Dong Ik Shin

Patient Monitoring System using Sensor Network Based on the ZigBee Radio

In these days of u-healthcare, for convenient monitoring of biological signals, the wireless communication technique is necessary. We have investigated several wireless technologies of biological sensor networking for u-healthcare. There are some standard techniques such as Bluetooth, wireless LAN, Zigbee etc. We have tested these techniques for biological sensor networking and summarize the advantages and the disadvantages. As a result we decided the ZigBee radio as sensor network of patients in the hospital. We developed this patient monitoring system which has several biological parameters. Especially, this system has ability of patients location awareness in the hospital.

Statistical 3D Distribution Analysis of Prostate Cancers in Korean Using Digital Processing Techniques

Objectives Several researchers have shown that three dimensional (3D) distribution analysis of prostate cancer is helpful when initiating needle biopsy procedures. Knowledge regarding the distribution of prostate cancer could enhance understanding of the pathophysiology involved and improve detection of these malignancies. We propose utilizing digital processing techniques to analyze prostate cancer distribution in a 3D setting. Methods Pre-made radical prostatectomy sample slices were digitized with a resolution of 76 dpi. Slices of each sample were aligned and registered by deformation algorithm and interpolated for analysis of relative distribution statistics. We analyzed 80 samples saved in electronic medical record and compared the detection rate of preoperative needle biopsies and radical prostatectomies using our 3D analysis technique. Results The statistical 3D distribution of prostate cancer was evaluated using a 36-sector process. Results were represented in the following two ways: distribution of a single patient, and statistical distribution of prostate cancers of multiple patients. The overall concordance rate was 62.7% between the two methods; therefore a technique is needed which can raise this percentage. Conclusions We suggest using the normalization method to develop a software tool which permits reconstruction of the 3D distribution of prostate cancer from 2D legacy images and reduces the loss of image quality as well. This application will facilitate detection of prostate cancer by aiding in the determination of the most effective clinical position via partial sampling with decreased patient inconvenience.

Comparison of Recognition Accuracy of ADL with Sensor Wearing Positions using 3-Axis Accelerometer

The monitoring of single elderly is being more important due to rapid transition to aging society. There are many bio-signals to monitor the emergent state of elderly. In this paper we propose new criteria to classify daily life activities using accelerometer and pulse oximeter. We categorized activities with the motility of real action. The upper most criteria are normal and abnormal activity. The lower criteria are ‘small or large movement’, ‘periodic or random movement’, ‘no movement or shock’. Then we derive some parameters to get thresholds to classify these activities according to our new criteria. The main parameters are entropy, energy and autocorrelation. Some experiments were carried out to determine classifying thresholds. Finally we got results of classified activities such as ‘no movements’, ‘small movements’, ‘large movements’, ‘periodic movements’ and ‘falls’. We got nearly 100% of classifying result for falls and no movements. In this case of ‘quasi-emergency state’ our developing device investigates further status of elderly by measuring of heart rate and oxygen saturation (SpO2) using pulse oximeter. Finally the device decides in emergency, it sends a short message to server and then connects to the u-Healthcare centre or emergency centre and one’s family.

Activity Classification Using 3-Axis Accelerometer Wearing on Wrist for the Elderly

The monitoring of single elderly is more important due to rapid transition to aging society. There are many bio-signals to monitor the emergent state of elderly. These vital signals including ECG, PPG, blood pressure signal spend heavy processing resource and costs. We have been developed the monitoring device for the elderly emergency monitoring. In this paper we propose new criteria to classify daily life activities. We categorized activities with the motility of real action. The upper most criteria are normal and abnormal activity. The lower criteria are ‘small or large movement’, ‘periodic or random movement’, ‘no movement or shock’. Then we derive some parameters to get thresholds to classify these activities according to our new criteria. The main parameters are entropy, energy and autocorrelation. Some experiments were carried out to determine classifying thresholds. Finally we got results of classified activities such as ‘no movements’, ‘small movements’, ‘large movements’, ‘periodic movements’ and ‘falls’. We got nearly 100% of classifying result for falls and no movements. In this case of ‘quasi-emergency state’ our developing device will investigate further status of elderly by measuring of heart rate and oxygen saturate using pulse oxymeter. Finally the device decides in emergence, it sends a short message to server and then connected to the u-Healthcare center or emergency center and one’s family.

Hybrid Vital Sensor of Health Monitoring System for the Elderly

There are many sensors to monitor vital signs in u-Healthcare system. These vital sensors including ECG, PPG, blood pressure sensor spend heavy processing resource and costs. We propose and developing a new type of hybrid vital sensor. We combine accelerometer and PPG module and control two basic sensors with classified situations. So, we can monitor vital signs more compactly, inexpensively and conveniently using our hybrid sensor. We measured the activity using 3-axis accelerometer and measured the heart rate and oxygen saturation using pulse oxymeter. The major problem of pulse oxymeter is motion artifact. But we suggested a new method using the combination of these two sensors. In case of active motion, we used and analyzed the accelerometer signal and withdraw the pulse oxymeter signal. In case of no activity, we adopt pulse oxymeter signal which has no motion artifacts. The important thing is to categorize activity patterns such as normal or abnormal activity. We categorized activities to 4 patterns which are normal activity, no activity(resting), sleeping and abnormal state. When the device detects abnormal condition, it sends a short message to server and then connected to the u-Healthcare center or emergency center.

The Mobile Implementation of HL7 API for u-Healthcare Devices

Health Level Seven (HL7) is the standard of electronic data interchange in the health domain. In This paper, we have developed mobile application with HL7 protocol. This application, data are transmitted the bio-signal like SpO2 from sensor to mobile phone through serial communication. The mobile phone convert raw data to HL7 formed data and send it to other PCs by Bluetooth or WLAN.

The use of the LabVIEW to automate analysis of action potential and monophasic action potential

The action potential(AP) and monophasic action potential(MAP) has been known to reliably reproduce the time course of cardiac repolarization and has been applied clinically to evaluate the mechanism of arrhythmia or the effect of antiarrhythmic drugs.

Optimal Body Area Network for u-Healthcare

In these days of u-Healthcare, for convenient monitoring of biological signals, the wireless communication technique is necessary. We have investigated several wireless technologies of biological sensor networking for u-Healthcare. There are some standard techniques such as Bluetooth, Wireless LAN, Zigbee etc. We have tested these techniques for biological sensor networking and summarize the advantages and the disadvantages. Furthermore, for compactness and minimum software overload, we have manufactured and evaluated several customized RF devices. On the other hand, there are some trials of using RFID for non-invasive intrabody signal measuring such as intracranial pressure. We also investigated this emerging technique as an optimal measuring technique for some special signals. Furthermore, for ultimate intra-body wireless network, we tried some experiments of wireless communication using body itself as a transmission medium. As a conclusion, we summarize and evaluate several conventional wireless techniq ues and investigated new technologies for u-Healthcare monitoring.

The Study on HL7 Message Modeling Algorithm based on uHealthcare Environment

Health Level Seven (HL7) is the standard of electronic data interchange in the health domain. In This paper, we suggest abstract structure algorithm for modeling HL7 message. Compared with other existing ones, this method optimized uHealthcare environment. When updating HL7 message structure, there is no need to compile entire code. Besides, no speed down results from repetitive request queries.