scholarly journals Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 673 ◽  
Author(s):  
Yifan Zhang ◽  
Shuang Song ◽  
Rik Vullings ◽  
Dwaipayan Biswas ◽  
Neide Simões-Capela ◽  
...  
Keyword(s):  
Signal Reconstruction ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Health Conditions ◽  
Average Error ◽  
Artifact Reduction ◽  
Modular Algorithm ◽  
Algorithm Framework ◽  
Electrocardiogram Ecg

Long-term heart rate (HR) monitoring by wrist-worn photoplethysmograph (PPG) sensors enables the assessment of health conditions during daily life with high user comfort. However, PPG signals are vulnerable to motion artifacts (MAs), which significantly affect the accuracy of estimated physiological parameters such as HR. This paper proposes a novel modular algorithm framework for MA removal based on different wavelengths for wrist-worn PPG sensors. The framework uses a green PPG signal for HR monitoring and an infrared PPG signal as the motion reference. The proposed framework includes four main steps: motion detection, motion removal using continuous wavelet transform, approximate HR estimation and signal reconstruction. The proposed algorithm is evaluated against an electrocardiogram (ECG) in terms of HR error for a dataset of 6 healthy subjects performing 21 types of motion. The proposed MA removal method reduced the average error in HR estimation from 4.3, 3.0 and 3.8 bpm to 0.6, 1.0 and 2.1 bpm in periodic, random, and continuous non-periodic motion situations, respectively.

scholarly journals Use of Transforms in Biomedical Signal Processing and Analysis

2021 ◽  
Author(s):  
Ette Harikrishna ◽  
Komalla Ashoka Reddy
Keyword(s):  
Wavelet Transforms ◽  
Research Work ◽  
Reference Signal ◽  
Low Frequency ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Biomedical Signal Processing ◽  
Blood Oxygen Saturation ◽  
Biomedical Signals ◽  
Electrocardiogram Ecg

Biomedical signals like electrocardiogram (ECG), photoplethysmographic (PPG) and blood pressure were very low frequency signals and need to be processed for further diagnosis and clinical monitoring. Transforms like Fourier transform (FT) and Wavelet transform (WT) were extensively used in literature for processing and analysis. In my research work, Fourier and wavelet transforms were utilized to reduce motion artifacts from PPG signals so as to produce correct blood oxygen saturation (SpO2) values. In an important contribution we utilized FT for generation of reference signal for adaptive filter based motion artifact reduction eliminating additional sensor for acquisition of reference signal. Similarly we utilized the transforms for other biomedical signals.

scholarly journals Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning–based filter using convolutional neural network

2020 ◽  
Vol 30 (11) ◽  
pp. 5923-5932
Author(s):  
M.-L. Kromrey ◽  
D. Tamada ◽  
H. Johno ◽  
S. Funayama ◽  
N. Nagata ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Arterial Phase ◽  
Artifact Reduction ◽  
Gadoxetate Disodium ◽  
Mr Images ◽  
Liver Mri ◽  
Lesion Conspicuity

Abstract Objectives To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium–enhanced multi-arterial phase MRI of the liver. Methods This retrospective study included 192 patients (131 men, 68.7 ± 10.3 years) receiving gadoxetate disodium–enhanced liver MRI in 2017. Datasets were submitted to a newly developed filter (MARC), consisting of 7 convolutional layers, and trained on 14,190 cropped images generated from abdominal MR images. Motion artifact for training was simulated by adding periodic k-space domain noise to the images. Original and filtered images of pre-contrast and 6 arterial phases (7 image sets per patient resulting in 1344 sets in total) were evaluated regarding motion artifacts on a 4-point scale. Lesion conspicuity in original and filtered images was ranked by side-by-side comparison. Results Of the 1344 original image sets, motion artifact score was 2 in 597, 3 in 165, and 4 in 54 sets. MARC significantly improved image quality over all phases showing an average motion artifact score of 1.97 ± 0.72 compared to 2.53 ± 0.71 in original MR images (p < 0.001). MARC improved motion scores from 2 to 1 in 177/596 (29.65%), from 3 to 2 in 119/165 (72.12%), and from 4 to 3 in 34/54 sets (62.96%). Lesion conspicuity was significantly improved (p < 0.001) without removing anatomical details. Conclusions Motion artifacts and lesion conspicuity of gadoxetate disodium–enhanced arterial phase liver MRI were significantly improved by the MARC filter, especially in cases with substantial artifacts. This method can be of high clinical value in subjects with failing breath-hold in the scan. Key Points • This study presents a newly developed deep learning–based filter for artifact reduction using convolutional neural network (motion artifact reduction with convolutional neural network, MARC). • MARC significantly improved MR image quality after gadoxetate disodium administration by reducing motion artifacts, especially in cases with severely degraded images. • Postprocessing with MARC led to better lesion conspicuity without removing anatomical details.

