Active regulation systems in biomedical settings demand an adaptive, reliable, and efficient control strategy under dynamic and uncertain circumstances. This paper presents a process control biomimetic strategy for biomedical regulation that takes inspiration from the octopuses decentralized, adaptive neural control system. With a distributed sensing operation, decision making is performed locally, actuating proportionally-a quite robust biological paradigm for real-time control with minimal centralized computation. In the proposed approach, the biomedical sensors measure the parameter and produce feedback signals similar to the function of sensory neurons in the octopus arm system. The proportional controller is used in imitating the adaptive response in the octopus neural control system, which reacts to error in proportion to its magnitude from the desired state. The biomedical process is described as a first-order system that can allow for transparent analysis and implementation. The controller’s corrective action is based on the actuator, and there is a closed-loop feedback control system that maintains stability. Performance evaluation is carried out by analyzing time-domain parameters such as rise time, settling time, and steady-state error for variable controller gains. The results reveal enhanced accuracy of regulation and rapid response compared to open-loop operation. This octopus-inspired control strategy represents one of the low-cost, robust, and easy applications of biomedical uses for regulating physiological parameters and automated therapeutic systems.