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Wireless sensor networks are increasingly being used for continuous monitoring of patients with chronic health conditions such as diabetes and heart problems. As biomedical sensor nodes become more wearable, their battery sizes diminish, necessitating very careful energy management. This paper proposes feedback-based closed-loop algorithms for dynamically adjusting radio transmit power in body-worn devices, and evaluates their performance in terms of energy savings and reliability as the data periodicity and feedback time-scales vary. Using experimental trace data from body worn devices, we first show that the performance of dynamic power control is adversely affected at long data periods. Next for a given data period we show that modifying the transmit power at too long timescales (around a minute) reduces the efficacy of dynamic power control, while too short a time-scale (few seconds or less) incurs a high feedback signaling overhead. We therefore advocate an intermediate range of time-scales (when permitted by the data periodicity), typically in the few tens of seconds, at which the control algorithms should adapt transmit power in order to achieve maximal energy savings in body-worn sensor devices used for medical monitoring.