Motion Artifact Detection Research Articles

Motion artefact detection in capacitively coupled EEG recording

Motion artefact detection in capacitively coupled EEG recording

RPCA-based detection and quantification of motion artifacts in ECG signals

In this paper, a recursive principal component analysis (RPCA)-based algorithm is applied for detecting and quantifying the motion artifact episodes encountered in an ECG signal. The motion artifact signal is synthesized by low-pass filtering a random noise signal with different spectral ranges of LPF (low pass filter): 0–5 Hz, 0–10 Hz, 0–15 Hz and 0–20 Hz. Further, the analysis of the algorithm is carried out for different values of SNR levels and forgetting factors (α) of an RPCA algorithm. The algorithm derives an error signal, wherever a motion artifact episode (noise) is present in the entire ECG signal with 100% accuracy. The RPCA error magnitude is almost zero for the clean signal portion and considerably high wherever the motion artifacts (noisy episodes) are encountered in the ECG signals. Further, the general trend of the algorithm is to produce a smaller magnitude of error for higher SNR (i.e. low level of noise) and vice versa. The quantification of the RPCA algorithm has been made by applying it over 25 ECG data-sets of different morphologies and genres with three different values of SNRs for each forgetting factor and for each of four spectral ranges.

Automatic Motion and Noise Artifact Detection in Holter ECG Data Using Empirical Mode Decomposition and Statistical Approaches

We present a real-time method for the detection of motion and noise (MN) artifacts, which frequently interferes with accurate rhythm assessment when ECG signals are collected from Holter monitors. Our MN artifact detection approach involves two stages. The first stage involves the use of the first-order intrinsic mode function (F-IMF) from the empirical mode decomposition to isolate the artifacts' dynamics as they are largely concentrated in the higher frequencies. The second stage of our approach uses three statistical measures on the F-IMF time series to look for characteristics of randomness and variability, which are hallmark signatures of MN artifacts: the Shannon entropy, mean, and variance. We then use the receiver-operator characteristics curve on Holter data from 15 healthy subjects to derive threshold values associated with these statistical measures to separate between the clean and MN artifacts' data segments. With threshold values derived from 15 training data sets, we tested our algorithms on 30 additional healthy subjects. Our results show that our algorithms are able to detect the presence of MN artifacts with sensitivity and specificity of 96.63% and 94.73%, respectively. In addition, when we applied our previously developed algorithm for atrial fibrillation (AF) detection on those segments that have been labeled to be free from MN artifacts, the specificity increased from 73.66% to 85.04% without loss of sensitivity (74.48%-74.62%) on six subjects diagnosed with AF. Finally, the computation time was less than 0.2s using a MATLAB code, indicating that real-time application of the algorithms is possible for Holter monitoring.

Comparison of Sagittal T2-Weighted BLADE and Fast Spin-Echo MRI of the Female Pelvis for Motion Artifact and Lesion Detection

The objective of this study was to evaluate the effectiveness of BLADE (proprietary name for periodically rotated overlapping parallel lines with enhanced reconstruction [PROPELLER] in MR systems from Siemens Healthcare) MRI compared with conventional T2-weighted fast spin-echo (FSE) MRI for reducing artifacts and improving image quality when imaging the female pelvis. Sagittal T2-weighted BLADE and FSE examinations of the pelvis of 26 women were performed on a 1.5-T scanner. Three radiologists assessed the images for the presence of artifacts, level of anatomic detail, and overall image quality using a modified Likert scale. Scores for each radiologist and each imaging sequence were analyzed with a linear mixed model, adjusting for correlation within radiologist and within patient. A quantitative comparison was conducted to investigate signal uniformity. The BLADE sequence was superior for evaluation of the junctional zone (p = 0.0019), delineation of ovarian borders and depiction of follicles (p < 0.0001), and detection of fibroids (p = 0.022). Overall image quality was improved with BLADE, with fewer respiratory motion artifacts. The BLADE sequence introduced "radial" artifact that was absent from the FSE images, but this artifact did not affect image quality. Quantitative analysis revealed mean coefficients of variation for BLADE and FSE in the uterus of 21.6% and 22.5%, respectively (p = 0.36). The mean coefficients of variation were 4.6% and 6.1% in fat (p = 0.0007), indicating less variation with BLADE. The mean acquisition times for the BLADE and FSE sequences were 4 minutes 31 seconds and 3 minutes 46 seconds, respectively. Imaging of uterine junctional zone anatomy, ovaries, and fibroids was improved and artifacts were reduced with BLADE compared with FSE. Radial artifact introduced by the BLADE sequence and slightly longer imaging times needed for the BLADE sequence were offset by improved image quality.

