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A Piezoelectric Heart Sound Sensor for Wearable Healthcare Monitoring Devices

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Abstract

Heart disease is the leading cause of death all around the world. And heart sound monitoring is a commonly used diagnostic method. This method can obtain vital physiological and pathological evidence about health. