• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.454-458
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• 2008

It can improve human being's life quality that all people can have more convenient medical service under pervasive computing environment. For a pervasive health care application for diabetes patient, we've implemented a health care system, which is composed of three parts. Various sensors monitor both outer and inner environment of human such as temperature, blood pressure, pulse, and glycemic index, etc. These sensors form zigbee based sensor network. And medical information server accumulates sensing values and performs back-end processing. To simply transfer these sensing values to a medical team is a low level's medical service. So, we've designed a new service model based on back propagation neural network for more improved medical service. Our experiments show that a proposed healthcare system can give high level's medical service because it can recognize human's context more concretely.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.465-474
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• 2014

Wireless sensor network (WSN) is considered to be one of the most important research fields for ubiquitous healthcare (u-healthcare) applications. Healthcare systems combined with WSNs have only been introduced by several pioneering researchers. However, most researchers collect physiological data from medical nodes located at static locations and transmit them within a limited communication range between a base station and the medical nodes. In these healthcare systems, the network link can be easily broken owing to the movement of the object nodes. To overcome this issue, in this study, the fast link exchange minimum cost forwarding (FLE-MCF) routing protocol is proposed. This protocol allows real-time multi-hop communication in a healthcare system based on WSN. The protocol is designed for a multi-hop sensor network to rapidly restore the network link when it is broken. The performance of the proposed FLE-MCF protocol is compared with that of a modified minimum cost forwarding (MMCF) protocol. The FLE-MCF protocol shows a good packet delivery rate from/to a fast moving object in a WSN. The designed wearable platform utilizes an adaptive linear prediction filter to reduce the motion artifacts in the original electrocardiogram (ECG) signal. Two filter algorithms used for baseline drift removal are evaluated to check whether real-time execution is possible on our wearable platform. The experiment results shows that the ECG signal filtered by adaptive linear prediction filter recovers from the distorted ECG signal efficiently.

• KIEAE Journal
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• v.14 no.6
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• pp.23-29
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• 2014

It is essential to investigate the structure and the main characteristics of BSN (Bio-Sensor Network) platform in built smart healthcare environment while designing healthy housing facilities. For this study, WSN (Wireless Sensor Network) data transmission technologies have been employed with medical sensors, and optimal medical devices would provide various Web 2.0 services by connecting to the WiBro network. The BSN platform normally recognizes in surroundings of WBAN (Wireless Body Area Network) or WPAN (Wireless Personal Area Network), and it is possible to manage sensor nodes by utilizing SOAP (Simple Object Access Protocol) and REST (REpresentational State Transfer). In addition, the feature of SNMP (Simple Network Management Protocol) for mobile gateway is also included for being adapted to huge network structure. Finally, BSN platform will play a role as important clues for developing personal WSN service models for smart healthy housing properties.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.13-24
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• 2005

The sensor network is a key component of the ubiquitous computing system which is expected to be widely utilized in logistics control, environment/disaster control, medical/health-care services, digital home and other applications. Nodes in the sensor network are small-sized and exposed to adverse environments. They are demanded to perform their missions with very limited power supply only. Also the sensor network is composed of much more nodes than the wireless ad hoc networks are. In case that some nodes consume up their power capacity, the network topology should change, and rerouting/retransmission is necessitated. Communication protocols studied for conventional wireless networks or ad hoc networks are not suited for the sensor network resultantly. Schemes should be devised to control the efficient usage of node power in the sensor network. This paper proposes a medium access protocol to enhance the efficiency of energy consumption in the sensor network node. Its performance is analyzed by simulation.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.160-166
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• 2011

In u-healthcare services based on wireless body sensor networks, reliable connection is very important as many types of information, including vital signals, are transmitted through the networks. The transmit power requirements are very stringent in the case of in-body networks for implant communication. Furthermore, the wireless link in an in-body environment has a high degree of path loss (e.g., the path loss exponent is around 6.2 for deep tissue). Because of such inherently bad settings of the communication nodes, a multi-hop network topology is preferred in order to meet the transmit power requirements and to increase the battery lifetime of sensor nodes. This will ensure that the live body of a patient receiving the healthcare service has a reduced level of specific absorption ratio (SAR) when exposed to long-lasting radiation. We propose an efficientmethod for delivering delay-intolerant data packets over multiple hops. We consider forward error correction (FEC) in an erasure correction mode and develop a mathematical formulation for packet-level scheduling of delay-intolerant FEC packets over multiple hops. The proposed method can be used as a simple guideline for applications to setting up a topology for a medical body sensor network of each individual patient, which is connected to a remote server for u-healthcare service applications.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.143-151
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• 2008