Automatic detection of motion artifacts in the ballistocardiogram measured on a modified bathroom scale

Ballistocardiography (BCG) is a non-invasive technique used to measure the ejection force of blood into the aorta which can be used to estimate cardiac output and contractility change. In this work, a noise sensor was embedded in a BCG measurement system to detect excessive motion from standing subjects. For nine healthy subjects, the cross-correlation of the motion signal to the BCG noise--estimated using a simultaneously acquired electrocardiogram and statistics of the BCG signal--was found to be 0.94 and 0.87, during periods of standing still and with induced motion artifacts, respectively. In a separate study, where 35 recordings were taken from seven subjects, a threshold-based algorithm was used to flag motion-corrupted segments of the BCG signal using only the auxiliary motion sensor. Removing these flagged segments enhanced the BCG signal-to-noise ratio (SNR) by an average of 14 dB (P < 0.001). This integrated motion-sensing technique addresses a gap in methods available to identify and remove noise in standing BCG recordings due to movement, in a practical manner that does not require user intervention or obtrusive sensing.

Two-Stage Approach for Detection and Reduction of Motion Artifacts in Photoplethysmographic Data

Corruption of photopleythysmograms (PPGs) by motion artifacts has been a serious obstacle to the reliable use of pulse oximeters for real-time, continuous state-of-health monitoring. In this paper, we propose an automated, two-stage PPG data processing method to minimize the effects of motion artifacts. The technique is based on our prior work related to motion artifact detection (stage 1) [R. Krishnan, B. Natarajan, and S. Warren, "Analysis and detection of motion artifacts in photoplethysmographic data using higher order statistics,'' in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP 2008), Las Vegas, Nevada, Apr. 2008, pp. 613-616] and motion artifact reduction (stage 2) [R. Krishnan, B. Natarajan, and S. Warren, "Motion artifact reduction in photoplethysmography using magnitude-based frequency domain independent component analysis,'' in Proc. 17th Int. Conf. Comput. Commun. Network, St. Thomas, Virgin Islands, Aug. 2008, pp. 1-5]. Regarding stage 1, we present novel and consistent techniques to detect the presence of motion artifact in PPGs given higher order statistical information present in the data. We analyze these data in the time and frequency domains (FDs) and identify metrics to distinguish between clean and motion-corrupted data. A Neyman-Pearson detection rule is formulated for each of the metrics. Furthermore, by treating each of the metrics as observations from independent sensors, we employ hard fusion and soft fusion techniques presented in [Z. Chair and P. Varshney, "Optimal data fusion in multiple sensor detection systems,'' IEEE Trans. Aerosp. Electron. Syst., AES, vol. 1, no. 1, pp. 98-101, Jan. 1986] and [C. C. Lee and J. J. Chao, "Optimum local decision space partitioning for distributed detection,'' IEEE Trans. Aerosp. Electron. Syst., AES, vol. 25, no. 7, pp. 536-544, Jul. 1989], respectively, in order to fuse individual decisions into a global system decision. For stage two, we propose a motion artifact reduction method that is effective even in the presence of severe subject movement. The approach involves an enhanced preprocessing unit consisting of a motion detection unit (MDU, developed in this paper), period estimation unit, and Fourier series reconstruction unit. The MDU identifies clean data frames versus those corrupted with motion artifacts. The period estimation unit determines the fundamental frequency of a corrupt frame. The Fourier series reconstruction unit reconstructs the final preprocessed signal by utilizing the spectrum variability of the pulse waveform. Preprocessed data are then fed to a magnitude-based FD independent component analysis unit. This helps reduce motion artifacts present at the frequencies of the reconstruction components. Experimental results are presented to demonstrate the efficacy of the overall motion artifact reduction method.

