• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1749-1754
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• 2007

In this paper, we propose a new Intra-body communication system for bio-sensor which is one of applications in PAN(Personal Area Network) using body channel. The communication systems for bio-sensor network usually transmits a lot of data acquired in sensor to the receiver in wrist or waist. So we deign the intra-body modem with high data rate, low power, and small size which are achieved by baseband communication techniques. It is noted that the baseband transmission does not requires any analog IF and RF frontends, and can be operated in lower frequency than bandpass transmission. The proposed modem operates at 10MHz band according to the characteristics of intra-body channel, and shows the capability of 5Mbps data rate at distance of 20cm, with $BER=10^{-5}$. In addition, we implement the modem within $2{\times}2cm$ area.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.227-228
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• 2008

노인들이 주거하는 실버타운에는 노인들의 건강 관리가 가장 중요하다. 이러한 노인들은 갑작스럽게 생체 신호의 변화나 건강 상태가 나빠질 수 있다. 대부분의 실버타운은 의료시설 외의 다른 장소에서 노인들의 건강 상태를 확인할 수 없다. 따라서 본 논문에서는 실버타운에서 노인들의 생체 정보 및 응급상황을 언제, 어디서나 모니터링 할 수 있는 USN(Ubiquitous Sensor Network)시스템을 설계 및 구현한 연구를 소개한다. 또한, 실버타운 환경을 고려한 라우팅 알고리즘을 소개한다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.105-112
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• 2010

In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one's emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.62-69
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• 2008

In this paper, we proposed the real-time bio-signals monitoring system that is based on the ZigBee wireless sensor network and SIP. This system makes medical team and user easily confirm user's medical state irrelative to their location and time. The communication between medical sensors and the user's end device uses the ZigBee wireless sensor network. The power consumption was decreased because wireless sensor network does not use the Ad-hoc routing protocol but routing protocol that is based on tree structure. Our proposed system includes a wireless user's end device, monitoring console, SIP server and database server. This real-time bio-signals monitoring system makes possible to implement the U-health care services and improving efficiency of medical treatment services.

• Smart Structures and Systems
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• v.7 no.3
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.31-37
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• 2010

This study was developed the home network system for the home stay care by bio-sensor system to translate the physical signal algorithm. The composition algorithm has five functions for a input function, frequency variable, displacement point input function, axial Variable, axial Sway Displacement to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a measurement such as a heart rate, temperature, weight. The algorithm of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for health management system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.585-588
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• 2009

Wireless Sensor Network (WSN) is consisted of lots of tiny sensor nodes with limited processing power and computing resources. Thus, the most critical and fundamental element of WSN technology is sensor node, which gathers environmental information and transmits it to the user application systems. Due to the technological advancement, sensor nodes are become smaller and more intelligent, hence, expand their application area. Specifically, implantable wireless sensor node technology, to monitor and treat disease by implanting tiny sensor nodes into human body or livestock, shows further directions of WSN. In this paper, we have designed an implantable wireless sensor node to monitor livestock body temperature in real time. We also discussed on the additional considerations to implement real time bio-monitoring systems.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.506-516
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• 2015

Wireless sensor networks (WSNs) are generally comprised of densely deployed sensor nodes, which results in highly redundant sensor data transmissions and energy waste. Since the sensor nodes depend on batteries for energy, previous studies have focused on designing energy-efficient medium access control (MAC) protocols to extend the network lifetime. However, the energy-efficient protocols induce an extra end-to-end delay, and therefore recent increase in focus on WSNs has led to timely and reliable communication protocols for mission-critical applications. In this paper, we propose an energy efficient and delay guaranteeing node scheduling scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique.With the identification of analogies between cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired algorithm determines the state of the sensor node, as required by each application and as determined by the local environmental conditions and the states of the adjacent nodes. A control analysis shows that the proposed bio-inspired scheme guarantees the system stability by controlling the parameters of each node. Simulation results also indicate that the proposed scheme provides significant energy savings, as well as reliable delay guarantees by controlling the states of the sensor nodes.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.116-123
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• 2013

In mobile healthcare applications, the reliable transmission of the bio-data is very important. In this article, we present a reliable bio-data transmission technique for mobile healthcare monitoring service at 6LoWPAN multi-hop wireless networks. In particular, we expand IEEE 11073-20601 protocol, and propose the reliable path construction for 6LoWPAN aimed to reliably provide mobile healthcare service over wireless sensor network, using IPv6 network. 6LoWPAN is recognized possibility because it is agree with sensor network by raising Adaptation layer on the MAC layer to transmit IPv6 packets. In this article proposed minimize the algorithm complexity and reliability routing protocol because the 6LoWPAN devices are suitable for low cost, small size and battery that can be used to health care system environment. And detailed procedures and algorithms are presented. We the proposed method to prove the superiority of using NS-3 for compareing with AODV protocol.

• Journal of the Korean Society of Tobacco Science
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• v.17 no.1
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• pp.5-14
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• 1995

Efficient algorithms for the automatic classification of flue-cured tovacco ripeness and grading have been developed The ripeness of the tobacco was classified into 4 levels vased on the color. The lab-built simple RGB color measuring system was utilized for detecting the light reflectance of the tobacco leaves. The measured data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The spectrophotometer was used to detect the light reflectance and absorption of the graded tobacco leaves in the frequency ranges of the visible light The measured data and the statistical analysis was performed to investigate the light characteristics of the graded samples. The measured data were obtained from samples of 5 different grades directly without considering the leaf positions. Those data were used far training the artificial neural network The performance of the trained network was also tested far the untrained samples. The neural network based sensor information processing showed successful results for grading of tobacco leaves.