论文信息 - Hardware implementation of MFCC feature extraction for respiratory sounds analysis

Hardware implementation of MFCC feature extraction for respiratory sounds analysis

In this paper, an acoustic feature extraction method based on mel frequency cepstral coefficients (MFCC) was implemented on FPGA for real-time respiratory sound analysis. The proposed technique was implemented using Xilinx System Generator (XSG) in MATLAB/SIMULINK environment. The feature vectors obtained with fixed-point XSG implementation is compared to those obtained with on the floating-point MATLAB one using normal and wheezing respiratory sounds.

Mohammed Bahoura | Hassan Ezzaidi | H. Ezzaidi | M. Bahoura

[1] Amjad HASHEMI,et al. Classification of Wheeze Sounds Using Cepstral Analysis and Neural Networks , 2012, MMVR.

[2] Gwo-Ching Chang. FPGA realization of an automatic wheeze detector based on wavelet filter bank , 2009, 2009 IEEE 13th International Symposium on Consumer Electronics.

[3] M. Bahoura,et al. Respiratory sounds classification using cepstral analysis and Gaussian mixture models , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4] Gwo-Ching Chang,et al. Performance evaluation and enhancement of lung sound recognition system in two real noisy environments , 2010, Comput. Methods Programs Biomed..

[5] Mohammed Bahoura,et al. Pattern recognition methods applied to respiratory sounds classification into normal and wheeze classes , 2009, Comput. Biol. Medicine.

[6] Youngmoo E. Kim,et al. Efficient Acoustic Feature Extraction for Music Information Retrieval Using Programmable Gate Arrays , 2009, ISMIR.