Design of Embedded EMD and its Real-Time Implementation for Biomedical Signal Processing

• Main Authors: Yi-Hsuan Lin, 林義軒
• Other Authors: Ching-Wei Yeh
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/39312293399077642268

碩士 === 國立中正大學 === 電機工程研究所 === 100 === Empirical mode decomposition (EMD) has outstanding performance in non-linear and non-stationary signal analysis. But it is not widely adopted in embedded and real-time signal processing applications due to its high complexities. This thesis proposes an embedded EMD design, which has been integrated into an embedded real-time ECG de-noising system successfully. First, an embedded optimization framework has been constructed, where “the decomposition of synthetic dual-tone signals” and “the noise removal capability of ECG” have been proposed to quantitatively evaluate the various design parameters in EMD and optimization schemes. A compact test signal has also been presented to improve the design space exploration time. Then, a hybrid decomposition scheme with DWT-like filtering and a multirate EMD algorithm have been proposed to significantly reduce the computational complexities. The former effectively decreases the required number of siftings in EMD, while mitigating mode mixing effects. The latter exploits the incremental bandwidth reductions during EMD to dynamically down-sample the signal for dramatic savings in storage and computations. Finally, segmented cubic spline computation has been proposed to reduce the buffer size in embedded hardware realizations. All design techniques have been implemented and verified using FPGA and a real-time ECG de-noising system has been demonstrated. Compared with the original EMD algorithm, 30% computations and 59.7% memory space have been saved with our proposed design techniques.