• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.33-39
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• 2019

In this paper, we propose a parametric model for analyzing the motion information obtained from the acceleration sensors to measure the activity of the human body. The motion of the upper body and the lower body does not occur at the same time, and the motion analysis method using a single motion sensor involves a lot of errors. In this study, the 3-axis accelerometer is attached to the arms and legs, the body's activity data are measured, the momentum of the arms and legs are calculated for each channel, and the linear predictive coefficient is obtained for each channel. The periodicity of the upper body and the lower body is determined by analyzing the correlation between the channels. The linear predictive coefficient and the periodic value are used as data to measure the type of exercise and the amount of exercise. In the proposed method, we measured four types of movements such as walking, stair climbing, slow hill climbing, and fast hill descending. In order to verify the usefulness of the parameters, the recognition results are presented using the linear predictive coefficient and the periodic value for each motion as the neural network input.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.215-221
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• 2018

In this paper, a comprehensive design of HBC(Human Body Communication) system for capsule endoscope is presented. First, we propose a method of combining the signals received from multiple patches attached to the body of patient through differential operation and derive the signal SNR mathematically. To synchronize HBC transmission signal sent from capsule, we analyzed coarse timing synchronization method using PN code and fine timing synchronization performance among Manchester, NRZ and RZ modulation method using ZCD(Zero Crossing Detector). In addition, we evaluated the equalization performance of HBC signal frame in Rician and Rayleigh channel environments by applying LMS and RLS algorithm.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.142-148
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• 2011

Because currently available wireless technologies are not appropriate for wireless body area networks (WBANs), the IEEE 802.15.6 standard was introduced by the IEEE 802.15.6 Task Group to satisfy all the requirements for a monitoring system that operates on, in, or around the human body. In this work, we develop an analytical model for evaluating the performance of an IEEE 802.15.6-based WBAN under saturation condition and a noisy channel. We employ a three-dimensional Markov chain to model the backoff procedure as specified in the standard. Probability generating functions (PGFs) are used to compute the performance descriptors of the network. The results obtained from the analytical model are validated by simulation results. Our results indicate that under saturation condition, the medium is accessed by the highest user priority nodes at the vast majority of time while the other nodes are starving.

• 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 IKEEE
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• v.24 no.1
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• pp.120-126
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• 2020

We present a user recognition method using human body impulse response signals. The body compositions vary from person to person depending on the portion of water, muscle, and fat. In the body communication study, the body has been interpreted circuit models using capacitance and resistances, and its characteristics are determined by the body compositions. Therefore, the individual body channel is unique and can be used for user recognition. In this paper, we applied pseudo impulse signals to the left hand and recorded received signals from the right hand. The empirical mode decomposition (EMD) method removed noise from the received signals and 10 peak values are extracted. We set the differences between peak amplitudes as a key feature to identify individuals. We collected data from 6 subjects and achieved accuracy of 97.71% for the user recognition application.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.5-52
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• 2002

In this paper, we develop analysis models for classification of temporal data from human subjects. The study focuses on the analysis of electroencephalogram (EEG) signals obtained during various emotional states. We demonstrate a generally applicable method of removing EOG and EMG artifacts from EEGs based on independent component analysis (ICA). All EEG channel maps were interpolated from 10 EEG subbands. ICA methods are based on the assumptions that the signals recorded on the scalp are mixtures of signals from independent cerebral and artifactual sources, that potentials arising from different parts of the brain, scalp and body are summed linearly at the electrodes and that prop...

