FPGA Based Real-Time Implementation of Online EMD With Fixed Point Architecture

Abstract

Empirical mode decomposition (EMD) is a data driven method for nonstationary data analysis which has proven to be extremely useful in diverse applications in biomedical engineering. In its original formulation, the EMD method works collectively on a batch of data and hence is not suitable for online applications that demand continuous data processing capability in real-time. To cater for such applications, few complete field-programmable gate array (FPGA) based designs for EMD computations have emerged in recent years, yet they have found limited practical applications. The main reason could be that existing complete FPGA based architectures invariably work on integer data sets thus ignoring the sensitivity EMD to truncation errors. Moreover, these architectures mostly implement simplistic linear interpolation technique for sifting process within EMD, thereby compromising its accuracy. To that end, we develop a complete FPGA-based architecture for EMD which works on fixed point data formats thereby alleviating the main source of error in existing EMD based architectures. We also implement well established and accurate cubic spline interpolation technique in addition to giving provision to linear interpolation within the sifting process in EMD, which further improves its accuracy. Our proposed pipeline design ensures that despite implementing computationally expensive EMD related tasks, the proposed architecture exhibits lowest execution time among all existing EMD architectures. We provide examples of computation of EMD decomposition through proposed architecture for both synthetic and real world biomedical signals to demonstrate the prowess of our work.INDEX TERMS Empirical mode decomposition, FPGA, time frequency analysis.

Field‐programmable gate array‐based design for real‐time computation of ensemble empirical mode decomposition

“…From Tables 1 and 2, it is observed that the correlation values obtained are near to unity and RMSE values are smaller than the amplitude of x(t) which proves the effectiveness of the proposed designs. Comparing with the design proposed by Gul et al, 18 we can say that the average RMSE value of our proposed EMD design is higher than the mentioned design (Table 3). But our proposed EEMD design has the least average RMSE value.…”

“…Many FPGA-based designs were proposed for EMD, 15,[17][18][19][20] whereas in Chen et al, 22 a semi FPGA-based design for EEMD was proposed. In Table 7, we have presented the comparison of our design with existing designs in respect of FPGA used, envelope computation, clock rate, sampling frequency, and execution time.…”

“…The sampling frequency is higher than the sampling frequency of the some existing state-of-the-art designs. 15,17,18,20,22 In our EMD and EEMD designs, pipeline architecture is used, which reduces the execution time of the designs. In the design proposed in Chen et al, 17 EMD implementation with CSI used batch processing, basically an offline processing-based design and has more execution time.…”

“…In Gul et al, 18 an FPGA-based design for EMD was proposed; in this design, the authors have used linear interpolation (LI) and CSI for the envelope computation. Their proposed designed was operated at a clock rate and sampling frequency of 46.44 MHz.…”

Research on NMR Noise Reduction Method Based on Improved CEEMD

“…In recent years, Huang proposed a new time-frequency analysis method --empirical mode decomposition (EMD). These methods have been widely used in signal noise reduction in various fields [6][7][8][9]. EMD is an adaptive decomposition method.…”