• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.185-188
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• 2000

Heart sound contains rich information regarding the dynamics of the heart and the auscultation has been a first choice of routine procedures for diagnosis of the heart. However, heart sounds captured using a conventional stethoscope are not often loud or clear enough for doctors to precisely classify their characteristics, especially, under the noisy environments of the hospital. A simple auscultation device that removed shortcomings of the conventional stethoscope was constructed in the study. The device employed a polymer based adherent differential output sensor which was on contact with skin through a coupling medium and appropriated electronic circuits for signal amplification and conditioning. An ordinary headphone is taken to hear the captured heart sounds and the volume can be adjusted to hear well. It is also possible that the device sends the captured heart sound signals to a PC where the signals are further processed and viualized.

• Proceedings of the KWS Conference
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• 1996.10a
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• Journal of Welding and Joining
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• v.16 no.3
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• pp.102-110
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• 1998

The horizontal fillet welding is prevalently used in heavy and ship building industries to fabricate the large scale structures. A deep understanding of the horizontal fillet welding process is restricted, because the phenomena occurring in welding are very complex and highly non-linear characteristics. To achieve the satisfactory weld bead geometry in robot welding system, the seam tracking algorithm should be reliable. The number of seam tracker was developed for arc welding automation by now. Among these seam tracker, the arc sensor is prevalently used in industrial robot welding system because of its low cost and flexibility. However, the accuracy of arc sensor would be decreased due to the electrical noise and metal transfer. In this study, the signal processing algorithm based on the neural network was implemented to enhance the reliability of measured welding current signals. Moreover, the seam tracking algorithm in conjunction with the signal processing algorithm was implemented to trace the center of weld line. It was revealed that the neural network could be effectively used to predict the welding current signal at the end of weaving.

• Smart Media Journal
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• v.5 no.3
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• pp.25-29
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• 2016

This paper presents research for non-contact gesture recognition system using EPS(Electronic Potential Sensor) for measuring the human body of electromagnetic fields. It implemented a signal acquisition and signal processing system for designing a system suitable for motion recognition using the data coming from the sensors. we transform AC-type data into DC-type data by applying a 10Hz LPF considering H/W sampling rate. in addition, we extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1297-1303
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• 2003

This paper propose an advanced circuit for fingerprint sensor signal processing. We increased the voltage between ridge and valley by modifying the parasitic capacitance eliminating circuit of sensor plate. The analog comparator was designed for comparing the sensor signal voltage with the reference signal voltage. We also propose an effective isolation strategy for removing noise and signal coupling, ESD of each sensor pixel. The 128${\times}$l44 pixel fingerprint sensor circuit was designed and simulated, and the layout was performed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.209-213
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• 1997

This paper deals with sensing ability of $2^{nd}$ smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the $2^{nd}$ smart sensor for experiment. The second type of smart sensor is HH type. We have developed a new signal processing method that can distinguish among different materials. The estimation method (RSAIIn dex) is developed for $2^{nd}$ smart sensor(HH smart sensor). Experiment and analysis are executed for estimation the new method. We estimated sensing ability of $2^{nd}$ smart sensor with RsA, method. Sensing Ability of the $2^{nd}$ smart sensor were evaluated relatively through a new RsAl method. According to frequency changing, influences of the $2^{nd}$ smart sensor are evaluated through a new recognition index RSAI. Applications of this method are for finding abnormal conditions of objects (automanufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4A
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• pp.466-471
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• 2004

This paper proposes an advanced circuit for fingerprint sensor signal processing. We increased the voltage between ridge and valley by modifying the parasitic capacitance eliminating circuit of sensor plate. The analog comparator was designed for comparing the sensor signal voltage with the reference signal voltage. 1-Pixel Fingerprint sensor circuit was designed and simulated, and the layout was performed.

• Journal of Sensor Science and Technology
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• v.15 no.2
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• pp.77-83
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• 2006

A monitoring apparatus for pulse shapes of human heartbeats has been developed using an amorphous MI(Magnetic Impedance) sensor. The pulse shapes are successfully obtained from voltage signals due to the variations of magnetic impedance in the amorphous MI sensor, which is attached to a patient's wrist. This voltage signal was fed into a signal processing module to extract the pulse shapes of heartbeats. The signal processing module, which is proposed to detect a weak variations of impedance in MI sensor under a noisy measurement environment, consists of a high frequency current source, an amplifier stage and a synchronous detection circuit. To evaluate the characteristics of a newly developed apparatus, various experiments were performed. The experimental results show that the developed apparatus could be used as a diagnosis tool for traditional Korean medicine with further systematic clinical studies.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.12
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• pp.550-557
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• 2006

This paper proposes a dry-type surface myoelectric sensor for the myoelectric hand prosthesis. The designed surface myoelectric sensor is composed of skin interface and processing circuits. The skin interface has one reference and two input electrodes, and the reference electrode is located in the center of two input electrodes. In this paper is proposed two types of sensors with the circle- and bar-shaped reference electrode, but all input electrodes are the bar-shaped. The metal material of the electrodes is the stainless steel (SUS440) that endures sweat and wet conditions. Considering the conduction velocity and the median frequency of the myoelectric signal, the inter-electrode distance (IED) between two input electrodes as 18mm, 20mm, and 22mm is selected. The signal processing circuit consists of a differential amplifier with a band pass filter, a band rejection filter for rejecting 60Hz power-line noise, amplifiers, and a mean absolute value(MAV) circuit. Using SUS440, six prototype skin interface with different reference electrode shape and IED is fabricated, and their output characteristics are evaluated by output signal obtained from the forearm of a healthy subject. The experimental results show that the skin interface with parallel bar shape and the 18mm IED has a good output characteristics. The fabricated dry-type surface myoelectric sensor is evaluated for the upper-limb amputee.

• Journal of Sensor Science and Technology
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• v.19 no.1
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• pp.8-16
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• 2010

This research proposes measuring of BCG(ballistocardiogram) to monitor heart activities in a non-constrained environment, at home or work. Unlike with ECG, measuring BCG does not require the attachment of leads on the subject's body and allows signal measuring in a non-constrained state. It enables effective long-term monitoring of cardiac conditions. In this study a chair type BCG measurement system to continuous monitor the activity of the heart is implemented. The instrument consists of upper petal and ready for press of chair load cell sensor is attached to measure the change of the object's weight. In order to extract the output ballistic signal from the weight and force sensor signals. Beside the signal processing circuit for the digital conversion, the ballistic signal is detected using DAQ equipment. Signal processing algorithm including wavelet transforms for noise cancellation, template matching for normalization and peak detection in BCG is developed. ECG and BCG were concurrently measured to evaluate the performance of the system, and comparing the characteristics of the two signals verified the possibility of the system in non-constrained and nonconscious health monitoring.