Efficient implementation of real-time ECG derived respiration system using cubic spline interpolation

Monitoring the respiratory signal is crucial in many medical applications. Traditional methods for the respiration measurement are normally based on measuring the volume of air inhaled and exhaled by lungs (like spirometer) or oxygen saturation in blood. However, these methods have numerous challenges including their high cost and not being accessible in some cases. In this paper, an algorithm for deriving the respiratory signal from ECG signal is proposed, which is based on other proposed algotithms. This algorithm uses the cubic spline interpolation (CSI) of R-waves in ECG to derive the respiratory signal. The CSI algorithm is made efficient with respect to ECG features in order to reduce the latency and the complexity of calculations. In addition, a hardware architecture for real-time and low-power processing is implemented. This architecture is synthesized using 180nm process and consumes 817μW. The FPGA tests are also performed on Xilinx Virtex-6 platform.