Hello,
I am currently engaged in fatigue modeling using AnyFatigueModelM specifically for elbow flexion. In my analysis, I employed the following parameters based on the technical notes:
FatigueCoef: 1/60
RecoveryCoef: 2.4/60
RecoveryActivity: 1e-3
During my observations, I noted that the Fatigue Capacity (FC) was highly sensitive to the FatigueCoef, while the RecoveryCoef had a minimal effect. It is important to mention that the AnyFatigueModelM has only been validated with isometric data.
I would appreciate your insights on the following questions:
What is the significance of the RecoveryCoef and RecoveryActivity in the context of the model?
Is it feasible to apply this model to isokinetic data?
How can the fatigue parameters be appropriately scaled when using isometric/isokinetic data?
I will start with RecoveryActivity. In AnyFatigueModelM, recovery happens when the muscle is not activated. This is modelled by defining a recovery threshold activity, i.e. RecoveryActivity, in AMS (muscle can still fatigue below the threshold activity).
Recovery coefficient is the rate of muscle recovery. In your simulations, I believe, the RecoveryActivity value is so low that the muscles never get a chance to recover. You mentioned about elbow flexion, but do you have some time in your simulation with low muscle activity so that the muscles can recover? You may also need to bump up RecoveryActivity since there might be some muscle activity just due to gravity.
You could also try AnyFatigueModel3CM, where fatigue and recovery happen simultaneously.
About using these models for isokinetic data, this is a hard question to answer since most of the literature mentions about using these models in isometric tasks. So, to be honest, I don't know if the models will accurately capture dynamic situations. Likewise, for scaling the coefficients, there is no magic formula that I am aware of. Perhaps, there is some new literature looking into this that I am not aware of.