19,513 research outputs found
Detection of Change--Points in the Spectral Density. With Applications to ECG Data
We propose a new method for estimating the change-points of heart rate in the
orthosympathetic and parasympathetic bands, based on the wavelet transform in
the complex domain and the study of the change-points in the moments of the
modulus of these wavelet transforms. We observe change-points in the
distribution for both bands.Comment: proceeding of the workshop 'Fouille de donn\'ees temporelles et
analyse de flux de donn\'ees' EGC'2009, january 27, Strasbourg, Franc
Multifractality in Human Heartbeat Dynamics
Recent evidence suggests that physiological signals under healthy conditions
may have a fractal temporal structure. We investigate the possibility that time
series generated by certain physiological control systems may be members of a
special class of complex processes, termed multifractal, which require a large
number of exponents to characterize their scaling properties. We report on
evidence for multifractality in a biological dynamical system --- the healthy
human heartbeat. Further, we show that the multifractal character and nonlinear
properties of the healthy heart rate are encoded in the Fourier phases. We
uncover a loss of multifractality for a life-threatening condition, congestive
heart failure.Comment: 19 pages, latex2e using rotate and epsf, with 5 ps figures; to appear
in Nature, 3 June, 199
Long-Distance Quantum Communication with Entangled Photons using Satellites
The use of satellites to distribute entangled photon pairs (and single
photons) provides a unique solution for long-distance quantum communication
networks. This overcomes the principle limitations of Earth-bound technology,
i.e. the narrow range of some 100 km provided by optical fiber and terrestrial
free-space links.Comment: 12 pages, 7 figures; submitted to IEEE Journal of Selected Topics in
Quantum Electronics, special issue on "Quantum Internet Technologies
Model validation for a noninvasive arterial stenosis detection problem
Copyright @ 2013 American Institute of Mathematical SciencesA current thrust in medical research is the development of a non-invasive method for detection, localization, and characterization of an arterial stenosis (a blockage or partial blockage in an artery). A method has been proposed to detect shear waves in the chest cavity which have been generated by disturbances in the blood flow resulting from a stenosis. In order to develop this methodology further, we use both one-dimensional pressure and shear wave experimental data from novel acoustic phantoms to validate corresponding viscoelastic mathematical models, which were developed in a concept paper [8] and refined herein. We estimate model parameters which give a good fit (in a sense to be precisely defined) to the experimental data, and use asymptotic error theory to provide confidence intervals for parameter estimates. Finally, since a robust error model is necessary for accurate parameter estimates and confidence analysis, we include a comparison of absolute and relative models for measurement error.The National Institute of Allergy and Infectious Diseases, the Air Force Office of Scientific Research, the Deopartment of Education and the Engineering and Physical Sciences Research Council (EPSRC)
Proceedings of Abstracts Engineering and Computer Science Research Conference 2019
© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care
Heart Rate Monitoring During Different Lung Volume Phases Using Seismocardiography
Seismocardiography (SCG) is a non-invasive method that can be used for
cardiac activity monitoring. This paper presents a new electrocardiogram (ECG)
independent approach for estimating heart rate (HR) during low and high lung
volume (LLV and HLV, respectively) phases using SCG signals. In this study,
SCG, ECG, and respiratory flow rate (RFR) signals were measured simultaneously
in 7 healthy subjects. The lung volume information was calculated from the RFR
and was used to group the SCG events into low and high lung-volume groups. LLV
and HLV SCG events were then used to estimate the subjects HR as well as the HR
during LLV and HLV in 3 different postural positions, namely supine, 45 degree
heads-up, and sitting. The performance of the proposed algorithm was tested
against the standard ECG measurements. Results showed that the HR estimations
from the SCG and ECG signals were in a good agreement (bias of 0.08 bpm). All
subjects were found to have a higher HR during HLV (HR) compared
to LLV (HR) at all postural positions. The
HR/HR ratio was 1.110.07, 1.080.05,
1.090.04, and 1.090.04 (meanSD) for supine, 45 degree-first
trial, 45 degree-second trial, and sitting positions, respectively. This heart
rate variability may be due, at least in part, to the well-known respiratory
sinus arrhythmia. HR monitoring from SCG signals might be used in different
clinical applications including wearable cardiac monitoring systems
Embedded star clusters as sources of high-energy cosmic rays: Modelling and constraints
Massive stars are mainly found in stellar associations. These massive star
clusters occur in the heart of giant molecular clouds. The strong stellar wind
activity in these objects generates large bubbles and induces collective
effects that could accelerate particles up to high energy and produce gamma
rays. The best way to input an acceleration origin to the stellar wind
interaction in massive stellar cluster is to observe young massive star
clusters in which no supernova explosion has occurred yet.
This work aims to constrain the part of stellar wind mechanical energy that
is converted into energetic particles using the sensitivity of the ongoing
Fermi/LAT instrument. This work further provides detailed predictions of
expected gamma-ray fluxes in the view of the on-set of the next generation of
imaging atmospheric Cherenkov telescopes.
A one-zone model where energetic particles are accelerated by repeated
interactions with strong supersonic shocks occurring in massive star clusters
was developed. The particle escape from the star cluster and subsequent
interaction with the surrounding dense material and magnetic fields of the HII
region was computed. We applied this model to a selection of eight embedded
star clusters constricted by existing observations. We evaluated the gamma-ray
signal from each object, combining both leptonic and hadronic contributions. We
searched for these emissions in the Fermi/LAT observations in the energy range
from 3 to 300 GeV and compared them to the sensitivity of the Cherenkov
Telescope Array.
No significant gamma-ray emission from these star clusters has been found.
Less than 10% of stellar wind luminosities are supplied to the relativistic
particles. Some clusters even show acceleration efficiency of less than 1%. The
CTA would be able to detect gamma-ray emission from several clusters in the
case of an acceleration efficiency of close to 1%.Comment: accepted for publication in Astronomy&Astrophysic
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