A Dynamic Difficulty Adjustment Mechanism Based on Cellular Automata Using Cardiac Signals for Serious Games

Dynamic difficulty adjustment in Serious Games remains challenging because most adaptive approaches respond primarily to performance variables and insufficiently incorporate the player’s psychophysiological state in real time. Prior studies have shown the potential of biofeedback and heart rate variability based adaptation; however, many proposals rely on isolated indicators, limited temporal integration, or mechanisms that do not explicitly stabilize state transitions before modifying gameplay. In response, this article proposes a dynamic difficulty adjustment mechanism based on cardiac signals and Cellular Automata for Serious Games. The novelty of the proposal lies in combining individualized instantaneous heart rate ranges, time and frequency domain heart rate variability features, a hybrid multilayer caching for resolving discrepancies between short and longer window estimates, and a Cellular Automaton that introduces temporal inertia before applying adaptive changes to game parameters. Methodologically, the study follows a design and implementation research process in which the mechanism is integrated with a Polar H10 sensor, structured as a modular architecture, and evaluated through functional and architectural, including real time tests of arousal band assignment, adaptive response, and trace level coherence. The engine assigns three classes of operational arousal bands, defining individualized low, target, and high BPM/HRV control regions for DDA actuation. The results demonstrate technically stable operation and effective real time adaptation, with an average response latency of approximately two seconds, supporting the feasibility of the proposed mechanism. Overall, the findings indicate that cardiac signal driven adaptation combined with Cellular Automata based transition control constitutes a technically viable approach for Serious Games.