Mobile Users ECG Signal Processing

Plesnik, Emil; Zajc, Matej

doi:10.1007/978-3-642-37169-1_31

Cited by 1 publication

(2 citation statements)

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“…The signal is transformed from time domain to the phase space ‫ݔ‬ሾ݇ሿ ൌ ‫ݏ‬ሾ݇ሿǡ ‫ݕ‬ሾ݇ሿ ൌ ‫ݏ‬ሾ݇ ͳሿ െ ‫ݏ‬ሾ݇ሿ, for ͳ ൏ ݇ ൏ ܰ െ ͳ (2) and normalized…”

Section: A Phase Space Transformationmentioning

confidence: 99%

“…This makes the mobile user's environment, where the monitored person is moving constantly during daily routine, a significant signal processing challenge, especially when the specific design requirements for the monitoring equipment (wireless, low-power, mobile, unobtrusive, etc.) are also considered [2]. To support reliable interpretation of the acquired data computationally simple, fast and efficient algorithms for noise cancellation are required.…”

Section: Introductionmentioning

confidence: 99%

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Improved removal of electrocardiogram baseline wandering

et al. 2013

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Baseline wandering interference causes inaccurate detection of electrocardiogram (ECG) characteristics such as detection of the R point. This paper presents a novel phase spacebased approach for baseline wandering removal of ECG signals. The baseline wander contaminated ECG signal is transformed to the phase space by using the signal derivative. Baseline wandering was eliminated by shifting loops of the ECG phase portrait on a predefined fixed position. This resulted in signal discontinuities in time domain which were solved using linear correction. The method was evaluated on synthetized ECG signals and on signals from the MIT-BIH database. Results show an improvement of signal-to-noise ratio after baseline wandering removal in phase space, comparable with related works, and efficient elimination of time-domain discontinuities in time domain.

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Section: A Phase Space Transformationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%