Quantitative image analysis for the detection of motion artefacts in coronary artery computed tomography

Multi detector-row CT (MDCT), the current preferred method for coronary artery disease assessment, is still affected by motion artefacts. To rule out motion artefacts, qualitative image analysis is usually performed. Our study aimed to develop a quantitative image analysis for motion artefacts detection as an added value to the qualitative analysis. An anthropomorphic moving heart phantom with adjustable heart-rate was scanned on 64-MDCT and dual-source-CT. A new software technique was developed which detected motion artefacts in the coronaries and also in the myocardium, where motion artefacts are more apparent; with direct association to the qualitative analysis. The new quantitative analysis managed to detect motion artefacts in phantom scans and relate them to artefact-induced vessel stenoses. Quantifying these artefacts at corresponding locations in the myocardium, artefact-induced vessel stenosis findings could be avoided. In conclusion, the quantitative analysis together with the qualitative analysis rules out artefact-induced stenosis.

Multiple Overlapping k-Space Junctions for Investigating Translating Objects (MOJITO)

It is a well-known property in Fourier transform magnetic resonance imaging (MRI) that rigid body translational motion in image space results in linear phase accumulation in k -space. This work describes Multiple Overlapping k-space Junctions for Investigating Translating Objects (MOJITO), a correction scheme based on phase differences at trajectory intersections caused by 2-D alterations in the position of an object during MR imaging. The algorithm allows both detection and correction of motion artifacts caused by 2-D rigid body translational motion. Although similar in concept to navigator echoes, MOJITO does not require a repeating path through k-space, uses k-space data from a broader region of k -space, and uses the repeated data in image reconstruction; this provides the potential for a highly efficient self-navigating motion correction method. Here, the concept and theoretical basis of MOJITO is demonstrated using the continuous sampling BOWTIE trajectory in simulation and MR experiments. This particular trajectory is selected since it is well suited for such an algorithm due to numerous trajectory intersections. Specifically, the validity of the technique in the presence of noise and off-resonance effects is demonstrated through simulation.

Detection of motion artifacts in optical coherence tomography using the fundus enhancement system

HINTERGRUND: Bei Untersuchungen mit der optischen Koharenztomographie (OCT) sind ausgepragte Bewegungsartefakte erkennbar, Haufigkeit und Auspragung geringer Bewegungen sind aber bislang nicht untersucht worden. ZIEL DER STUDIE war es, Haufigkeit und Ausmas von durch Augenbewegungen wahrend des Untersuchungsprozesses hervorgerufenen Artefakten und Fehlmessungen bei OCT zu untersuchen. METHODEN: Mit Hilfe eines zur Integration von OCT-Bildern in fluoreszenzangiographische Aufnahmen entwickelten Fundusbildsystems (Fundus-Enhancement-System, FES) kann der Scanning-Prozess bei einem konventionellen Zeiss-Stratus-OCT aufgenommen und als Videosequenz verlangsamt wiedergegeben werden. Wir untersuchten mit Hilfe dieses Systems 40 Augen bei 20 gesunden Probanden mit einem Visus von mindestens 1,0; untersucht wurde das Vorhandensein von Bewegungen (Fixationsverlusten) wahrend des Ablaufes des Scans bei je einem 5 mm langen horizontalen und vertikalen Scan durch die Fovea. Gemessene Parameter: Vorhandensein oder Abwesenheit von Augenbewegungen wahrend der Aufnahme und mittlere Abweichung von der geplanten Scanposition in horizontaler oder vertikaler Richtung in Millimeter. ERGEBNISSE: Sieben von 20 gesunden Probanden zeigten uberhaupt keine Bewegung wahrend der Untersuchung. Von den ubrigen 13 Patienten zeigten vier Bewegungen nur auf einer Seite. Die mittlere Abweichung von der gewunschten Position betrug 0,2 mm bei den horizontalen und 0,28 mm bei den vertikalen Scans. SCHLUSSFOLGERUNG: Konventionelle OCT-Systeme konnen erweitert werden, um geringe Augenbewegungen wahrend der Untersuchung zu erfassen. In dieser ersten Serie gesunder Probanden mit voller Sehscharfe traten durch Fixationsverlust bedingte Augenbewegungen bei uber der Halfte der Untersuchungen auf. Auch wenn die Abweichungen von der intendierten Scanposition bei Gesunden gering erscheinen, sind weitere Untersuchungen dieses Phanomens notwendig. OCT wird bei Makulaerkrankungen in zunehmendem Mase als Therapiekontrolle verwendet und das Ausmas bewegungsbedingter Fehler ist bislang nicht untersucht worden.

