||This paper presents a motion-adaptive approach to duty-cycling the orientation estimation of a wearable inertial measurement unit (IMU). Specifically, a proportional forward-controller was employed to dynamically tune the sampling and orientation update rate of a Madgwick filter. An energy model was defined to estimate the power consumed by individual inertial sensors and processing elements. We demonstrate the efficacy of our controller by analysing multi-day free-living motion recordings of wrist-worn IMUs. In a comparison of the orientation estimation between the full duty-cycle and the adaptive one, average error was approx. 10 degrees while saving more than 30% of sensor node energy. To assess the orientation information retained by our approach, we analysed the binary pattern classification performance for recognising food and fluid intake gestures. Recognition performance of the motion-adaptive duty-cycling remained above 90% up to an energy saving of approx. 32.5%, confirming the profound potential of the method.