• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.328-330
• /
• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• The Magazine of the IEIE
• /
• v.31 no.1
• /
• pp.58-72
• /
• 2004

Smart sensors and biochip technologies have received a great deal of attention in recent years not only because of the enormous potential markets in the healthcare expenditures but more importantly because of its great impact on the quality of human life in the future. Collaborative research among BT (Bio Technologies), IT (Information Technologies) and NT (Nano Technologies) will bring us a new paradigm of the healthcare services. Examples include disease prediction based on the genetic tests, personal medicines, point-of-care analysis, rapid and sensitive infectious disease diagnostics, environmental monitoring for chemical or biological warfares, intelligent drug delivery systems etc. In this report, recent accomplishment in the research area on biosensors, DNA chips, Protein Chips and Lab-on-a-chips are reviewed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.05a
• /
• pp.505-508
• /
• 2008

Electrocardiogram (ECG) and blood pressure (BP) are main vital signs which are the standards in most medical settings in assessing the most basic body functions. Multi parameters are desired in providing more information for health professionals in order to detect or monitor medical problems of patients more precisely. This study urges us to develop a robust wireless healthcare monitoring system which has multiple physiological signs measurements on real time that applicable to various environments which integrates wireless sensor network technology and code division multiple access (CDMA) network with extended feature of locally standalone diagnosis algorithms that implemented in tell phone. ECG signal and BP parameter of the patients are routinely be monitored, processed and analyzed in details at cell phone locally to produce useful medical information to ease patients for tracking and future reference purposes. Any suspected or unknown patterns of signals will be immediately forwarded to hospital server using cell phone for doctors' evaluation. This feature enables the patients always recognize the importance of self-health checking so that the preventive actions can be taken earlier through this analytic information provided by this monitoring system because "Prevention is better than Cure".

• Journal of Biomedical Engineering Research
• /
• v.29 no.4
• /
• pp.295-301
• /
• 2008

A wireless 3 channel ECG monitoring system was developed so that it could monitor the health and movement state during subject's daily life. The developed system consists of a wireless biomedical signal acquisition device, a personal healthcare server, and a remote medical server. Three experiments were performed to evaluate the accuracy, reliability and operability, applicability during daily life of the developed device. First, ECG signals were measured using the developed device and commercial reference device during sitting and marking time and compared to verify the accuracy of R-R intervals. Second, the reliable data transmission to remote server was verified on two types of simulated emergency event using patient simulator. Third, during five types of motion in daily life, the accuracy of data transmission to remote server using CDMA network was verified on two types of event occurring. By acquiring and comparing subject's biomedical signal and motion signal, the accuracy, reliability and operability, applicability during daily life of the developed device were verified. In addition, PDA-phone based wireless system enabled subject to be monitored without any constraints. Therefore, the developed system is expected to be applicable for monitoring the aged and chronic diseased people and giving first-aid in emergency.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.6
• /
• pp.1215-1221
• /
• 2009

A novel approach for electrocardiogram (ECG) analysis within a functional sensor node has been developed and evaluated. The main aim is to reduce data collision, traffic overload and power consumption in healthcare applications of wireless sensor networks(WSN). The sensor node attached on the patient's body surface around the heart can perform ECG analysis based on a QRS detection algorithm to detect abnormal condition of the patient. Data transfer is activated only after detected abnormality in the ECG. This system can reduce packet loss during transmission by reducing traffic overload. In addition, it saves power supply energy leading to more reliable, cheap and user-friendly operation in the WSN for ubiquitous health monitoring.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.7
• /
• pp.1252-1256
• /
• 2016

Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.406-409
• /
• 2022

In recent years, the developments in technologies, such as AI systems, Blockchain, VR/AR, 3D printing, robotics, and nanotechnology, are reshaping the future of healthcare right before our eyes. And also, healthcare has seen a paradigm shift towards prevention-oriented medicine, with a focus on consumers requirements. The spread of infectious diseases such as Covid-19 have altered the definition of healthcare and treatment facilities, necessitating immediate action to redesign hospitals' physical environments, adapt communication models to address social distancing requirements, implement virtual health solutions, and establish new clinical protocols. Hospitals, which have traditionally served as the hub of healthcare systems, are pursuing or being forced to reestablish themselves against this landscape. Rather than only treating ailments, future healthcare is predicted to focus on wellness and prevention. In personalized care, long-term prevention strategies, remote monitoring, early diagnosis, and detection are critical. Given the growing interest in smart healthcare defined by these modern technologies, this study looked into the definitions and service kinds of smart healthcare. The background and technical aspects of smart hospitals were also explored through a literature review.

• Journal of Satellite, Information and Communications
• /
• v.11 no.3
• /
• pp.18-23
• /
• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.482-485
• /
• 2007

Recent generation of wireless computing has focus on the integrating of exisitng technologies to enhance the mobile capabilities and developing a new approaches to meet the needs of the growing pool of applications. This paper describes an integrated IEEE802.15.4 wireless CDMA based healthcare system that interacts and received the data wirelessly from wireless medical devices of patient and forward to medical center by using the cellular network. Mobile application had been developed not only as the middle ware to handle the receive and transmit of medical data between wireless sensor network and cellular network but also provides the interface for monitoring and analyzing the health condition of patients continuously at cellular phone regardless of its physical location. This system thus enables the remote healthcare monitoring and supports medical data seamlessly roams between IEEE802.15.4 wireless network and CDMA network beyond and outside the hospital environment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.13 no.3
• /
• pp.267-276
• /
• 2020

Manufacturing workers are easily exposed to the risk of musculoskeletal disorders caused by repetitive tasks in their working environment. This is due to problems with occupational characteristics that repeatedly use the body. However, the current lack of monitoring systems for monitoring and prevention has led to an increase in workers' exposure to risks each year. This paper presents how to solve these problems in real working environment by producing wearable devices using IMU sensors. After wearing a wearable type device, the user's movement is judged through data analysis by receiving the rotation value according to musculoskeletal movement. At this time, the risk is determined by measuring the number of rotations of the user by eliminating bias and eliminating cumulative error, acquiring sophisticated data, and analyzing it in the form of dynamic threshold values. Using the wearable device proposed in this paper, the effect of this method could be checked through a web page measuring the number of rotations for elbow musculoskeletal disorders.