• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.3
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• pp.14-21
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• 2010

For the ubiquitous healthcare environment, real-time measurement of biomedical signals and accuracy of the measured biomedical information are very important. In addition, it is important to develop a healthcare device with low power In this paper, the synchronized pulse in a heartbeat was detected from the radial artery using the piezo film sensor, in order to eliminate inconvenience to wear a pulse detection finger probe. We can get a best output after applying the adaptive noise canceller using two piezo film sensor signals, pulse signal having motion artifacts and motion artifacts reference signal. To detect heartbeat, we use maximum point detection method from pulse removed motion artifacts.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2159-2164
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• 2008

Ubiquitous healthcare system is system that monitors and manages user's health information, and most important in the healthcare system is accuracy of the measured health data. But, the accuracy changes remarkably according to user's motion artifacts in real life. To elevate accuracy of health data, we proposed new algorithm to detect maximum point of pulse wave for heart rate extraction. and the proposed algorithm is to detect maximum points detect of pulse wave in photo-plethysmography signal included motion artifacts by fuzzy inference and multi sub-band filters. In results of experiment to evaluate the performance of the proposed algorithm, we could verify the proposed algorithm extracted maximum point of pulse wave in complex motion artifacts.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.28-32
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• 2014

Purpose Patient motion during myocardial perfusion SPECT can produce images that show visual artifacts and perfusion defects. This artifacts and defects remain a significant source of unsatisfactory myocardial perfusion SPECT. Motion correction has been developed as a way to correct and detect the patient motion for reducing artifacts and defects, and each motion correction uses different algorithm. We corrected simulated motion patterns with several motion correction methods and compared those images. Materials and Methods Phantom study was performed. The anthropomorphic torso phantom was made with equal counts from patient's body and simulated defect was added in myocardium phantom for to observe the change in defect. Vertical motion was intentionally generated by moving phantom downward in a returning pattern and in a non-returning pattern throughout the acquisition. In addition, Lateral motion was generated by moving phantom upward in a returning pattern and in a non-returning pattern. The simulated motion patterns were detected and corrected similarly to no-motion pattern image and QPS score, after Motion Detection and Correction Method (MDC), stasis, Hopkins method were applied. Results In phantom study, Changes of perfusion defect were shown in the anterior wall by the simulated phantom motions, and inferior wall's defect was found in some situations. The changes derived from motion were corrected by motion correction methods, but Hopkins and Stasis method showed visual artifact, and this visual artifact did not affect to perfusion score. Conclusion It was confirmed that motion correction method is possible to reduce the motion artifact and artifactual perfusion defect, through the apply on the phantom tests. Motion Detection and Correction Method (MDC) performed better than other method with polar map image and perfusion score result.

• Journal of the Korean Society of Clothing and Textiles
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• v.39 no.3
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• pp.369-378
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• 2015

Various forms of wearable bio-signal monitoring systems have been developed recently. Acquisition of stable bio-signal data for health care purposes needs to be unconscious and continuous without hindrance to the users' daily activities. The garment type is a suitable form of a wearable bio-signal monitoring system; however, motion artifacts caused by body movement degrade the signal quality during the measurement of bio-signals. It is crucial to stabilize the electrode position to reduce motion artifacts generated when in motion. The problems with motion artifacts remain unresolved despite their significant effect on bio-signal monitoring. This research creates a foundation for the design of garment-type wearable systems for everyday use by finding a method to reduce motion artifacts through modular design. Two distinct garment-type wearable systems (tee-shirt with a motion artifact-reducing module (MARM) and tee-shirt without a MARM) were designed to compare the effects of modular design on the measurement of heart activity in terms of electrode position displacement, signal quality index value, and morphological quality. The tee-shirt with MARM showed superior properties and yielded higher quality signals than the tee-shirt without MARM. In addition, the tee-shirt with MARM showed a better repeatability of the heart activity signals. Therefore, a garment design with MARM is an efficient way to acquire stable bio-signals while in motion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.141-148
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• 1994

This paper presents a new method for reducing the blocking artifacts there by increasing the prediction gains of the block-based motion compensation keeping the amount of the motion information to be transmitted intact. The new method improves the motion compensation along the edges of moving objects by segmenting the motion field at the pixel resolution based on the model that the motion compensated image is the maximum a poseriori estimate of the current frame.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2448-2463
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• 2013

