Structural control of civil infrastructure in response to large external loads, such as earthquake or wind, is still not widely employed due to several key issues, such as latency in the system and challenges with information exchange. To promote information flow, wireless sensor networks have emerged as a potential solution that is also a low-cost alternative to the traditional wired sensing and actuation infrastructure. However, these systems also introduce additional challenges such as latency in the wireless communication channel and computational inundation at individual sensing nodes. Inspiration can be drawn from the real-time sensing and actuation capabilities of the biological central nervous system to overcome some of these challenges experienced by wireless sensor nodes. A novel bio-inspired wireless sensor node was developed that is capable of real-time time-frequency decomposition of a sensor signal, thus drawing inspiration from the frequency selectivity of certain neurons. Similar to the functionality of neurons, the node uses asynchronous sampling based on the content of the perceived signal, resulting in large power savings and compressed data communication. In this study, the bio-inspired wireless sensor node is utilized for a feedback control application in order to overcome the challenges currently seen in wireless control. The sensor node is able to transmit frequency- specific data in real-time to a controller node which constructs a control force using minimal computational resources. This study validates that performance of the bio-inspired wireless feedback control architecture on a one-story partial- scale shear structure that is seismically excited and controlled via active mass actuators.