Wearable inertial sensors represent an opportunity to enable gait monitoring and feedback-based rehabilitation in real-world environments. Here, we describe the development of an inexpensive I MU-based wireless body area network capable of recording 9-axis motion data from 8 sites on the body simultaneously. This system can generate data comparable to existing commercial sensor networks and can distinguish varying loading conditions observed during real-time biofeedback-based human subject testing.