Abstract
The aim of this study was to develop and evaluate a model based upon four identified characteristics of the power spectral density associated with isometric force at a range of constant force levels (5-95% maximum voluntary contraction). The characteristics modeled were: (1) a low-frequency resonant peak located at about 1 Hz; (2) a region of 1/f-like fractional Gaussian noise (fGn); (3) the resonant peak in the 8-12 Hz region on the PSD; and (4) Gaussian white noise resulting from a combination of neural as well as equipment noise. When superimposed, these components were used in a direct fit to the isometric force data to generate a linear predictor that resulted in residual values on the order of the white noise present in the original force time series.
Original language | English (US) |
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Pages (from-to) | 137-144 |
Number of pages | 8 |
Journal | Biological Cybernetics |
Volume | 102 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2010 |
All Science Journal Classification (ASJC) codes
- Biotechnology
- Computer Science(all)