scholarly journals A Rigid Motion Artifact Reduction Method for CT Based on Blind Deconvolution

Algorithms ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 155 ◽  
Author(s):  
Yuan Zhang ◽  
Liyi Zhang
Keyword(s):  
Iterative Process ◽  
Degrees Of Freedom ◽  
Blind Deconvolution ◽  
Pearson Correlation ◽  
Rigid Motion ◽  
Structural Similarity ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Artifact Reduction ◽  
Clinical Experiments

In computed tomography (CT), artifacts due to patient rigid motion often significantly degrade image quality. This paper suggests a method based on iterative blind deconvolution to eliminate motion artifacts. The proposed method alternately reconstructs the image and reduces motion artifacts in an iterative scheme until the difference measure between two successive iterations is smaller than a threshold. In this iterative process, Richardson–Lucy (RL) deconvolution with spatially adaptive total variation (SATV) regularization is inserted into the iterative process of the ordered subsets expectation maximization (OSEM) reconstruction algorithm. The proposed method is evaluated on a numerical phantom, a head phantom, and patient scan. The reconstructed images indicate that the proposed method can reduce motion artifacts and provide high-quality images. Quantitative evaluations also show the proposed method yielded an appreciable improvement on all metrics, reducing root-mean-square error (RMSE) by about 30% and increasing Pearson correlation coefficient (CC) and mean structural similarity (MSSIM) by about 15% and 20%, respectively, compared to the RL-OSEM method. Furthermore, the proposed method only needs measured raw data and no additional measurements are needed. Compared with the previous work, it can be applied to any scanning mode and can realize six degrees of freedom motion artifact reduction, so the artifact reduction effect is better in clinical experiments.

scholarly journals Camera-based heart rate estimation for hospitalized newborns in the presence of motion artifacts

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Qiong Chen ◽  
Yalin Wang ◽  
Xiangyu Liu ◽  
Xi Long ◽  
Bin Yin ◽  
...  
Keyword(s):  
Heart Rate ◽  
Body Movement ◽  
Region Of Interest ◽  
Ground Truth ◽  
Absolute Error ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Majority Voting ◽  
Thermal Cameras ◽  
Electrocardiogram Ecg

Abstract Background Heart rate (HR) is an important vital sign for evaluating the physiological condition of a newborn infant. Recently, for measuring HR, novel RGB camera-based non-contact techniques have demonstrated their specific superiority compared with other techniques, such as dopplers and thermal cameras. However, they still suffered poor robustness in infants’ HR measurements due to frequent body movement. Methods This paper introduces a framework to improve the robustness of infants’ HR measurements by solving motion artifact problems. Our solution is based on the following steps: morphology-based filtering, region-of-interest (ROI) dividing, Eulerian video magnification and majority voting. In particular, ROI dividing improves ROI information utilization. The majority voting scheme improves the statistical robustness by choosing the HR with the highest probability. Additionally, we determined the dividing parameter that leads to the most accurate HR measurements. In order to examine the performance of the proposed method, we collected 4 hours of videos and recorded the corresponding electrocardiogram (ECG) of 9 hospitalized neonates under two different conditions—rest still and visible movements. Results Experimental results indicate a promising performance: the mean absolute error during rest still and visible movements are 3.39 beats per minute (BPM) and 4.34 BPM, respectively, which improves at least 2.00 and 1.88 BPM compared with previous works. The Bland-Altman plots also show the remarkable consistency of our results and the HR derived from the ground-truth ECG. Conclusions To the best of our knowledge, this is the first study aimed at improving the robustness of neonatal HR measurement under motion artifacts using an RGB camera. The preliminary results have shown the promising prospects of the proposed method, which hopefully reduce neonatal mortality in hospitals.

