• Journal of Biomedical Engineering Research
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• v.37 no.1
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• pp.1-6
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• 2016

The biomedical information (heart rate, HRV, $SpO_2$ etc) from the Photoplethysmography (PPG) signal section can be estimated without the motion artifacts if the PPG signal section in the motion artifacts is detected accurately. But the PPG signal is easily exposed to the motion artifacts by the decrease of the medical instrument size and applying as portable or wearable. Besides, it is difficult to completely eliminate the motion artifacts from the PPG signal without distortion and ensure reliability as well. In this paper, the method was suggested to determine the motion artifacts or not on the PPG signal of the section divided into intervals of constant length. By comparing the spectrum of each section, it can be determined whether the motion artifacts are or not after obtaining the spectrum of each section by the Goertzel algorithm. Moreover, an amount of computation while maintaining a high detection rate can be reduced by using the Goertzel algorithm.

• Journal of Biomedical Engineering Research
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• v.38 no.3
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• pp.137-141
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• 2017

The indirect-contact bio-electric measurements using capacitive electrodes show large motion artifacts in comparison with conventional direct-contact measurements. It is necessary to measure the motion artifacts quantitatively, for the researches of reducing the motion artifacts. In this study, a device for quantitative measurement of motion artifacts was built. Using the device, an electrode was rubbed against some cloth(cotton) and the voltage variation of the electrode was measured as motion artifact in several environmental conditions(temperature and relative humidity). The measured waveforms agreed with that expected by the triboelectricity and the prior observations of the motion artifacts. Therefore, the results demonstrated the usability of the measurement system built in this study. The measurement system will be a great contribution to future research for reducing motion artifact.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.701-706
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• 2007

The measurement accuracy for heart rate or $SpO_2$ using photoplethysmography (PPG) is influenced by how well the noise from motion artifacts and other sources can be removed. Eliminating the motion artifacts is particularly difficult since its frequency band overlaps that of the basic PPG signal. Therefore, we propose the Periodic Moving Average Filter (PMAF) to remove motion artifacts. The PMAF is based on the quasi-periodicity of the PPG signals. After segmenting the PPG signal on periodic boundaries, we average the $m^{th}$ samples of each period. As a result, we remove the motion artifacts well without the deterioration of the characteristic point.

• Journal of information and communication convergence engineering
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• v.10 no.1
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• pp.91-95
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• 2012

The photoplethysmography (PPG) signal measured from a mobile healthcare device contains various motion artifacts occurring from a patient’s movements. Recently, to reject the motion artifacts, the method of using an acceleration sensor was suggested, but such sensors are very expensive. Therefore, this study deals with a novel sensor device to replace the acceleration sensor, and evaluated the performance of the proposed sensor experimentally. In the results of the experiments, it is shown that the proposed sensor device can reconstruct the PPG signal despite the occurrence of motion artifacts, and also that the variation rate in heart rate analysis was 1.22%. According to the experimental results, the proposed method can be applied to design a low-cost device.

• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.987-990
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• 2009

Motion-induced artifacts on LCDs appear as blurred boundaries and/or color aberration between the moving objects and background. Perceived degree of the motion-induced artifacts depends on the blur width as well as color difference. This paper presents a quantitative measure for the motion-induced artifacts on LCDs. Performance of the proposed measure is verified by calculating correlation coefficients between the proposed measures and the results of human visual tests performed on the 240 Hz and 120 Hz scanning LCD TVs.

• Proceedings of the KSMRM Conference
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• 1999.04a
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• pp.34-42
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• 1999

의료영상에서 인공물(Artifacts) 이라 함은 영상이 얻어지는 신체부위와 아무런 관련이 없으나 얻어진 영상에는 마치 영상의 일부분으로 나타나는 모든 것을 가리킨다. 따라서 영상에서 이들 인공물들은 실제 조직의 해부학적인 구조를 나타내지 않으므로 영상 판독에 영향을 주어 잘못된 진단을 초래할 수도 있다. 그러나 MR 영상이 가능한 이래로 새로운 여러 종류의 MR 인공물들이 많이 발견 되었으나 다행스럽게도 거의 모든 MR 인공물들은 쉽게 설명이 가능하며, 따라서 이들 인공물들에 의한 진단 오류의 가능성은 매우 희박한 실정이다. 그러나 새로운 영상방법이나 혹은 새로운 펄스대열이 계속 고안됨에 따라 새로운 종류의 인 공물들이 생겨날 가능성은 항상 존재하고 있다. 지금까지 알려진 여러 MR 인공물들은 그 생겨난 원인에 따라 다음과 같이 크게 세 가지로 분류가 가능하다. I. Motion Artifacts 1. Voluntary motion 2. Involuntary motion 1) Bowel Peristalsis 2) Respiration 3) Cardiac and vessel pulsation 4) Swallowing 3. Fluid motion 1) Blood flow 2) Cerebrospinal fluid flow II. Reconstruction Artifacts 1. Aliasing 2. Partial volume averaging 3. Truncation (Ringing) 4. Central point III. Magnetic and RF Field Related Artifacts 1. Chemical shift 1) First kind 2) Second kind 2. Susceptibility 1) Dental 2) Metal 3. Magic angle 4. Zipper 5. Bad data point 6. RF field inhomogeneity 7. Magnetic field inhomogeneity 8. Eddy current 9. slice overlapping 10. Zebra 11. RF overflow

