 궁둥 패드가 뇌졸중 환자의 목, 몸통 각도 및 가슴우리 확장에 미치는 영향)

  • An, Jae-Young;Jeon, Kyung-Soo;Choi, Hye-Jin;Park, Jae-Hong;Kwon, Jeong-Eun;Shin, Ji-Yeon;Sin, Han-Sol;Gwon, Ji-Su;Jeong, Hye-Ji;Park, Shin-Jun
    • Journal of Digital Convergence
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    • v.16 no.8
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    • pp.301-309
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    • 2018
  • The purpose of this study was to investigate the immediate effect of lumbar support and ischial pad on neck, trunk angle and chest expansion for stroke patients using wheelchair. Fifteen stroke patients were measured repeatedly when a lumbar support using(L support), a Ischial pad using(I Pad), a Lumbar support with ischial pad using(L With I), and non using it(Non using). The measurement of the neck and trunk angle was confirmed using a mobile phone camera, and chest expansion was performed using a tapeline. L With I increased significantly in neck and trunk angle and lower chest expansion than non using. This study shows that simultaneous use of lumbar support and ischial pad for stroke patients using wheelchair can increase the neck and trunk angle, chest expansion immediately. Future studies will need to identify more long-term changes by continuing intervention with more subjects.

Development of an IoT Device for Detecting Escherichia coli from Various Agri-Foods and Production Environments (IoT 적용 대장균 검출기 개발과 농식품 및 생산환경에 적용)

  • Nguyen, Bao Hung;Chu, Hyeonjin;Kim, Won-Il;Hwang, Injun;Kim, Hyun-Ju;Kim, Hwangyong;Ryu, Kyoungyul;Kim, Se-Ri
    • Journal of Food Hygiene and Safety
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    • v.34 no.6
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    • pp.542-550
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    • 2019
  • To detect Escherichia coli from agri-food and production environments, a device based on IoT (internet of things) technology that can check test results in real time on a mobile phone has been developed. The efficiency of the developed device, which combines an incubator equipped with a UV lamp, a high-resolution camera and software to detect E. coli in the field, was evaluated by measuring the device's temperature, detection limit, and detection time. The device showed a difference between its programmed temperature setting and actual temperature of about 1.0℃. In a detection limit test performed with a single-colony inoculation, a color change to yellow and a florescent signal were detected after 12 and 15 h incubations, respectively. The incubation time also decreased along with increasing bacteria levels. When applying the developed method and device to various samples, including utensils, gloves, irrigation water, seeds, and vegetables, detection rates of E. coli using the device were higher than those of the Korean Food Code method. These results show that the developed protocol and device can efficiently detect E. coli from agri-food production environments and vegetables.

Change Attention-based Vehicle Scratch Detection System (변화 주목 기반 차량 흠집 탐지 시스템)

  • Lee, EunSeong;Lee, DongJun;Park, GunHee;Lee, Woo-Ju;Sim, Donggyu;Oh, Seoung-Jun
    • Journal of Broadcast Engineering
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    • v.27 no.2
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    • pp.228-239
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    • 2022
  • In this paper, we propose an unmanned vehicle scratch detection deep learning model for car sharing services. Conventional scratch detection models consist of two steps: 1) a deep learning module for scratch detection of images before and after rental, 2) a manual matching process for finding newly generated scratches. In order to build a fully automatic scratch detection model, we propose a one-step unmanned scratch detection deep learning model. The proposed model is implemented by applying transfer learning and fine-tuning to the deep learning model that detects changes in satellite images. In the proposed car sharing service, specular reflection greatly affects the scratch detection performance since the brightness of the gloss-treated automobile surface is anisotropic and a non-expert user takes a picture with a general camera. In order to reduce detection errors caused by specular reflected light, we propose a preprocessing process for removing specular reflection components. For data taken by mobile phone cameras, the proposed system can provide high matching performance subjectively and objectively. The scores for change detection metrics such as precision, recall, F1, and kappa are 67.90%, 74.56%, 71.08%, and 70.18%, respectively.

The Effect of Spiral Balance Taping on Postoperative Sequelae in Breast Cancer : Case study (스파이랄 발란스 테이핑이 유방암 환자의 수술 후 후유증에 미치는 영향 : 사례연구)

  • Su-Ji Kang;Dae-Hee Lee;Cheul Jang;Back-Vin Lim
    • Journal of The Korean Society of Integrative Medicine
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    • v.12 no.3
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    • pp.37-47
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    • 2024
  • Purpose : Cancer survivors often suffer from postoperative sequelae. the diagnosing and provision of manual therapy using spiral taping significantly improves the quality of life of cancer patients. The aim of this case study is to investigate the immediate effects of spiral taping on pain, range of motion (ROM), chemotherapy-induced peripheral neuropathy (CIPN), and lymphedema following breast cancer surgery. Methods : The taping techniques were performed as follows by spiral taping. The measurements were taken before, in the middle, and after taping using a mobile phone camera, tape measure, and a numerical rating score (NRS). The evaluation employed a single-group pre-post design based on a primitive experimental design. Results : Out of four patients, all four exhibited Reverse circle flow energy (RCFE), Passive cervical right (Rt) rotation test, anterior-posterior movement pattern, nerve type (+), cold energy (CE), sangcho acupuncture point, blood clot, hwal point. Comparing before and after treatment, almost all values were reduced to zero after treatment in terms of pain complaints. The lack of range of motion (ROM) caused by the shortened tissue after surgery did not increase. The range of motion (ROM) lost due to pain returned to normal. The circumference of lymphedema did not show a tendency. The symptoms of CIPN improved. Conclusion : There was a significant change in joint range of motion, with pain decreasing, but there were structural limitations in the tissue due to total resection, and the chemotherapy-induced peripheral neuropathy scale. It was effectively treated surgical site pain, axillary membrane syndrome-induced pain, and unexplained pain. While there was a treatment effect for lymphedema in the evaluation of circumference values, there was no significant change in circumference. There was a significant effect on chemotherapy-induced peripheral neuropathy, particularly in treating numbness in the feet, which is a side effect of TC anticancer drugs. This case study found that spiral balance taping provides a rapid therapeutic effect for most side effects in patients who have undergone total breast cancer resection. However, the generalization is limited due to the small sample size, and further research is needed to determine the extent to which the effects of one treatment are maintained.

Accelerometer-based Gesture Recognition for Robot Interface (로봇 인터페이스 활용을 위한 가속도 센서 기반 제스처 인식)

  • Jang, Min-Su;Cho, Yong-Suk;Kim, Jae-Hong;Sohn, Joo-Chan
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.53-69
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    • 2011
  • Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.