The accurate detection and analysis of the P-QRS-T complex in electrocardiogram (ECG) signals are crucial for diagnosing cardiac diseases. This paper presents a practical approach to ECG signal processing by integrating multiple filter fusion techniques to enhance detection accuracy. Recognizing the specific challenges at sea, including motion-induced noise and electromagnetic interference, the study examines the performance of low-pass, high-pass, and Chebyshev Type II filters in improving ECG signal quality. Using a dataset generated by a Dynamic Model for Synthetic ECG Signal Generation, the analysis evaluates the effectiveness of these filters under various noise conditions, such as baseline drift, electrode contact noise, and muscle noise. The proposed method combines filtered outputs from multiple channels: P and T waves are extracted using low-pass and high-pass filters, while the QRS complex is identified through the Chebyshev Type II filter. Results indicate improved detection accuracy, with performance varying based on the type of noise present. While not introducing a novel algorithm, the study demonstrates that the fusion of established filtering techniques offers a fast and reliable solution suitable for maritime health monitoring systems. However, these results are derived from simulated signals under controlled experimental settings and therefore reflect proof-of-concept performance rather than clinical validation.