• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.1
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• pp.45-49
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• 2013

High frequency system has been used for the purpose of skin care and obesity treatment, by high-frequency energy is applied to the human body generates deep heat. Conventional high frequency system could not selection control by depending on the body load fluctuations. Such as burns and side effects have been reported by system instability and then therapeutic effect is insufficient. During treatment, objective information about the status of the patient was no. Because of treatment methods are subjective, and so tailored treatments were impossible. In this paper, high frequency medical system with sinusoidal frequency characteristics without distortion of the Push pull switching scheme for pain relief therapy was designed. And control circuit that was designed by feedback using the output changes according to the body-load fluctuation. Last, power circuit for efficient control the heat generated from the hardware was proposed.

• Journal of information and communication convergence engineering
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• v.16 no.2
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• pp.130-134
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• 2018

Wireless capsule endoscopy (WCE) is considered as recent technology for the detection cancer cells in the human digestive system. WCE sends the captured information from inside the body to a sensor on the skin surface through a wireless medium. In WCE, the design of low-power consumption devices is a challenging topic. In the Shannon-Nyquist sampling theorem, the number of samples should be at least twice the highest transmission frequency to reconstruct precise signals. The number of samples is proportional to the power consumption in wireless communication. This paper proposes compressive sensing as a method to reduce power consumption in WCE, by means of a trade-off between samples and reconstruction accuracy. The proposed scheme is validated under channel constraints, expressed as the realistic human body path loss. The results show that the proposed scheme achieves a significant reduction in WCE power consumption and achieves a faster computation time with low signal error reconstruction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4385-4399
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• 2021

The Internet of Things (IoT) eHealth systems composed by Wireless Body Area Network (WBAN) has emerged recently. Sensor nodes are placed around or in the human body to collect physiological data. WBAN has many different applications, for instance health monitoring. Since the limitation of the size of the battery, besides speed, reliability, and accuracy; design of WBAN protocols should consider the energy efficiency and time delay. To solve these problems, this paper adopt the end-edge-cloud orchestrated network architecture and propose a transmission based on reinforcement algorithm. The priority of sensing data is classified according to certain application. System utility function is modeled according to the channel factors, the energy utility, and successful transmission conditions. The optimization problem is mapped to Q-learning model. Following this online power control protocol, the energy level of both the senor to coordinator, and coordinator to edge server can be modified according to the current channel condition. The network performance is evaluated by simulation. The results show that the proposed power control protocol has higher system energy efficiency, delivery ratio, and throughput.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.401-404
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• 2008

In livestock, diagnosis of disease is found on body temperature variation like a human. In case of cattle, body temperature variation can estimate disease that milk fever, toxication, diarrhea, dyspepsia, chronic enteritis, influenza, pneumonia, anthrax. So we are suggested the temperature measurement system for livestock. This system will be useful to a stock farmer and alternative that a worker.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1305-1308
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• 2005

Recently, the basic research which is supported by engineering has been studied in order to develop oriental medicine scientifically. However, the research only has been limited to quantization, visualization and generalization of biological signal. In this paper, we studied about the effects to 12 Kyungmaks of Body based on meridian theory in oriental medicine after Taichi practice. we measured the heating time on the key measuring point of the meridian of the human body's left and right by using heating machine. After taichi practice than other stimulation, experimental results showed that disharmony state of meridian had changed to harmony state more quickly.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1690-1697
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• 2016

In a beacon-enabled Zigbee network, the slotted CSMA/CA mechanism based on the super frame structure fairly provides communication chance for each node and makes a reasonable usage of the available energy. In the case of wireless nano sensors that are implanted into the target human body area for detecting disease symptoms or virus, such a nano-network requires a similar type of channel sharing and transmission of short length event-driven data. In this paper, for nano-network's in-body applications, we aim to design conceptually a new super frame derived from the existing beacon-enabled Zigbee MAC protocol. And we analyze the efficiency of the proposed super frame in the aspect of practical deployment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1964-1967
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• 2021

Recently, to improve the effectiveness of education to learn from textbooks, immersive 3D environments such as virtual reality(VR) has been widely used for education. In this paper, in order to intuitively present education about content scenarios on changes in the human body according to food intake, we consist an immersive virtual reality environment to express the same life-size organs. The participants in our educational system showed higher results in all items compared to the existing textbook-based education such as immersion, understanding, and quality of education program. Also it was found the importance of interactivity to increase the effectiveness of immersive class.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.111-118
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• 2022

In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Journal of information and communication convergence engineering
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• v.11 no.2
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• pp.124-131
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• 2013

Extraction and representation of postures and/or gestures from human activities in videos have been a focus of research in this area of action recognition. With various applications cropping up from different fields, this paper seeks to improve the performance of these action recognition machines by proposing a shape-based silhouette-edge descriptor for the human body. Information entropy, a method to measure the randomness of a sequence of symbols, is used to aid the selection of vital key postures from video frames. Morphological operations are applied to extract and stack edges to uniquely represent different actions shape-wise. To classify an action from a new input video, a Hausdorff distance measure is applied between the gallery representations and the query images formed from the proposed procedure. The method is tested on known public databases for its validation. An effective method of human action annotation and description has been effectively achieved.