ECG Noise Filtering Using Online Model-Based Bayesian Filtering Techniques

The electrocardiogram (ECG) is a time-varying electrical signal that interprets the electrical activity of the heart. It is obtained by a non-invasive technique known as surface electromyography (EMG), used widely in hospitals. There are many clinical contexts in which ECGs are used, such as medical diagnosis, physiological therapy and arrhythmia monitoring. In medical diagnosis, medical conditions are interpreted by examining information and features in ECGs. Physiological therapy involves the control of some aspect of the physiological effort of a patient, such as the use of a pacemaker to regulate the beating of the heart. Moreover, arrhythmia monitoring involves observing and detecting life-threatening conditions, such as myocardial infarction or heart attacks, in a patient. ECG signals are usually corrupted with various types of unwanted interference such as muscle artifacts, electrode artifacts, power line noise and respiration interference, and are distorted in such a way that it can be difficult to perform medical diagnosis, physiological therapy or arrhythmia monitoring. Consequently signal processing on ECGs is required to remove noise and interference signals for successful clinical applications. Existing signal processing techniques can remove some of the noise in an ECG signal, but are typically inadequate for extraction of the weak ECG components contaminated with background noise and for retention of various subtle features in the ECG. For example, the noise from the EMG usually overlaps the fundamental ECG cardiac components in the frequency domain, in the range of 0.01 Hz to 100 Hz. Simple filters are inadequate to remove noise which overlaps with ECG cardiac components. Sameni et al. have proposed a Bayesian filtering framework to resolve these problems, and this gives results which are clearly superior to the results obtained from application of conventional signal processing methods to ECG. However, a drawback of this Bayesian filtering framework is that it must run offline, and this of course is not desirable for clinical applications such as arrhythmia monitoring and physiological therapy, both of which re- quire online operation in near real-time. To resolve this problem, in this thesis we propose a dynamical model which permits the Bayesian filtering framework to function online. The framework with the proposed dynamical model has less than 4% loss in performance compared to the previous (offline) version of the framework. The proposed dynamical model is based on theory from fixed-lag smoothing

Search for CPCP violation in D0^0→\to KS0^0_\mathrm{S}KS0^0_\mathrm{S} decays in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceA search is reported for charge-parity D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$$CP$ violation in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ decays, using data collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6 fb$^{-1}$, which consists of about 10 billion events containing a pair of ẖadrons, nearly all of which decay to charm hadrons. The flavor of the neutral D meson is determined by the pion charge in the reconstructed decays D$^{*+}$$\to$ D$^0\pi^+$ and D$^{*-}$$\to$ D$^0\pi^-$. The D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$$CP$ asymmetry in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ is measured to be $A_{CP}$( K$^0_\mathrm{S}$K$^0_\mathrm{S}$) = (6.2 $\pm$ 3.0 $\pm$ 0.2 $\pm$ 0.8)%, where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the D$^0$ $\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ $CP$ asymmetry in the D$^0$ $\to$ K$^0_\mathrm{S}\pi^+\pi^-$ decay. This is the first D$^0$ $\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ $CP$ asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state

Observation of the J/ψ\psi →\to μ+μ−μ+μ−\mu^+\mu^-\mu^+\mu^- decay in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceThe J/$\psi$$\to$$\mu^+\mu^-\mu^+\mu^-$ decay has been observed with a statistical significance in excess of five standard deviations. The analysis is based on an event sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment in 2018 and corresponding to an integrated luminosity of 33.6 fb${-1}$. Normalizing to the J/$\psi$$\to$$\mu^+\mu^-$ decay mode leads to a branching fraction [10.1$^{+3.3}_{-2.7}$ (stat) $\pm$ 0.4 (syst) ]$\times$ 10$^{-7}$, a value that is consistent with the standard model prediction

Enriching the physics program of the CMS experiment via data scouting and data parking

International audienceSpecialized data-taking and data-processing techniques were introduced by the CMS experiment in Run 1 of the CERN LHC to enhance the sensitivity of searches for new physics and the precision of standard model measurements. These techniques, termed data scouting and data parking, extend the data-taking capabilities of CMS beyond the original design specifications. The novel data-scouting strategy trades complete event information for higher event rates, while keeping the data bandwidth within limits. Data parking involves storing a large amount of raw detector data collected by algorithms with low trigger thresholds to be processed when sufficient computational power is available to handle such data. The research program of the CMS Collaboration is greatly expanded with these techniques. The implementation, performance, and physics results obtained with data scouting and data parking in CMS over the last decade are discussed in this Report, along with new developments aimed at further improving low-mass physics sensitivity over the next years of data taking

Observation of the J/ψ\psi→\toμ+μ−μ+μ−\mu^+\mu^-\mu^+\mu^- decay in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceThe J/$\psi$$\to$$\mu^+\mu^-\mu^+\mu^-$ decay has been observed with a statistical significance in excess of five standard deviations. The analysis is based on an event sample of proton-proton collisions at a center-of-mass energy of 13 TeV, collected by the CMS experiment in 2018 and corresponding to an integrated luminosity of 33.6 fb${-1}$. Normalizing to the J/$\psi$$\to$$\mu^+\mu^-$ decay mode leads to a branching fraction [10.1$^{+3.3}_{-2.7}$ (stat) $\pm$ 0.4 (syst) ]$\times$ 10$^{-7}$, a value that is consistent with the standard model prediction

The CMS Statistical Analysis and Combination Tool: COMBINE

International audienceThis paper describes the COMBINE software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run COMBINE and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of COMBINE. However, the online documentation referenced within this paper provides an up-to-date and complete user guide

Search for the Z boson decay to ττμμ\tau\tau\mu\mu in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceThe first search for the Z boson decay to $\tau\tau\mu\mu$ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138 fb$^{-1}$. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.9 times the standard model expectation is placed on the ratio of the Z $\to$ $\tau\tau\mu\mu$ to Z $\to$ 4$\mu$ branching fractions. Limits are also placed on the six flavor-conserving four-lepton effective-field-theory operators involving two muons and two tau leptons, for the first time testing all such operators

Search for soft unclustered energy patterns in proton-proton collisions at 13 TeV

International audienceThe first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138 fb$^{-1}$ of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by Hidden Valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics. With no observed excess of events over the standard model expectation, limits are set on the cross section for production via gluon fusion of a scalar mediator with SUEP-like decays

Search for the Z boson decay to ττμμ\tau\tau\mu\mu in proton-proton collisions at s\sqrt{s} = 13 TeV

International audienceThe first search for the Z boson decay to $\tau\tau\mu\mu$ at the CERN LHC is presented, based on data collected by the CMS experiment at the LHC in proton-proton collisions at a center-of-mass energy of 13 TeV and corresponding to an integrated luminosity of 138 fb$^{-1}$. The data are compatible with the predicted background. For the first time, an upper limit at the 95% confidence level of 6.9 times the standard model expectation is placed on the ratio of the Z $\to$ $\tau\tau\mu\mu$ to Z $\to$ 4$\mu$ branching fractions. Limits are also placed on the six flavor-conserving four-lepton effective-field-theory operators involving two muons and two tau leptons, for the first time testing all such operators