In this paper, we have implemented a ubiquitous healthcare system that can measure and check human's health in anytime and anywhere. The implemented prototype are composed of both front-end and back-end. The front-end have several groups: environment sensor group such as temperature, humidity, photo, voice sensor, health sensor group such as blood pressure, heart beat, electrocardiogram, spo2 sensor, gateway for wired/wireless communication, and RFID reader to identify personal. The back-end has a serial forwarder to propagate measurment results, monitor program, and medical information server The implemented sensor node constructs a sensor network using the Zigbee protocol and is ported the tinyOS. The data gathering base node is linux-based terminal that can transfer a sensed medial data through wireless LAN. And, the medical information server stores the processed medical data and can promptly notify the urgent status to the connected medical team. Through our experiments, we've confirmed the possibility of ubiquitous healthcare system based on sensor network using the Zigbee.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.186-194
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• 2008

This paper has implemented a ubiquitous healthcare system that can measure and check the electrocardiogram of a human body in anytime and anywhere. The implemented prototype is composed of electrocardiogram measurement terminal, data gathering base node, and medical information server. The implemented node constructs a sensor network using the Zigbee protocol and the TinyOS is installed on each node. The data gathering base node is linux-based node that can transfer sensed medial data through wireless LAN. And, the medical information server stores the processed medical data and can promptly notify the urgent status to the connected medical team. Through experiment, we confirmed the possibility of ubiquitous healthcare system based on sensor network using the Zigbee.

• The KIPS Transactions:PartC
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• v.19C no.1
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• pp.19-28
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• 2012

Wireless sensor network provides services anytime and anywhere they are requested. Especially, medical sensor network based on biosensors is applied a lot to biotechnology and medical engineering. In medical sensor network, people can make their health checked at home free from temporal and spatial constraints. In ubiquitous healthcare environment, people can get instant help even in the emergency, and in hospital, patients can be taken care of efficiently. In this environment, health and life related data are delivered, and the privacy and security of personal data are very important. In this paper, we propose user authentication and data communication mechanism in two modes, normal and urgent situation using cellular phone. Through our proposal, data can be transferred in quick and secure manner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1706-1725
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• 2024

The unique U-shaped structure of U-Net network makes it achieve good performance in image segmentation. This network is a lightweight network with a small number of parameters for small image segmentation datasets. However, when the medical image to be segmented contains a lot of detailed information, the segmentation results cannot fully meet the actual requirements. In order to achieve higher accuracy of medical image segmentation, a novel improved U-Net network architecture called multi-scale encoder-decoder U-Net+ (MEDU-Net+) is proposed in this paper. We design the GoogLeNet for achieving more information at the encoder of the proposed MEDU-Net+, and present the multi-scale feature extraction for fusing semantic information of different scales in the encoder and decoder. Meanwhile, we also introduce the layer-by-layer skip connection to connect the information of each layer, so that there is no need to encode the last layer and return the information. The proposed MEDU-Net+ divides the unknown depth network into each part of deconvolution layer to replace the direct connection of the encoder and decoder in U-Net. In addition, a new combined loss function is proposed to extract more edge information by combining the advantages of the generalized dice and the focal loss functions. Finally, we validate our proposed MEDU-Net+ MEDU-Net+ and other classic medical image segmentation networks on three medical image datasets. The experimental results show that our proposed MEDU-Net+ has prominent superior performance compared with other medical image segmentation networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.967-979
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• 2013

Now a day, Wireless Sensor Networks (WSNs) are being widely used in different areas one of which is healthcare services. A wireless medical sensor network senses patient's vital physiological signs through medical sensor-nodes deployed on patient's body area; and transmits these signals to devices of registered medical professionals. These sensor-nodes have low computational power and limited storage capacity. Moreover, the wireless nature of technology attracts malicious minds. Thus, proper user authentication is a prime concern before granting access to patient's sensitive and private data. Recently, P. Kumar et al. claimed to propose a strong authentication protocol for healthcare using Wireless Medical Sensor Networks (WMSN). However, we find that P. Kumar et al.'s scheme is flawed with a number of security pitfalls. Information stored inside smart card, if extracted, is enough to deceive a valid user. Adversary can not only access patient's physiological data on behalf of a valid user without knowing actual password, can also send fake/irrelevant information about patient by playing role of medical sensor-node. Besides, adversary can guess a user's password and is able to compute the session key shared between user and medical sensor-nodes. Thus, the scheme looses message confidentiality. Additionally, the scheme fails to resist insider attack and lacks user anonymity.