• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.212-226
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• 2014

This paper presents the design and implementation of a pipelined architecture and a method for real-time human detection using depth image from a Time-of-Flight (ToF) camera. In the proposed method, we use Euclidean Distance Transform (EDT) in order to extract human body location, and we then use the 1D, 2D scanning window in order to extract human joint location. The EDT-based human extraction method is robust against noise. In addition, the 1D, 2D scanning window helps extracting human joint locations easily from a distance image. The proposed method is designed using Verilog HDL (Hardware Description Language) as the dedicated hardware architecture based on pipeline architecture. We implement the dedicated hardware architecture on a Xilinx Virtex6 LX750 Field Programmable Gate Arrays (FPGA). The FPGA implementation can run 80 MHz of maximum operating frequency and show over 60fps of processing performance in the QVGA ($320{\times}240$) resolution depth image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1854-1868
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• 2018

A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies.

• The Journal of Korean Physical Therapy
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• v.13 no.3
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• pp.637-642
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• 2001

Hershel found out Infrared for the first time, in the Industrial Revolution the Infrared and FlR had been begun to use making products. FIR with low temperature can deeply penetrate on the human body composed things without troublesome. since FIR has effectively operated on the human body at low temperature (35-40$^{\circ}$C). When FIR penetrated on the human body, it would inhibit the abnormal genes and cells expression, and then information of DNA and RNA would be reexpressed for arranging DNA and RNA abnormal state. As FIR's receptors in the body, it colud be presumed that N-glycosyl linkage of purine and deoxyribose, RNA splicing process. and Heat shock protein. To radiate optimized FIR, in this study, we made the FIR radiation compound and instrument for unharming biological things. According to the results, the FIR radiation to E. coli., it did not induce genetic mutations and change the survival rate of E.coli.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.6
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• pp.341-345
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• 2000

This paper analysed the induced electric field of human body under the 765 kV transmission line considering permittivity and conductivity. As permittivity of human body is very high as 106 at 60 Hz, special numerical computation technique is Surface Charge Method(SCM) for composite media with extremely different properties is applied to reduce calculation error of induced electric field inside the human body.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2327-2347
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• 2018

Human actions can be recognized from depth sequences. In the proposed algorithm, we initially construct depth, motion maps (DMM) by projecting each depth frame onto three orthogonal Cartesian planes and add the motion energy for each view. The body part of the action (BPoA) is calculated by using bounding box with an optimal window size based on maximum spatial and temporal changes for each DMM. Furthermore, feature vector is constructed by using BPoA for each human action view. In this paper, we employed an ensemble based learning approach called Rotation Forest to recognize different actions Experimental results show that proposed method has significantly outperforms the state-of-the-art methods on Microsoft Research (MSR) Action 3D and MSR DailyActivity3D dataset.

• ETRI Journal
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• v.33 no.4
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• pp.569-579
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• 2011

This paper presents a novel approach for human activity recognition (HAR) using the joint angles from a 3D model of a human body. Unlike conventional approaches in which the joint angles are computed from inverse kinematic analysis of the optical marker positions captured with multiple cameras, our approach utilizes the body joint angles estimated directly from time-series activity images acquired with a single stereo camera by co-registering a 3D body model to the stereo information. The estimated joint-angle features are then mapped into codewords to generate discrete symbols for a hidden Markov model (HMM) of each activity. With these symbols, each activity is trained through the HMM, and later, all the trained HMMs are used for activity recognition. The performance of our joint-angle-based HAR has been compared to that of a conventional binary and depth silhouette-based HAR, producing significantly better results in the recognition rate, especially for the activities that are not discernible with the conventional approaches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.329-331
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• 2021

Recently, as various cases of using deep learning in the health-care field are increasing, functions such as electrocardiogram examination and body composition analysis through wearable device can be provided to provide rational decision-making and a process tailored to the individual. In order to utilize deep learning, it it most important to secure refined data, and this data is being made through human intervention or unsupervised learning. In this paper, we propose a model that conducts unsupervised learning by clusters according to gender and age using human body data such as chest and waist circumferences, which are easy to measure, and classifies them with CNN. For data, the 7th human body data provided by Korean Agency for Technology and Standards was used. Through this, it it thought that it can be applied to various application cases such as personalized body shape management service and obesity analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1504-1508
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• 2003

The functional behavior of each body segments were investigated with respect to human standing posture when they were exposed to the horizontal vibration in the sagittal plane. This study is processed by experimental approach. The data is analyzed, both in the time domain and in the frequency domain. Random and multisinusoidal vibration was used as input. The ankle, hip, and head were employed as the significant body segments. High relative movements were present between hip and head, and there was no significant relationship between ankle and head. Variations of visual input produced a significant postural effect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1077-1093
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• 2013

This paper proposes a new network coordinator node design to select the most suitable wireless technology for WBANs by using fuzzy logic. Its goal is to select a wireless communication technology available considering the user/application requirements and network conditions. A WBAN is composed of a set of sensors placed in, on, or around human body, which monitors the human body functions and the surrounding environment. In an effort to send sensor readings from human body to medical center or a station, a WBAN needs to stay connected to a local or a wide area network by using various wireless communication technologies. Nowadays, several wireless networking technologies may be utilized in WLANs and/or WANs each of which is capable of sending WBAN sensor readings to the desired destination. Therefore, choosing the best serving wireless communications technology has critical importance to provide quality of service support and cost efficient connections for WBAN users. In this work, we have developed, modeled, and simulated some networking scenarios utilizing our fuzzy logic-based NCN by using OPNET and MATLAB. Besides, we have compared our proposed fuzzy logic based algorithm with widely used RSSI-based AP selection algorithm. The results obtained from the simulations show that the proposed approach provides appropriate outcomes for both the WBAN users and the overall network.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.2078-2079
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• 2009

This research suggests the framework for human body learning system using various forms of bidirectional interfaces. The existing systems mostly use the limited and unidirectional methods which are merely focused on the visual information. Our system provides more realistic visual information using 3D organ models from the real human body. Also we combine the haptic and augmented reality techniques into our system for wider range of interaction means. Through this research, we aim to overcome the limitation of existing science education systems and explore the effective scheme to fuse the real and virtual educational environment into one.