Transmission power control in energy-constrained mobile wireless sensor nodes is a necessary means to extend the battery lifetime and reduce the overall operational expenditure. The body-wearable sensors are perhaps the best examples when they are used for tracking and monitoring health of individuals and to carry out data analysis for possible symptoms of any disease. In indoor environments, the challenge is increased manifold due to complex multi-path propagation and temporal variation of link quality. This paper has enhanced our previous work on the state based adaptive power control protocol (SAPC) to suit well in indoor dynamic radio environments. The proposed protocol adjusts the state-transition rate R (drop-off rate) from a higher to a lower state, depending on the radio link quality. This improvement is implemented in SAPC protocol and renamed as SAPC-R. This protocol is compared with an existing practical adaptive power control protocol (P-ATPC) that can track variations in the radio link quality, and select an appropriate transmission power level and the number of retransmissions. The aim is to keep the algorithm computationally simple as it will run on battery powered devices and therefore are energy-constrained. Simulation results show that SAPC-R can save at least 25% energy as compared to P-ATPC. Results from the experiments that were conducted inside a University building show that by using the SAPC-R algorithm, energy consumption per successful transmission can be reduced by at least 15% as compared to P-ATPC while the packet success rates are comparable. This is a significant improvement, given the small changes in current consumption corresponding to the large changes in transmission power in present-day low power wireless transmitters.