<p>Neuromorphic systems are crucial for the development of intelligent human–machine interfaces. Memristive hardware can emulate the neuron dynamics of biological systems, but typically uses rate coding, whereas single-spike coding (in which information is expressed by the firing time of a sole spike per neuron and the relative firing times between neurons) is faster and more energy efficient. Here we report a robust memristive hardware system that uses single-spike coding. For input encoding and neural processing, we use uniform vanadium oxide memristors to create a single-spiking circuit with under 1% coding variability. For synaptic computations, we develop a conductance consolidation strategy and mapping scheme to limit conductance drift due to relaxation in a hafnium oxide/tantalum oxide memristor chip, achieving relaxed conductance states with standard deviations within 1.2 μS. We also develop an incremental step and width pulse programming strategy to prevent resource wastage. The combined end-to-end hardware single-spike-coded system exhibits an accuracy degradation under 1.5% relative to a software baseline. We show that this approach can be used for real-time vehicle control from surface electromyography. Simulations show that our system consumes around 38 times lower energy with around 6.4 times lower latency than a conventional rate coding system.</p>