• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.1-10
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• 2020

In this paper, we propose an algorithm for estimating blood pressure using ECG (Electrocardiogram) and PPG (Photoplethysmography) signals. To estimate the BP (Blood pressure), we generate a periodic input signal, remove the noise according to the differential and threshold methods, and then estimate the systolic and diastolic blood pressures based on the convolutional neural network. We used 49 patient data of 3.1GB in the MIMIC database. As a result, it was found that the prediction error (RMSE) of systolic BP was 5.80mmHg, and the prediction error of diastolic BP was 2.78mmHg. This result confirms that the performance of class A is satisfied with the existing BP monitor evaluation method proposed by the British High Blood Pressure Association.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2161-2162
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• 2006

In this study, we developed five mobile units and an integrated system which can manage vital signs from each unit using Bluetooth wireless communication. The five kinds of mobile unit were so designed that each has different function to be applied according to the condition of patient properly. The mobile units can measure ECG signal of single or 12 channel, blood pressure, pulse and SpO2 signal from a patient. Also, to reduce the uncomfortable measurement, several types of units such as belt type, wrist type and necklace type were designed. Our proposed system can integrate and monitor several biological signals from different patient by using Bluetooth wireless communication simultaneously. The developed system was evaluated in the simulated emergent situation and showed the system can monitor 5 patients in maximum according to the data quality. It showed the possibilities that the developed system can be used effectively for emergency situation or in- or out-hospital transport of patient. In future, with the combination of mobile communication technique, a patient who is in emergency situation can be provided with proper first-aid and a doctor can pile information of patient and give better diagnosis and treatments.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.17-23
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• 2011

In this paper, daily life stress monitoring system is proposed. The proposed wireless ECG module, reducing the noise and increasing the size of signal, amplification circuit was designed for. Using HRV(Heart Rate Variability), extracted by measuring R-wave, stress diagnostic algorithms to assess the stress of human emotion were developed. For monitoring the activities, the proposed system is consist of small rectangular size for portable and by simple measurement it is possible to measure at any time. Through experiments, the proposed approach to represent user's stress level can be confirmed. Through that, it can see appropriate structure to obtain R-wave for stress assess as well as high resemblance to the clinical electrocardiogram. In this paper, performed experiments was developed nonrestraint measuring and wearable wireless biometric scanner that is able to monitor the heart's electrical activity of everyday life.Using this, the algorithm system, that is able to assess stress index through time-domain and frequency-domain analysis of the front and the rear of performing stress load protocol, was developed,

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.315-319
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• 1996

We have developed a prototype patient monitoring system including module-based bedside units, interbed network, and central stations. A bedside unit consists of a color monitor and a main CPU unit with peripherals including a module controller. It can also include up to 3 module cases and 21 different modules. In addition to the 3-channel recorder module, six different physiological parameters of ECG, respiration, invasive blood pressure, noninvasive blood pressure, body temperature, and arterial pulse oximetry with plethysmogaph are provided as parameter modules. Modules and a module controller communicate with up to 1Mbps data rate through an intrabed network based on RS-485 and HDLC protocol. Bedside units can display up to 12 channels of waveforms with any related numeric informations simultaneously. At the same time, it communicates with other bedside units and central stations through interbed network based on 10Mbps Ethernet and TCP/IP protocol. Software far bedside units and central stations fully utilizes gaphical user interface techniques and all functions are controlled by a rotate/push button on bedside unit and a mouse on central station. The entire system satisfies the requirements of AAMI and ANSI standards in terms of electrical safety and performances. In order to accommodate more advanced data management capabilities such as 24-hour full disclosure, we are developing a relational database server dedicated to the patient monitoring system. We are also developing a clinical workstation with which physicians can review and examine the data from patients through various kinds of computer networks far diagnosis and report generation. Portable bedside units with LCD display and wired or wireless data communication capability will be developed in the near future. New parameter modules including cardiac output, capnograph, and other gas analysis functions will be added.