Neuromorphic computing holds the promise of transforming traditional computing methods by mimicking the functionalities of biological neural circuits. The slow dynamics of neurons and synapses in biological systems enable real-time information processing in cooperation with the environment, a feature lacking in digital circuits. To address this gap and incorporate bio-inspired characteristics into electronic circuits, researchers are exploring scalable electronic devices that operate on the same time scale as the surrounding environment. Ion transport in solid-state devices, particularly using protons, emerges as a promising avenue due to high mobility and compatibility with complementary metal–oxide–semiconductor (CMOS) technology. The study focuses on two-terminal protonic devices, a relatively rare configuration, to achieve long-timescale and volatile resistance change. By leveraging the vertical proton dynamics in the Pt/WO3/Pd structure, the devices exhibit resistance change phenomena with a time constant of seconds to minutes. This unique design allows for efficient real-time information processing, demonstrated through the real-time prediction of blood glucose levels. The structural characteristics of the device, along with the role of hydrogen spillover in catalyzing H2 molecules, contribute to the successful modulation of electronic conductance. Overall, the study paves the way for utilizing protonic devices in neuromorphic computing for enhanced controllability and scalability, offering a new paradigm for information processing.