Delay-based reservoir computing is a novel computational framework with only single nonlinear node. This feature makes it a strong candidate for the hardware implementation of the analogue cognitive system. Such system can be exploited to improve the energy efficiency of data processing in bioelectronics. This paper presents a system modelling of this network that is capable of cognitively processing Electrocardiograph (ECG) signal. The proposed single-input single-output model receives encoded ECG signal while the output amplitude indicates the diagnostic result. The information processor is an analogue circuit with the dynamic properties of Mackey-Glass nonlinearity and fading memory. To validate this system and mimic real-time operation, the experiment is designed and implemented to detect ventricular ectopic beat, an ectopic heartbeat type, in a continuous ECG signal. After training with the available ECG data, the model successfully locates ventricular ectopic beat with 87.51% sensitivity for the testing dataset.