Extraction of heartbeat signal from CW vital sign radar using cubic spline interpolation function and adaptive bandpass filter

With the increasing demand for health monitoring and biometric identification technologies, radar-based heartbeat signal extraction techniques have been widely applied and deeply researched. This article proposes a time-domain method for heartbeat signal extraction, employing a cubic spline-based heartbeat enhancement algorithm combined with an adaptive bandpass filter. The proposed method offers significant advantages, including a simplified computational process and reduced time delay compared to conventional signal decomposition techniques, making it highly suitable for real-time applications. Additionally, it provides higher confidence and better interpretability than signal extraction methods based on neural networks. To achieve this, the method enhances the heartbeat signal of the continuous-wave (CW) radar output signal using cubic spline curve interpolation. The heartbeat signal is subsequently extracted by dynamically adjusting the frequency range of a bandpass filter. The method is implemented on a 2.4 GHz CW radar system based on a phase discriminator, which features a simpler structure and higher accuracy compared to traditional quadrature receivers. Experimental results in multiple subjects validate the effectiveness of the proposed approach, demonstrating an average heartbeat count accuracy of up to 98.06% in the time domain compared to the reference signal collected by the wearable sensor. Furthermore, the method achieves a computational complexity of O(N), highlighting its efficiency and potential for practical deployment.