This study determined the feasibility and performance of center of mass (COM) acceleration feedback control of a neuroprosthesis utilizing functional neuromuscular stimulation (FNS) to restore standing balance to a single subject paralyzed by a motor and sensory complete, thoracic-level spinal cord injury. An artificial neural network (ANN) was created to map gain-modulated changes in total body COM acceleration estimated from body-mounted sensors to optimal changes in stimulation required to maintain standing. Feedback gains were systematically tuned to minimize the upper-limb (UL) loads applied by the subject to an instrumented support device during internally generated postural perturbations produced by volitional reaching and object manipulation. Total body COM acceleration was accurately estimated (>90% variance explained) from 2 three-dimensional (3-D) accelerometers mounted on the pelvis and torso. Compared with constant muscle stimulation employed clinically, COM acceleration feedback control of stimulation improved standing performance by reducing the UL loading required to resist internal postural disturbances by 27%. This case study suggests that COM acceleration feedback could potentially be advantageous in a standing neuroprosthesis since it can be implemented with only a few feedback parameters and requires minimal instrumentation for comprehensive 3-D control of dynamic standing function.