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Recent advances in ultra-low-power circuits and energy harvesters are making self-powered body wireless autonomous transducer solutions (WATS) a reality. Power optimization at the system and application level is crucial in achieving ultra-low-power consumption for the entire system. This paper deals with innovative WATS modeling techniques, and illustrates their impact on the case of autonomous wireless ElectroCardioGram monitoring. The results show the effectiveness of our power optimization approach for improving the WATS autonomy.