Browsing by Author "Li, Arvin Huang-Te"

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An Advanced Hardware Design Based on Ensemble Empirical Mode Decomposition Algorithm for Heart Sound Signal Processing
(2013)
Chou, Chia-Ching
;
Lin, Kuen-Chih
;
Fang, Wai-Chi
;
Li, Arvin Huang-Te
;
Chang, Yu-Ching
In this study, an advanced hardware design for heart sound signal processing based on ensemble empirical mode decomposition (EEMD) is developed and implemented. The EEMD method [1] is developed to alleviate a key drawback in the original empirical mode decomposition (EMD) algorithm. In a previous research, Huang et al. [2] developed an adaptive and efficient EMD method for nonlinear and nonstationary signal analysis. The physical meaning of a single intrinsic mode function (IMF) is obscure, and the original EMD algorithm cannot separate signals with different scales into appropriate IMFs. To overcome this major drawback, a noise-assisted data analysis (NADA) method called EEMD is developed. Heart sound signals are fed into the proposed system to simulate the EEMD-fixed-point performance. A comparison of the floating-point and fixed-point results exhibits satisfactory consistency and demonstrates that our design can accommodate wide variations of dynamic ranges and complicated calculations.
An Efficient and Accurate Empirical Mode Decomposition of the Technical Design and Methods for Biological Sound
(2012)
Fang, Wai-Chi
;
Chou, Chia-Ching
;
Hung, Tzu-Hsun
;
Lin, Kuen-Chih
;
Li, Arvin Huang-Te
An EMD-based algorithm for bio-sound signal processing was proposed and implemented on VEX330 Xilinx FPGA. A free-format fixed point library was development to deal with overflow and underflow problems. Downsampled phonocardiogram signals were fed into our EMD-processor. Comparison of floating point and fixed point results exhibited satisfactory consistency and demonstrated that our novel fixed point library are able to accommodate with wild variations of dynamic ranges.
Time-Frequency Analysis of Heart Sound Signals Based on Hilbert-Huang Transformation
(2012)
Hung, Tzu-Hsun
;
Chou, Chia-Ching
;
Fang, Wai-Chi
;
Li, Arvin Huang-Te
;
Chang, Yu-Ching
In this study, a method based on Hilbert-Huang Transformation (HHT) for time-frequency analysis of heart sound signals is presented. HHT is employed because most biomedical signals such as Electroencephalogram (EEG), Electrocardiogram (ECG) and heart sound signals are non-stationary signals. Heart sound signals recordings are often contaminated with the spike noise caused by the front-end circuits or measurement instruments in the real situations. A digital median filter is firstly employed to remove the spike noise of the heart sound signals. Then, the time series data are decomposed into several IMFs (Intrinsic Mode Function) using Empirical Mode Decomposition (EMD) algorithm. Hilbert transformation algorithm is utilized to acquire the instantaneous frequency for every IMF. Simulation results show that time-frequency domain analysis of heart sounds signals based on HHT algorithm is able to offer higher frequency resolution.