Neuromorphic Computing in Human-System Interaction: A Scoping Review of Recent Developments, Key Challenges, and Future Research Opportunities

This review examines recent advances in neuromorphic computing for human-system interaction (HSI). Inspired by the nervous system, neuromorphic computing utilizes spiking neural network models, event-driven processing, and biomimetic hardware to enable ultra-low power computing. The review analyzes 35 scientific papers published up to May 2026, classifying applications into five categories: brain-computer interface and healthcare applications, human-robot collaboration, neuromorphic synapse and hardware, affective computing and emotion recognition, and neuromorphic sensors and human-machine interfaces. Compared to conventional computing techniques, neuromorphic computing exhibits low-power consumption and faster processing. Recent advancements in neuromorphic computers include the development of memristors, flexible synaptic devices, and self-powered sensory systems. However, challenges such as standardization of datasets, system scalability, hardware-software integration, system explainability, data security, and data privacy can be recognized as the future research topics of neuromorphic computing for HSI. Overall, neuromorphic computing provides a potential HSI solution for a safer, more intelligent, and more human-centered future.