The traditional block-based motion compensation methods in frame rate up-conversion (FRUC) only use a single uniquely motion vector field. However, there will always be some mistakes in the motion vector field whether the advanced motion estimation (ME) and motion vector analysis (MA) algorithms are performed or not. Once the motion vector field has many mistakes, the quality of the interpolated frame is severely affected. In order to solve the problem, this paper proposes a novel joint overlapped block motion compensation method (8J-OBMC) which adopts motion vectors of the interpolated block and its 8-neighbor blocks to jointly interpolate the target block. Since the smoothness of motion filed makes the motion vectors of 8-neighbor blocks around the interpolated block quite close to the true motion vector of the interpolated block, the proposed compensation algorithm has the better fault-tolerant capability than traditional ones. Besides, the annoying blocking artifacts can also be effectively suppressed by using overlapped blocks. Experimental results show that the proposed method is not only robust to motion vectors estimated wrongly, but also can to reduce blocking artifacts in comparison with existing popular compensation methods.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.199-202
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• 2001

In this paper, we propose new method of signal processing for the Pulse Oximeter for resistant motion artifact. When measure Oxygen saturation, today Pulse Oximeter is low reality because of patient moving, and it low difficult to filtering because of overlap Oxygen saturation and motion artifact. For we measure high reality Oxygen saturation, we reduces motion artifact. In this paper, we Propose and simulate method of signal processing for the Pulse Oximeter for resistant motion artifact.

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.123-130
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• 2008

Purpose : Motion effects in parallel magnetic resonance imaging (MRI) are investigated. Parallel MRI is known to be robust to motion due to its reduced acquisition time. However, if there are some involuntary motions such as heart or respiratory motions involved during the acquisition of the parallel MRI, motion artifacts would be even worse than those in conventional (non-parallel) MRI. In this paper, we defined several types of motions, and their effects in parallel MRI are investigated in comparisons with conventional MRI. Materials and Methods : In order to investigate motion effects in parallel MRI, 5 types of motions are considered. Type-1 and 2 are periodic motions with different amplitudes and periods. Type-3 and 4 are segment-based linear motions, where they are stationary during the segment. Type-5 is a uniform random motion. For the simulation, Cartesian and spiral grid based parallel and non-parallel (conventional) MRI are used. Results : Based on the motions defined, moving artifacts in the parallel and non-parallel MRI are investigated. From the simulation, non-parallel MRI shows smaller root mean square error (RMSE) values than the parallel MRI for the periodic (type-1 and 2) motions. Parallel MRI shows less motion artifacts for linear(type-3 and 4) motions where motions are reduced with shorter acquisition time. Similar motion artifacts are observed for the random motion (type-5). Conclusion : In this paper, we simulate the motion effects in parallel MRI. Parallel MRI is effective in the reduction of motion artifacts when motion is reduced by the shorter acquisition time. However, conventional MRI shows better image quality than the parallel MRI when fast periodic motions are involved.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.325-326
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• 2006

This paper proposes a new frame interpolation algorithm mainly designed for intra-mode blocks. In order to improve the accuracy of pixel interpolation, the new algorithm exploits two different interpolation modes for inter-mode blocks and intra-mode blocks, respectively. The use of the two modes reduces ghost artifacts but increases blocking artifacts between the blocks interpolated by different modes. To reduce blocking artifacts, this paper proposes an interpolation algorithm that attempts to isolate a fast moving object and interpolates such objects as the intra-mode while the remaining blocks are interpolated as the inter-mode. Simulation results show that the proposed algorithm improves subjective and objective quality of pictures by reducing ghost artifacts.

• ETRI Journal
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• v.43 no.5
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• pp.881-890
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• 2021

Photoplethysmography (PPG) is a noninvasive technique that can be used to conveniently measure heart rate (HR) and thus obtain relevant health-related information. However, developing an automated PPG system is difficult, because its waveforms are susceptible to motion artifacts and between-patient variation, making its interpretation difficult. We use deep neural network (DNN) filters to mimic the cognitive ability of a human expert who can distinguish the features of PPG altered by noise from various sources. Systolic (S), onset (O), and first derivative peaks (W) are recognized by three different DNN filters. In addition, the boundaries of uninformative regions caused by artifacts are identified by two different filters. The algorithm reliably derives the HR and presents recognition scores for the S, O, and W peaks and artifacts with only a 0.7-s delay. In the evaluation using data from 11 patients obtained from PhysioNet, the algorithm yields 8643 (86.12%) reliable HR measurements from a total of 10 036 heartbeats, including some with uninformative data resulting from arrhythmias and artifacts.