Design and Realization of Signal Processing Platform of Multi-Parameter Wearable Medical Devices

Xin Tan, Binfeng Xu, Qiancheng Liu

Guangdong Food and Drug Vocational College, Guangzhou, China.
Guangdong Food and Drug Vocational College, Guangzhou, China..

DOI: 10.4236/jsip.2013.42012                

Abstract

This paper presents a design of new type of multi-parameter wearable medical devices signal processing platform. The signal processing algorithm has a QRS-wave detection algorithm based on LADT, wavelet transformation and threshold detection with TMS320VC5509 DSP system. The DSP can greatly increase the speed of QRS-wave detection, and the results can be practical used for multi-parameter wearable device detection of abnormal ECG.

Keywords

Multi-Parameter Wearable Medical Devices; DSP; LADT; Wavelet Transform; ECG Detection Algorithm

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	S.-D. Bao and Y.-T. Zhang, “Telemedicine: Wearable Biomedical Devices,” China Medical Device Information, Vol. 10, No. 5, 2004, pp. 1-3.
[2]	S. M. S. Jalaleddine, C. G. Hutchens and R. D. Strattan, “ECG Compress Techniques,” IEEE Transaction on Biomedical Engineering, Vol. 37, 1990, pp. 232-243.
[3]	Q. I. Jin and M. O. Zhiwen, “On the Zero Equivalent Condition of Roughness of Knowledge in Rough Set Theory,” Chinese Journal of Engineering Mathematics, Vol. 18, No. 3, 2001, pp. 139-142.
[4]	L. Gang, Y. Wenyu and L. Ling. “An Artificial-Intelligence Approach to ECG Analysis,” Engineering in Medicine and Biology Magazine, IEEE, Vol. 19, No. 2, 2000, pp. 95-100. doi:10.1109/51.827412
[5]	D. Hu and Z. W. Mo, “Rough-Fuzzy Neural Network and Its Application,” Pattern Recognition and Artificial Intelligence, Vol. 14, No. 3, 2001, pp. 327-331.
[6]	L. Gang, F. Jing and L. Ling, “Fast Realization of the LADT ECG Data Compression Method,” Engineering in Medicine and Biology Magazine, IEEE, Vol. 13, No. 2, 1994, pp. 255-258. doi:10.1109/51.281685
[7]	J. K. Udupa and I. S. N. Murthy, “Syntactic Approach to ECG Rhythm Analysis,” IEEE Transactions on Biomedical Engineering, Vol. 37, No. 7, 1980, pp. 370-375.
[8]	P. S. Hamilton, “Compression of the Ambulatory ECG by Average Beat Subtraction and Residual Differencing,” IEEE Transaction on Biomedical Engineering, Vol. 38, No. 3, 1991, pp. 253-259.
[9]	Y. Zhang and T.-Q. Chen, “Hardware Programming Language: TMS320C5000 Family of DSP-Based,” Xidian University Press, Xi’an, 2003.
[10]	G. Li, J. Feng, L. Lin, et al. “Fast Realization of the LADT ECG Data Compression Method,” IEEE Engineering in Medicine and Biology Magazine, Vol. 13, No. 2, 1994, pp. 255-258. doi:10.1109/51.281685
[11]	G. Li, W. Y. Ye and F. He, “A New Algorithm for ECG Analysis Based On LADT-BP Neural Network,” Chinese Journal of Biomedical Engineering, Vol. 20, No. 2, 2001, pp. 127-131.
[12]	C.-H. Hu, J.-B. Zhang and J. Xia, “System Analysis and Design Based on MATLAB (Wavelet Analysis),” Xidian University Press, Xi’an, 1999.
[13]	Fei-Si Technology R & D Center, “Wavelet Analysis Theory and MATLAB7 Implementation,” Publishing House of Electronics Industry, Beijing, 2006.
[14]	R. T. Edwards and G. Cauwenberghs, “A VLSI Implementation of the Continuous Wavelet Transform,” IEEE International Symposium on Circuits and Systems, 12-15 May 1996, pp. 368-371.
[15]	“TMS320VC5509 Fixed-Point Digital Signal Processor,” Texas Instruments Incorporated, 2001.