Young-Dong Lee

A wireless sensor network compatible wearable u-healthcare monitoring system using integrated ECG, accelerometer and SpO 2

This paper presents the design and development of a wearable ubiquitous healthcare monitoring system using integrated electrocardiogram (ECG), accelerometer and oxygen saturation (SpO 2 ) sensors. In this design, non-intrusive healthcare system was designed based on wireless sensor network (WSN) for wide area coverage with minimum battery power to support RF transmission. We have developed various devices such as wearable ubiquitous sensor network (USN) node, wearable chest sensor belt and wrist pulse oximeter for this system. Low power ECG, accelerometer and SpO 2 sensors board was integrated to the wearable USN node for users health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network using IEEE 802.15.4 from on-body wearable sensor devices to a base-station which is connected to a server PC. Physiological data can be displayed and stored in the server PC continuously.This paper presents the design and development of a wearable ubiquitous healthcare monitoring system using integrated electrocardiogram (ECG), accelerometer and oxygen saturation (SpO2) sensors. In this design, non-intrusive healthcare system was designed based on wireless sensor network (WSN) for wide area coverage with minimum battery power to support RF transmission. We have developed various devices such as wearable ubiquitous sensor network (USN) node, wearable chest sensor belt and wrist pulse oximeter for this system. Low power ECG, accelerometer and SpO2 sensors board was integrated to the wearable USN node for users health monitoring. The wearable ubiquitous healthcare monitoring system allows physiological data to be transmitted in wireless sensor network using IEEE 802.15.4 from on-body wearable sensor devices to a base-station which is connected to a server PC. Physiological data can be displayed and stored in the server PC continuously.

Vital Sign Monitoring System with Life Emergency Event Detection using Wireless Sensor Network

A distributed healthcare monitoring system prototype for clinical and trauma patients, is to be developed, using wireless sensor network node. The proposed system aims to measure various vital physiological health parameters like ECG and body temperature, of patients and elderly persons and transfer his/her health status wirelessly in Ad-hoc network, to remote base station which is connected to a hospitals main Server, using wireless sensor node. Main server shows information of sensor node which transfer presently vital data and if an abnormal ECG activity is encounter, the server will store 1 minute of the ECG-recording and then transmit the recording to PDA and standard PC as a Clinical Diagnostic Station(CDS). Server can calculate Heart Rate(HR) and variation in the R-R interval and if desired by doctor, averaged values together with maximum and minimum values are calculated every on minute.

Design Issues and Implementation of Query-Driven Healthcare System Using Wireless Sensor Ad-hoc Network

Application specific design requirements for wireless sensor network have posed new challenges and need for revision of existing designs for its implementation in healthcare systems. These requirements are different from that needed for environmental, agricultural and industrial purposes. The proposed paper discusses the design issues in implementation of Query driven Healthcare monitoring system using wireless sensor network. Various MAC layers designs have been studied for their usefulness and compatibility with the requirements in the healthcare system. Topology and network layer design have also been discussed. Further the low and computational capabilities of wireless sensor nodes itself adds to the design complexity. Therefore some compromises have to be made in both the domains. We aimed to implement a healthcare system using wireless sensor node based on the above study. A hardware platform was designed for the use as wireless sensor node. In this system, a wireless sensor node attached on the human body provides ECG (Electrocardiogram) and body temperature from multiple patients in an ad-hoc network. A mote-based 3-lead ECG and body temperature monitoring system operates in wireless sensor network. Health data from multiple patients can be relayed wirelessly using multi-hop routing scheme to a base-station, following IEEE 802.15.4 standard for wireless communication. Unique id assigned to each mote is used to identify each patient in the network.

Frequency based classification of activities using accelerometer data

This work presents, the classification of user activities such as Rest, Walk and Run, on the basis of frequency component present in the acceleration data in a wireless sensor network environment. As the frequencies of the above mentioned activities differ slightly for different person, so it gives a more accurate result. The algorithm uses just one parameter i.e. the frequency of the body acceleration data of the three axes for classifying the activities in a set of data. The algorithm includes a normalization step and hence there is no need to set a different value of threshold value for magnitude for different test person. The classification is automatic and done on a block by block basis.

