Ambulatory ElectroCardioGram (ECG) analysis is adversely affected by motion artifacts induced due to body movements. Knowledge of the extent of motion artifacts could facilitate better ECG analysis. In this paper, our purpose is to determine the impact of body movement kinematics on the extent of ECG motion artifact by defining a notion called impact signal. Two approaches have been adopted in this paper to validate our experiments. One of them involves measuring local acceleration using motion sensors at appropriate body positions, in conjunction with the ECG, while performing routine activities at different intensity levels. The other method consists of ECG acquisition during Treadmill testing at controlled speeds and fixed duration. Data has been acquired from both healthy subjects as well as patients with suspected cardio-vascular disorders. In case of patients, the treadmill tests were carried out under the supervision of a cardiologist. We demonstrate that the impact signal shows a proportional increase with the increasing activity levels. The measured accelerations obtained are also found to be well correlated with the impact signal. The impact analysis thus indicates the suitability of the proposed method for quantification of body movement kinematics from the ECG signal itself, even in the absence of any accelerometer sensors. Such quantification would also help in automatic documentation of patient activity levels, which could aid in better interpretation of ambulatory ECG.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10439-008-9526-8 | DOI Listing |
Cell Commun Signal
January 2025
Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Background: Ovarian cancer (OC), particularly high-grade serous ovarian carcinoma (HGSOC), is the leading cause of mortality from gynecological malignancies worldwide. Despite the initial effectiveness of treatment, acquired resistance to poly(ADP-ribose) polymerase inhibitors (PARPis) represents a major challenge for the clinical management of HGSOC, highlighting the necessity for the development of novel therapeutic strategies. This study investigated the role of 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a pivotal regulator of glycolysis, in PARPi resistance and explored its potential as a therapeutic target to overcome PARPi resistance.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Medical Biology, Albert Szent-Györgyi Medical School, University of Szeged, Somogyi u. 4, Szeged, 6720, Hungary.
In our research, we performed temporal transcriptomic profiling of host cells infected with Equid alphaherpesvirus 1 (EHV-1) by utilizing direct cDNA sequencing based on nanopore MinION technology. The sequencing reads were harnessed for transcript quantification at various time points. Viral infection-induced differential gene expression was identified through the edgeR package.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center-University of Freiburg, Freiburg, Germany.
The characteristics of data produced by omics technologies are pivotal, as they critically influence the feasibility and effectiveness of computational methods applied in downstream analyses, such as data harmonization and differential abundance analyses. Furthermore, variability in these data characteristics across datasets plays a crucial role, leading to diverging outcomes in benchmarking studies, which are essential for guiding the selection of appropriate analysis methods in all omics fields. Additionally, downstream analysis tools are often developed and applied within specific omics communities due to the presumed differences in data characteristics attributed to each omics technology.
View Article and Find Full Text PDFSci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA.
The aberrant vascular response associated with tendon injury results in circulating immune cell infiltration and a chronic inflammatory feedback loop leading to poor healing outcomes. Studying this dysregulated tendon repair response in human pathophysiology has been historically challenging due to the reliance on animal models. To address this, our group developed the human tendon-on-a-chip (hToC) to model cellular interactions in the injured tendon microenvironment; however, this model lacked the key element of physiological flow in the vascular compartment.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!