  Stochastic thermodynamics is an important development in the direction of
finding general thermodynamic principles for non-equilibrium systems. We
believe stochastic thermodynamics has the potential to benefit from the
measure-theoretic framework of stochastic differential equations. Towards this,
in this work, we show that Fluctuation Theorem (FT) is a special case of the
Girsanov theorem, which is an important result in the theory of stochastic
differential equations. We report that by employing Girsanov transformation of
measures between the forward and the reversed dynamics of a general class of
Langevin dynamic systems, we arrive at the Integral Fluctuation Relation.
Following the same approach, we derive the FT also for the overdamped case. Our
derivation is applicable to both transient and steady state conditions and can
also incorporate diffusion coefficients varying as a function of state and
time. We expect that the proposed method will be an easy route towards deriving
the FT irrespective of the complexity and non-linearity of the system.