• Journal of Broadcast Engineering
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• v.21 no.4
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• pp.472-483
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• 2016

This paper proposes a blocking artifacts detection algorithm in frequency domain for MC-FRUC (Motion Compensated Frame Rate Up-Conversion). Conventional MC-FRUC algorithms occur blocking artifacts near interpolated block boundaries since motion compensation is performed from block-based motion vector. For efficiently decreasing blocking artifacts, this paper analyses frequency characteristics of the interpolated frame and reduces blocking artifacts on block boundaries. In experimental results the proposed method shows better subjective quality than some conventional FRUC method and also increases the PSNR(Peak Signal to Noise Ratio) value on average 0.45 dB compared with BDMC(Bi-Directional Motion Compensation).

• International conference on construction engineering and project management
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• 2024.07a
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• pp.902-908
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• 2024

A large number of construction accidents are caused by workers' unsafe behavior under excessive workload. Despite the demonstrated effectiveness and advantages of current portable electroencephalogram (EEG) devices in workload monitoring, accurate data acquisition remains challenging due to motion artifacts in dynamic environments. Consequently, most current research is limited to static conditions, thus restricting its application to construction tasks that inherently involve bodily movements. In this study, an innovative signal filtering framework is introduced that employs the principles of adaptive filtering to integrate acceleration signals containing motion information for the correction of motion artifacts in EEG signals. The experimental results demonstrate that this approach effectively eliminates motion-induced artifacts in EEG signals, thereby improving the preprocessing of hybrid kinematic-EEG signals acquired during bodily and muscular movements. By enhancing signal quality and reliability, this preprocessing framework aims to broaden the application of portable EEG devices for real-time workload monitoring among construction workers. This advancement is expected to enhance the practicality of EEG in construction safety management and ultimately contribute to safer construction practices.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.101-107
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• 2014

This study is proposed the novel PPG sensor device and the signal processing method to replace the acceleration sensor that is used to reject motion artifacts contained in photoplethysmography(PPG). The proposed method is to reject motion artifacts by an adaptive filter based on the estimated motion artifact by using a blue LED light. To evaluate the performance of the proposed method experimentally, We did design a novel sensor consisted of blue/red LEDs and photo-sensor and implemented, and then rejected the motion artifacts by using an adaptive filter and the implemented sensor. In the results of the experiments, it is shown that the proposed sensor device and signal processing can reconstruct the PPG signal despite the occurrence of motion artifacts, and also that the SNR was 4.5 times of moving average filter. According to the experimental results, the proposed method can be applied to design a low-cost device.

• Journal of Sensor Science and Technology
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• v.27 no.3
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• pp.192-198
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• 2018

Pulse oximetry is a non-invasive method for monitoring how much oxygenated hemoglobin is present in the blood. The principle of pulse oximetry is based on the red infrared light adsorption characteristics of oxygenated and deoxygenated hemoglobin. Even through the convenience of a pulse oximeter, its weak signal-to-noise ratio against motion artifacts and low perfusion makes it difficult to be accepted by execs devices. Several researchers have suggested the use of an adaptive noise cancellation (ANC) algorithm. They have demonstrated that ANC is feasible for reducing the effects of motion artifacts. Masimo Corporation developed a discrete saturation transformation (DST) algorithm that uses a reference signal and ANC. In commercial devices, it is very hard to escape it because Masimo's patents are very powerful and a better method is yet to be developed. This study proposes a new method that can measure noise saturation as well as accurate oxygen saturation from signals with high motion artifacts without using ANC and DST. The proposed algorithm can extract a normal signal without noise from a signal with motion artifacts. The reference signal from a pulse oximeter simulator was used for the evaluation of our proposed algorithm and achieved good results.