Before revision:  For this, we consider that the motor signal arises from the residual errors in the cognitive expectation about the nonstationary sensory inputs at the proprioceptive level.
After revision:  We build a Bayesian mechanics (BM) by casting the formulation reported in the earlier publication (Kim 2018) to considering active inference beyond passive perception. The BM is a neural implementation of variational Bayes under the FEP in continuous time. The resulting BM is provided as an effective Hamilton's equation of motion and subject to the control signal arising from the brain's prediction errors at the proprioceptive level.