SMASH navigators.

The additional data acquired when using multiple receiver coils is commonly used to improve SNR or reduce acquisition times. It may also be used to remove image artifacts by selectively replacing corrupt data. In the present study, a correction scheme is presented based on simultaneous acquisition of spatial harmonics (SMASH) that enables detection and correction of motion artifacts caused by 2D translations. Newly measured data is compared with predictions from previously measured data by making negative and positive spatial harmonics. Differences are attributed to motion occurring in the interval between the acquisition of separate phase encode lines and correction parameters are determined. Two types of rigid body motion are considered: 1) object and coil array move, and 2) object only moves, since each causes different phase errors in k-space. Simulation, phantom, and volunteer experiments demonstrate the validity of the technique.

Detection and elimination of motion artifacts by regeneration of k-space.

A method has been developed using techniques from partially parallel imaging (PPI) to detect localized inconsistencies in k-space that are caused by certain types of motion. The inconsistent data are discarded and consistent data regenerated from the remaining data using PPI techniques. The price is a small decrease in signal-to-noise ratio (SNR) and additional postprocessing. An iterative scheme is presented which does not require separately acquired coil sensitivity information for the PPI reconstructions. This method has been found to reduce artifact levels in phantom and in vivo test studies.

Detection and deletion of motion artifacts in electrogastrogram using feature analysis and neural networks.

Electrogastrogram is a surface measurement of gastric myoelectrical activity, and electrogastrography has been an attractive method for physiological and pathophysiological studies of the stomach due to its noninvasive nature. Motion artifacts, however, ruin the electrogastrogram (EGG), and make the analysis very difficult and sometimes even impossible. They must be eliminated from EGG signals before analysis. Up to now, this can only be done by visual inspection, which is not only time-consuming but also subjective. In this study, a method using feature analysis and neural networks has been developed to realize automatic detection and elimination of the motion artifacts in EGG recordings by computer. Experiments were conducted to investigate the characteristics of different motion artifacts. Useful features were extracted, and different combinations of the features used as the input of the neural network were compared to obtain the optimal performance for the detection of motion artifacts using the artificial neural network.

Real-time direct volume rendering in functional magnetic resonance imaging.

Direct volume rendering is a visualization method that allows display of all information hidden in three-dimensional data sets of, for example, computed tomography or magnetic resonance imaging (MRI). In contrast to commonly used surface rendering methods, these algorithms need no preprocessing but suffer from a high computational complexity. A real-time rendering system, VIRIM (Vitec: Visualization Technology GmbH, Mannheim, Germany), cuts down rendering times of minutes on normal workstations to an interactive rate of 1 second or less. The immediate visual feedback allows interactive steering of the visualization process to achieve insight into the internal three-dimensional structure of objects. Additional information is obtained by using an interactive gray-value segmentation tool that both allows segmentation of the data set according to bone, tissue, and liquor and display of multifunctional data sets (e.g., functional MRI [fMRI] data sets). Thus, real-time direct volume rendering allows segmentation and volume data processing of functional and anatomical MR data sets simultaneously. As this method can be integrated in the clinical routine, it is of great importance for real-time motion artifact detection and the interpretation of fMRI data acquired during cognitive experiments with normal subjects and psychiatric patients. Because of the free programmability of VIRIM, more complex matching procedures are currently being investigated for future implementation.