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Sampling rate and the estimation of ensamble variability for repetive signals

Laguna, P. and Sörnmo, Leif LU (2000) In Medical & Biological Engineering & Computing 38(5). p.540-546
Abstract
The measurement of ensemble variability in time-aligned event signals is studied in relation to sampling rate requirements. The theoretical analysis is based on statistical modelling of time misalignment in which the time resolution is limited by the length of the sampling interval. For different signal-to-noise ratios (SNRs), the sampling rate is derived which limits the misalignment effect to less than 10% of the noise effect. Each signal is assumed to be corrupted by additive noise. Using a normal QRS complex with a high SNR (≈ 30 dB), a sampling rate of approximately 3 kHz is needed for accurate ensemble variability measurements. This result is surprising since it implies that the Nyquist rate is far too low for accurate variability... (More)
The measurement of ensemble variability in time-aligned event signals is studied in relation to sampling rate requirements. The theoretical analysis is based on statistical modelling of time misalignment in which the time resolution is limited by the length of the sampling interval. For different signal-to-noise ratios (SNRs), the sampling rate is derived which limits the misalignment effect to less than 10% of the noise effect. Each signal is assumed to be corrupted by additive noise. Using a normal QRS complex with a high SNR (≈ 30 dB), a sampling rate of approximately 3 kHz is needed for accurate ensemble variability measurements. This result is surprising since it implies that the Nyquist rate is far too low for accurate variability measurements. The theoretical results are supplemented with results obtained from an ECG database of 94 subjects for which the ensemble variability is computed at different sampling rates using signal interpolation. The ensemble variability is substantially reduced (40%) when increasing the rate from 1 to 3 kHz, thus corroborating the results suggested by the theoretical analysis. (Less)
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author
and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Nyquist rate, Time-aligned signals, Ensemble variability, Sampling rate, ECG database
in
Medical & Biological Engineering & Computing
volume
38
issue
5
pages
540 - 546
publisher
Springer
external identifiers
  • scopus:0034281892
ISSN
0140-0118
DOI
10.1007/BF02345750
language
English
LU publication?
yes
id
57119625-d6c9-4834-9db6-b84041f749cc (old id 1758864)
date added to LUP
2016-04-04 09:35:13
date last changed
2022-01-29 18:32:39
@article{57119625-d6c9-4834-9db6-b84041f749cc,
  abstract     = {{The measurement of ensemble variability in time-aligned event signals is studied in relation to sampling rate requirements. The theoretical analysis is based on statistical modelling of time misalignment in which the time resolution is limited by the length of the sampling interval. For different signal-to-noise ratios (SNRs), the sampling rate is derived which limits the misalignment effect to less than 10% of the noise effect. Each signal is assumed to be corrupted by additive noise. Using a normal QRS complex with a high SNR (≈ 30 dB), a sampling rate of approximately 3 kHz is needed for accurate ensemble variability measurements. This result is surprising since it implies that the Nyquist rate is far too low for accurate variability measurements. The theoretical results are supplemented with results obtained from an ECG database of 94 subjects for which the ensemble variability is computed at different sampling rates using signal interpolation. The ensemble variability is substantially reduced (40%) when increasing the rate from 1 to 3 kHz, thus corroborating the results suggested by the theoretical analysis.}},
  author       = {{Laguna, P. and Sörnmo, Leif}},
  issn         = {{0140-0118}},
  keywords     = {{Nyquist rate; Time-aligned signals; Ensemble variability; Sampling rate; ECG database}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{540--546}},
  publisher    = {{Springer}},
  series       = {{Medical & Biological Engineering & Computing}},
  title        = {{Sampling rate and the estimation of ensamble variability for repetive signals}},
  url          = {{http://dx.doi.org/10.1007/BF02345750}},
  doi          = {{10.1007/BF02345750}},
  volume       = {{38}},
  year         = {{2000}},
}