High Accuracy Human Activity Monitoring Using Neural Network

This paper presents the designing of a neural network for the classification of Human activity. A Tri-axial accelerometer sensor, housed in a chest worn sensor unit, has been used for capturing the acceleration of the movements associated. All the three axis acceleration data were collected at a base station PC via a CC2420 2.4 GHz ISM band radio (zigbee wireless compliant), processed and classified using MATLAB. A neural network approach for classification was used with an eye on theoretical and empirical facts. The work shows a detailed description of the designing steps for the classification of human body acceleration data. A 4-layer back propagation neural network, with Levenberg-marquardt algorithm for training, showed best performance among the other neural network training algorithms.

Measurement of Motion Activity during Ambulatory Using Pulse Oximeter and Triaxial Accelerometer

An ambulatory pulse oximeter system based on wireless sensor network is designed and integrated to the wearable sensor node. The system is developed to measure motion activities using pulse oximeter and triaxial accelerometer sensor during in motion. The input signals are pulse oximeter and triaxial acceleration signals which are acquired from a finger. However, motion artifact is originated a result in a distorted PPG signal which may cause between the skin and sensor during physical activity. Therefore, motion artifacts prevent their broad in wearable, ambulatory pulse oximeter system. The measurement of those signals, such as the PPG and the electrocardiogram (ECG) requires being still tight during the measurement in order to get the accurate result preventing noises caused by the casual movement. In this paper, we calibrate the distorted PPG signal with the motion activities by measuring PPG and motion signals by using triaxial accelerometer as a reference signal. The system allows PPG signals to be transmitted in wireless sensor network from the pulse oximeter to a base-station connected to server PC via IEEE 802.15.4. The experiments were performed by using wearable ECG, accelerometer sensor and ambulatory pulse oximeter for measuring in different scenarios such as resting, swing, walking, etc.

Empirical analysis of the reliability of low-rate wireless u-healthcare monitoring applications

SUMMARY In this paper, we demonstrate an empirical analysis of the reliability of low-rate wireless u-healthcare monitoring applications. We have considered the performance analysis of the IEEE 802.15.4 low-rate wireless technologies for u-healthcare applications. For empirical measurement, we considered three scenarios in which the reliability features of the low-rate wireless u-healthcare monitoring applications have been measured: (i) distance between sensor nodes and base station; (ii) deployment of the number of sensor nodes in a network; and (iii) data transmission by different time intervals. The experimental results show that received data are used to calculate BER and analyze the performance according to the scenarios. The BER is affected when varying the distance between sensor node and base station, the number of nodes, and time interval. Copyright

Performance analysis of wireless link quality in wireless sensor networks

This paper aims to analyze wireless link quality like received signal strength indicator (RSSI) and link quality indicator (LQI) in IEEE 802.15.4 based wireless sensor networks. Our experiments are performed on Chipcon CC2420 radios, which comply with the IEEE 802.15.4. In order to measure the performance of LQI, RSSI and PRR in IEEE 802.15.4 based wireless sensor networks, the experiments were conducted by varying distances between transmitter and base-station and transmit power level. Our experimental results show that the PRR depends on some factors such as LQI and RSSI including the distance between transmitter and base-station and the location of each of the sensor nodes.

TriSec: A Secure Data Framework for Wireless Sensor Networks Using Authenticated Encryption

Wireless sensor networks (WSNs) are an emerging technology and offers economically viable monitoring solution to many challenging applications. However, deploying new technology in hostile environment, without considering security in mind has often proved to be unreasonably unsecured. Apparently, security techniques face many critical challenges in WSNs like data security and secrecy due to its hostile deployment nature. In order to resolve security in WSNs, we propose a novel and efficient secure framework called TriSec: a secure data framework for wireless sensor networks to attain high level of security. TriSec provides data confidentiality, authentication and data integrity to sensor networks. TriSec supports node-to-node encryption using PingPong-128 stream cipher based-privacy. A new PingPong-MAC (PP-MAC) is incorporated with PingPong stream cipher to make TriSec framework more secure. PingPong-128 is fast keystream generation and it is very suitable for sensor network environment. We have implemented the proposed scheme on wireless sensor platform and our result shows their feasibility.

Implementation of Greenhouse Environment Monitoring System based on Wireless Sensor Networks

In this paper, various growth environment data collecting and monitoring based on wireless sensor network for greenhouse environmental monitoring system is designed and implemented. In addition, greenhouse control system is proposed to integrated control and management in internal environment and greenhouse facilities. The system provides real-time remote greenhouse integrated management service which collects greenhouse environment information and controls greenhouse facilities based on wireless sensor network. Graphical user interface for an integrated management system is designed based on the HMI and the experimental results show that the sensor data were collected by integrated management in real-time.