This paper presents the stochastic modeling of isometric force variability in the steady-state time series recorded from the index finger of young adults in the act of attempting to hold different levels of constant force. The isometric force time series were examined by assuming that the stochastic (random) models were linear. System identification techniques were employed to estimate the parameters of each linear model. Once the models were parameterized, the values of the estimated parameters were compared to determine if a single linear time-invariant model was applicable across the entire isometric force range. Although the overall random models were found to be nonlinear functions of the target force level, within a fixed target level, linear modeling provided adequate estimates of the underlying processes thus enabling the use of well-known linear system identification algorithms.
All Science Journal Classification (ASJC) codes
- Physical Therapy, Sports Therapy and Rehabilitation
- Clinical Neurology
- Physiology (medical)