Removal of ECG Baseline Wander Using a Resting Cycle Template

2021 ◽  
Vol 10 (1) ◽  
pp. 45
Author(s):  
Eladio Altamira-Colado ◽  
Miguel Bravo-Zanoguera ◽  
Daniel Cuevas-González ◽  
Marco Reyna-Carranza ◽  
Roberto López-Avitia
Keyword(s):  
Spline Interpolation ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
New Method ◽  
Daily Activities ◽  
Pass Filter ◽  
Ecg Signals ◽  
Baseline Wander ◽  
Low Amplitude ◽  
Electrocardiogram Ecg

The development of electrocardiogram (ECG) wearable devices has increased due to its applications on ambulatory patients. ECG signals provide useful information about the heart behavior, but when daily activities are monitored, motion artifacts are introduced producing saturation of the signal, thus losing the information. The typical resolution used to record ECG signals is of maximum 16-bit, which might not be enough to detect low-amplitude potentials and at the same time avoid saturation due to baseline wander, since this last issue demands a low-gain signal chain. A high-resolution provides a more detailed ECG signal under a low gain input, and if the signal is corrupted by motion artifact noise but is not saturated, it can be filtered to recover the signal of interest. In this work, a 24-bit ADC is used to record the ECG, and a new method, the rest ECG cycle template, is proposed to remove the baseline wander. This new method is compared to high-pass filter and spline interpolation methods in their ability to remove baseline wander. This new method presumes that a user is able to establish a rest ECG during his/her daily activities.

MRI: How to perform a pediatric scan

2013 ◽  
Vol 54 (9) ◽  
pp. 991-997 ◽  
Author(s):  
Øystein E Olsen
Keyword(s):  
Signal To Noise Ratio ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Acquisition Time ◽  
Artifact Reduction ◽  
Resonance Imaging ◽  
Basic Principles ◽  
Low Snr ◽  
Patient Preparation ◽  
Magnetic Resonance Imaging Mri

Magnetic resonance imaging (MRI) is rich in diagnostic information but requires optimization for use in children. The main problems are motion artifacts and poor signal-to-noise ratio (SNR). SNR is proportional to voxel volume, which must therefore not be too small, however, usually needs to be reduced compared to adult imaging to account for the finer anatomy of the child. The use of multi-channel coils with element sizes appropriate for the anatomy of interest ensures optimal baseline SNR. Longer acquisition time increases SNR (with a square-root factor), but the flip-side is that this allows more motion artifacts. Attention to patient preparation and to techniques for motion artifact reduction is therefore crucial, and the most important principles are discussed. Low SNR may in part be compensated by optimizing the image contrast by weighting (tissue and lesions T1 and T2 may differ from adults) and by using contrast agents. It is also powerful to combine different image contrasts during postprocessing. The basic principles are discussed, followed by an example scan protocol.

scholarly journals Motion Artifact Reduction in Wearable Photoplethysmography Based on Multi-Channel Sensors with Multiple Wavelengths

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1493 ◽  
Author(s):  
Jongshill Lee ◽  
Minseong Kim ◽  
Hoon-Ki Park ◽  
In Young Kim
Keyword(s):  
Motion Artifact ◽  
Motion Artifacts ◽  
Measuring System ◽  
Depth Information ◽  
Artifact Reduction ◽  
Truncated Singular Value Decomposition ◽  
Fast Walking ◽  
Multiple Wavelengths ◽  
Measure Heart Rate ◽  
Value Decomposition

Photoplethysmography (PPG) is an easy and convenient method by which to measure heart rate (HR). However, PPG signals that optically measure volumetric changes in blood are not robust to motion artifacts. In this paper, we develop a PPG measuring system based on multi-channel sensors with multiple wavelengths and propose a motion artifact reduction algorithm using independent component analysis (ICA). We also propose a truncated singular value decomposition for 12-channel PPG signals, which contain direction and depth information measured using the developed multi-channel PPG measurement system. The performance of the proposed method is evaluated against the R-peaks of an electrocardiogram in terms of sensitivity (Se), positive predictive value (PPV), and failed detection rate (FDR). The experimental results show that Se, PPV, and FDR were 99%, 99.55%, and 0.45% for walking, 96.28%, 99.24%, and 0.77% for fast walking, and 82.49%, 99.83%, and 0.17% for running, respectively. The evaluation shows that the proposed method is effective in reducing errors in HR estimation from PPG signals with motion artifacts in intensive motion situations such as fast walking and running.

