Open Access
Modeling of noisy acceleration signals from quasi-periodic movements for drift-free position estimation
(IEEE, 2019) Zivanovic, Miroslav; Millor Muruzábal, Nora; Gómez Fernández, Marisol; Estadística, Informática y Matemáticas; Ingeniería Eléctrica, Electrónica y de Comunicación; Estatistika, Informatika eta Matematika; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
We present a novel approach to drift-free position estimation from noisy acceleration signals which often arise from quasi-periodic small-amplitude body movements. In contrast to the existing methods, this data-driven strategy is designed to properly describe time-variant harmonic structures in single-channel acceleration signals for low signal-to-noise ratios. Methods: It comprises three processing steps: (1) shorttime modeling of acceleration dynamics (instantaneous harmonic amplitudes and phases) in the analysis frame, (2) analytical integration which yields short-time position, and (3) overlap-add recombination for full length position synthesis. Results: The comparative results, obtained from the medio-lateral Xacceleration components from 30s Chair Stand Test recordings, suggest that the proposed method outperforms two state-of-theart reference methods in terms of Euclidean error, root mean square error, correlation coefficient and harmonic-to-noise ratio. Conclusion: A major benefit of the method is that acceleration signal components unrelated to movement are suppressed in the whole analysis bandwidth, which allows for position estimation completely free of low-frequency artifacts. Significance: We believe that the method can be useful in frailty assessment in elderly population, as well as in clinical applications related to gait analysis in aging and rehabilitation.
Open Access
Astronomical component estimation (ACE v.1) by time-variant sinusoidal modeling
(Copernicus Publications, 2016) Sinnesael, Matthias; Zivanovic, Miroslav; De Vleeschouwer, David; Claeys, Philippe; Schoukens, Johan; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
Accurately deciphering periodic variations in paleoclimate proxy signals is essential for cyclostratigraphy. Classical spectral analysis often relies on methods based on (fast) Fourier transformation. This technique has no unique solution separating variations in amplitude and frequency. This characteristic can make it difficult to correctly interpret a proxy's power spectrum or to accurately evaluate simultaneous changes in amplitude and frequency in evolutionary analyses. This drawback is circumvented by using a polynomial approach to estimate instantaneous amplitude and frequency in orbital components. This approach was proven useful to characterize audio signals (music and speech), which are non-stationary in nature. Paleoclimate proxy signals and audio signals share similar dynamics; the only difference is the frequency relationship between the different components. A harmonic-frequency relationship exists in audio signals, whereas this relation is non-harmonic in paleoclimate signals. However, this difference is irrelevant for the problem of separating simultaneous changes in amplitude and frequency. Using an approach with overlapping analysis frames, the model (Astronomical Component Estimation, version 1: ACE v.1) captures time variations of an orbital component by modulating a stationary sinusoid centered at its mean frequency, with a single polynomial. Hence, the parameters that determine the model are the mean frequency of the orbital component and the polynomial coefficients. The first parameter depends on geologic interpretations, whereas the latter are estimated by means of linear least-squares. As output, the model provides the orbital component waveform, either in the depth or time domain. Uncertainty analyses of the model estimates are performed using Monte Carlo simulations. Furthermore, it allows for a unique decomposition of the signal into its instantaneous amplitude and frequency. Frequency modulation patterns reconstruct changes in accumulation rate, whereas amplitude modulation identifies eccentricity-modulated precession. The functioning of the time-variant sinusoidal model is illustrated and validated using a synthetic insolation signal. The new modeling approach is tested on two case studies: (1) a Pliocene–Pleistocene benthic δ18O record from Ocean Drilling Program (ODP) Site 846 and (2) a Danian magnetic susceptibility record from the Contessa Highway section, Gubbio, Italy.

Zivanovic, Miroslav

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