Journal ArticleDOI
Biomedical signal processing (in four parts). Part 1. Time-domain methods.
R. E. Challis,R I Kitney +1 more
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This paper provides an introduction to terminology and basic ideas for testing for randomness and trend, and for the determination of basic signal properties in the time domain, given the uncertainties associated with the estimation process.Abstract:
This is the first of a series of four tutorial papers on biomedical signal processing. It provides an introduction to terminology and basic ideas for testing for randomness and trend, and for the determination of basic signal properties in the time domain, given the uncertainties associated with the estimation process. Techniques outlined in the paper are: the coherent average, cross-correlation and covariance, autocorrelation and phase-shift averaging.read more
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Journal ArticleDOI
Time--frequency feature representation using energy concentration: An overview of recent advances
TL;DR: Time-frequency domain signal processing using energy concentration as a feature is a very powerful tool and has been utilized in numerous applications and the expectation is that further research and applications of these algorithms will flourish in the near future.
Journal ArticleDOI
Motor Patterns for Human Gait: Backward Versus Forward Locomotion
TL;DR: It is argued that conservation of kinematic templates across gait reversal at the expense of a complete reorganization of muscle synergies does not arise from biomechanical constraints but may reflect a behavioral goal achieved by the central networks involved in the control of locomotion.
Journal ArticleDOI
EEG-EMG, MEG-EMG and EMG-EMG frequency analysis: physiological principles and clinical applications.
TL;DR: The main thrust of this review is to critically evaluate the utility of frequency analysis techniques in the investigation of pathophysiological mechanisms in the motor system and as a diagnostic tool.
Journal ArticleDOI
Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network
Sung-Nien Yu,Ying-Hsiang Chen +1 more
TL;DR: The result shows a promising accuracy of 99.65%, with equally well recognition rates of over 99% throughout all type of ECG beats, which proves the effectiveness and efficiency of the proposed method for computer-aided diagnosis of heart diseases based on ECG signals.
Journal ArticleDOI
A review on prognostic techniques for non-stationary and non-linear rotating systems
TL;DR: In this paper, the authors present a review of the applicability of prognostic techniques for rotating machinery operating under non-linear and non-stationary conditions, as well as their application in the research field.
References
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Book
The Analysis of Time Series: An Introduction
TL;DR: In this paper, simple descriptive techniques for time series estimation in the time domain forecasting stationary processes in the frequency domain spectral analysis bivariate processes linear systems state-space models and the Kalman filter non-linear models multivariate time series modelling some other topics.
Journal ArticleDOI
Characterization of an adaptive filter for the analysis of variable latency neuroelectric signals
TL;DR: In this paper, an adaptive filter system has been developed whereby variable latency neuroelectric signals may be detected and separated from associated noise, based on correlation-averaging techniques which are described in detail.
Book
An Introduction to the Analysis and Processing of Signals
TL;DR: Part 1 Signal analysis: periodic signals - the Fourier series aperiodic signals -the Fourier transform, use of the Laplace transform sampled-data signals random signals - Gaussian signals signal comparison.
Journal ArticleDOI
Coherent averaging technique: a tutorial review. Part 1: Noise reduction and the equivalent filter.
O. Rompelman,H.H. Ros +1 more
TL;DR: The improvement in s/n ratio due to averaging is calculated and it is shown that averaging acts as a filter which attenuates periodic interference when it is not time-locked to the stimulus.
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Biomedical signal processing (in four parts). Part 3. The power spectrum and coherence function.
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