Rigid Motion Artifact Reduction in CT Using the Phase Correlation Method

2020 ◽  
Vol 13 (8) ◽  
pp. 1119-1128
Author(s):  
Yuan Zhang ◽  
Liyi Zhang ◽  
Yunshan Sun
Keyword(s):  
Rigid Motion ◽  
Correlation Method ◽  
Reconstruction Algorithm ◽  
Human Head ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Phase Correlation ◽  
Artifact Reduction ◽  
Patient Motion ◽  
Reconstruction Quality

Background: In Computed Tomography (CT), it is often not possible for the subject to remain stationary during a scan. Unfortunately, a patient motion would result in degraded spatial resolution and image artifacts. It is desirable to improve reconstruction quality and reduce motion artifacts caused by patient motion. Methods: In this work, a method was proposed to eliminate the influence of the motion on image quality, based on the phase correlation method. Based on our previous work, projections were first taken by Radon transform and motion parameters were estimated by the phase-only correlation of projections in the Radon domain. In addition, an improved image reconstruction algorithm was performed to compensate for the motion effects. Results: Experimental results proved that the proposed method could not only obtain high precision and good real-time performance but also ensure a superior artifact reduction. Conclusion: Besides, the efficacy of the proposed method has been demonstrated in both simulated and human head experiments.

Electrocardiogram Recognition and Ablation of Atrial Tachycardia

2011 ◽  
Vol 3 (1) ◽  
pp. 80
Author(s):  
Alexander Feldman ◽  
Jonathan M Kalman ◽  
◽  
Keyword(s):  
Catheter Ablation ◽  
Atrial Tachycardia ◽  
Primary Treatment ◽  
P Wave ◽  
Wave Morphology ◽  
Focal Atrial Tachycardia ◽  
Mapping Techniques ◽  
Electrocardiogram Ecg ◽  
Surface Electrocardiogram

Focal atrial tachycardia (AT) is a relatively uncommon cause of supraventricular tachycardia, but when present is frequently difficult to treat medically. Atrial tachycardias tend to originate from anatomically determined atrial sites. The P-wave morphology on surface electrocardiogram (ECG) together with more sophisticated contemporary mapping techniques facilitates precise localisation and ablation of these ectopic foci. Catheter ablation of focal AT is associated with high long-term success and may be viewed as a primary treatment strategy in symptomatic patients.

scholarly journals Health of mothers of children with a life-limiting condition: a comparative cohort study

2021 ◽  
pp. archdischild-2020-320655
Author(s):  
Lorna K Fraser ◽  
Fliss EM Murtagh ◽  
Jan Aldridge ◽  
Trevor Sheldon ◽  
Simon Gilbody ◽  
...  
Keyword(s):  
Mental Health ◽  
Cohort Study ◽  
Secondary Care ◽  
Incidence Rates ◽  
Health Conditions ◽  
Clinical Practice Research Datalink ◽  
Physical And Mental Health ◽  
Term Condition ◽  
Limiting Condition

ObjectiveThis study aimed to quantify the incidence rates of common mental and physical health conditions in mothers of children with a life-limiting condition.MethodsComparative national longitudinal cohort study using linked primary and secondary care data from the Clinical Practice Research Datalink in England. Maternal–child dyads were identified in these data. Maternal physical and mental health outcomes were identified in the primary and secondary care datasets using previously developed diagnostic coding frameworks. Incidence rates of the outcomes were modelled using Poisson regression, adjusting for deprivation, ethnicity and age and accounting for time at risk.ResultsA total of 35 683 mothers; 8950 had a child with a life-limiting condition, 8868 had a child with a chronic condition and 17 865 had a child with no long-term condition.The adjusted incidence rates of all of the physical and mental health conditions were significantly higher in the mothers of children with a life-limiting condition when compared with those mothers with a child with no long-term condition (eg, depression: incidence rate ratio (IRR) 1.21, 95% CI 1.13 to 1.30; cardiovascular disease: IRR 1.73, 95% CI 1.27 to 2.36; death in mothers: IRR 1.59, 95% CI 1.16 to 2.18).ConclusionThis study clearly demonstrates the higher incidence rates of common and serious physical and mental health problems and death in mothers of children with a life-limiting condition. Further research is required to understand how best to support these mothers, but healthcare providers should consider how they can target this population to provide preventative and treatment services.

Sign in / Sign up

Export Citation Format

Share Document