• Journal of the Korean Society for Precision Engineering
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• v.31 no.6
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• pp.527-534
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• 2014

The control system of human torso model and driving system of stethoscope for physical assessment trainer are developed. The detecting characteristics of circular pickup coil which is driven by square wave voltage signal with resonance frequency of LC circuits are investigated and it is confirmed that the pickup coil can detect the existence of chestpiece near the coil region. The control system of human torso model is composed of 8 channel pickup coils, Mp3 and Bluetooth module. The driving system of stethoscope is composed of chestpiece with contact switch and Bluetooth headset. The chestpiece detecting algorithm check the contact of chestpiece with human body model first and excite the pickup coil sequentially to find the location. The proposed system can be applied the physical assessment trainer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3182-3198
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• 2019

Vision-based Human Pose Estimation has been considered as one of challenging research subjects due to problems including confounding background clutter, diversity of human appearances and illumination changes in scenes. To tackle these problems, we propose to use a new multi-stage convolution machine for estimating human pose. To provide better heatmap prediction of body joints, the proposed machine repeatedly produces multiple predictions according to stages with receptive field large enough for learning the long-range spatial relationship. And stages are composed of various modules according to their strategic purposes. Pyramid stacking module and dilation module are used to handle problem of human pose at multiple scales. Their multi-scale information from different receptive fields are fused with concatenation, which can catch more contextual information from different features. And spatial and channel information of a given input are converted to gating factors by squeezing the feature maps to a single numeric value based on its importance in order to give each of the network channels different weights. Compared with other ConvNet-based architectures, we demonstrated that our proposed architecture achieved higher accuracy on experiments using standard benchmarks of LSP and MPII pose datasets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.5
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• pp.315-327
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• 2013

Wireless Body Area Network (WBAN) is a network around a human body within 3~5m which consists of medical or non-medical device. WBAN has to satisfy many kinds of demands such as low-power, a variety of data rate and a data priority. Especially, it is hard for the nodes for monitoring vital signs to replace battery. Thus energy and channel efficiency is important because the battery power is limited. In this thesis, a novel algorithm for reducing the energy consumption is proposed. The proposed algorithm adjusts transmission period according to traffic. by means of determining transmission period by amount of data, the node can reduce energy consumption. Energy detection is performed in order to guarantee data priority before attempting to transmit. In case of failing to transmit, it is proposed that energy consumption is reduced through avoiding collision by changing priority. The comparison result shows that the proposed algorithm reduces power consumption and increasing maximum channel efficiency by avoiding collision.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.491-491
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• 2011

Transparent and flexible electronic devices that are light-weight, unbreakable, low power consumption, optically transparent, and mechanical flexible possibly have great potential in new applications of digital gadgets. Potential applications include transparent displays, heads-up display, sensor, and artificial skin. Recent reports on transparent and flexible field-effect transistors (tf-FETs) have focused on improving mechanical properties, optical transmittance, and performances. Most of tf-FET devices were fabricated with transparent oxide semiconductors which mechanical flexibility is limited. And, there have been no reports of transparent and flexible all-organic tf-FETs fabricated with organic semiconductor channel, gate dielectric, gate electrode, source/drain electrode, and encapsulation for sensor applications. We present the first demonstration of transparent, flexible all-organic sensor based on multifunctional organic FETs with organic semiconductor channel, gate dielectric, and electrodes having a capability of sensing infrared (IR) radiation and mechanical strain. The key component of our device design is to integrate the poly(vinylidene fluoride-triflouroethylene) (P(VDF-TrFE) co-polymer directly into transparent and flexible OFETs as a multi-functional dielectric layer, which has both piezoelectric and pyroelectric properties. The P(VDF-TrFE) co-polumer gate dielectric has a high sensitivity to the wavelength regime over 800 nm. In particular, wavelength variations of P(VDF-TrFE) molecules coincide with wavelength range of IR radiation from human body (7000 nm ~14000 nm) so that the devices are highly sensitive with IR radiation of human body. Devices were examined by measuring IR light response at different powers. After that, we continued to measure IR response under various bending radius. AC (alternating current) gate biasing method was used to separate the response of direct pyroelectric gate dielectric and other electrical parameters such as mobility, capacitance, and contact resistance. Experiment results demonstrate that the tf-OTFT with high sensitivity to IR radiation can be applied for IR sensors.