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Piezoelectric Pulse Diagnosis Transducer of 9x9 Sensing Arrays and Pulse Signal Processing

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Applied Informatics and Communication (ICAIC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 226))

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Abstract

Purpose: To propose the fabrication of pulse transducers of a 9x9 sensing array, and the strategies for collecting pulse patterns and studying these patterns with Fourier analysis. There will be 9 sensing probes on each location to attain pulse information from 27 locations of entire pulse holography.

Methodology: Our pulse transducers will be composed of 9 sensing probes in 1.5×1.5mm², which are integrated according to the array utilized in pulse diagnosis in Traditional Chinese Medicine (TCM). These probes will be separated by 0.1mm in rows and 0.3mm in columns, and therefore, the fabrication of the proposed transducers will be mainly based on microfabrication techniques. The piezoelectric material will be soft PVDF (Polyvinylidene Fluoride), which will be processed into sensor arrays using a PDMS (Polydimethylsiloxane) mold. All pulse information will be digitized and saved into a computer. MATLAB programs will be created to analyze the 243 signals that are output from the three partitions (Cun, Guan and Chi) of pulse holography with mathematical methods, such as Fourier analysis and transformations of matrix.

Conclusion: We expect the following research outcomes by the end of this project: (1) Design of the transducer; (2) Fabrication of the transducer; (3) Test of the transducer; (4) Composition of MATLAB programs; (5) Acquisition and analysis of pulse patterns in large numbers; (6) Establishment of a database for pulse patterns. Standardization and normalization of pulse patterns will be realized. As a result, our project will be helpful to manage the variations of pulses, and will provide an efficient approach for non-invasive and early diagnosis.

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References

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Chang, H., Chen, JX. (2011). Piezoelectric Pulse Diagnosis Transducer of 9x9 Sensing Arrays and Pulse Signal Processing. In: Zhang, J. (eds) Applied Informatics and Communication. ICAIC 2011. Communications in Computer and Information Science, vol 226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23235-0_69

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  • DOI: https://doi.org/10.1007/978-3-642-23235-0_69

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23234-3

  • Online ISBN: 978-3-642-23235-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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