• Journal of Korea Society of Industrial Information Systems
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• v.15 no.4
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• pp.53-60
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• 2010

Biometrics are methods of recognizing a person based on the physiological or behavioral characteristics of his of her body. They are highly secure with little risk of loss or falsification by others. This paper has designed and implemented a security system of biometrics by precisely measuring heartbeat signals at two fingertips and using a photoplethysmogram, which is applicable to biometrics. A performance evaluation has led to the following result. The security system of biometrics for personal authentication which has been designed and implemented by this study has achieved a recognition rate of 90.5%. The security system of biometrics suggested here has merits of time saving and easy accessibility. The system is touch-based and collects the necessary biometrics information by simply touching the machine with fingers, so anyone can utilize the system without any difficulty.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.23-29
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• 2009

The heart sends blood to the body with heart rate. When heart rate for men is from 60 to 80 per minute, he is generally normal. However, if heart rate is less than the normal heart rate, the symptom is called by bradycardia. Otherwise, the symptom is called by tachycardia. These symptoms make him even to death. Therefore, heartbeat rate has a very important role in a healthy life. In this study, we studied on auto-extracting methods of heart rates from ECG, and compared them with those measured by naked eyes. The first auto-extracting method employs the 2-order differential equations to extract heart rate. The second method uses the autocorrelation coefficients to detect heart rate. To verify its efficacy and validity in practical applications, these method has been applied to MIT/BIH database.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.214-217
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• 2017

In this paper, we propose a sleep efficiency measurement algorithm based on IR-UWB radar sensor in distance. Among the vital signs which can be measured by the IR-UWB radar sensor such as breathing rate, heartbeat rate, and movement, we analyzed correlation between the movement and the sleep efficiency, and based on the result, we propose a sleep efficiency measurement algorithm. In order to verify the performance of the proposed algorithm, we applied the algorithm to three polysomnography patients in hospitals and obtained the performance of an average absolute error within 3.9%.

• Biomaterials and Biomechanics in Bioengineering
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• v.2 no.3
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• pp.173-183
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• 2015

In obstetrics, cardiotocography is a procedure to record the fetal heartbeat and the uterine contractions usually during the last trimester of pregnancy. It helps to monitor patterns associated with the fetal activity and to detect the pathologies. In this paper, random forest classifier is used to classify normal, suspicious and pathological patterns based on the features extracted from the cardiotocograms. The results showed that random forest classifier can detect these classes successfully with overall classification accuracy of 93.6%. Moreover, important features are identified to reduce the feature space. It is found that using seven important features, similar classification accuracy can be achieved by random forest classifier (93.3%).

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.91-98
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• 2016

Outbreaks of highly contagious livestock diseases can cause direct and indirect economic impacts such as lower productivity of cattle farms, fall in tourism in damaged areas and countries, and decline in exports. They also incur tremendous social costs associated with disease elimination and restoration work. Thus, it is essential to prevent livestock diseases through monitoring and prediction efforts. Currently, however, it is still difficult to provide accurate predictive information regarding occurrences of livestock diseases, because existing cattle health monitoring or forecasting systems are only limited to monitor environmental conditions of livestock barns and check activities of cattle by using a pedometer or thermal image. In this paper, we present a biosensor-based cattle health monitoring system capable of collecting bio-signals of farm animals in an effective way. For the presented monitoring system, we design an integrated monitoring device consisting of a sensing module to measure bio-signals of cattle such as the heartbeat, the breath rate and the momentum, as well as a Zigbee module designed to transmit the biometric data based on Wireless Sensor Network (WSN). We verify the validity of the monitoring system by the comparison of the correlations of designed device with a commercial ECG equipment through analyzing the R-peak of measured signals.