The aging process in principal component analysis of posturographic signals

@inproceedings{Michalak2014TheAP,
  title={The aging process in principal component analysis of posturographic signals},
  author={Krzysztof Michalak and Anna Przekoracka-Krawczyk and Paweł Nawrot and Piotr Woźniak and P. Vieregge},
  year={2014}
}
Objective: High-pass filtering is able to remove slow oscillations in lower frequencies and releases postural reflexes with low amplitudes in the range of higher frequencies. Methods: Principal Component Analysis (PCA) was used for determining mutual dependences between the x and y components of posturographic signals (s2) which is defined as the ratio between the second and first components of the resulting PCA matrix. The posturographic signals in older patients with idiopathic gait… CONTINUE READING

References

Publications referenced by this paper.
SHOWING 1-10 OF 19 REFERENCES

Detecting high-dimensional determinism in time series with application to human movement data

  • S Ramdani, F Bouchara, O. Caron
  • Nonlinear Anal-Real ,
  • 2012

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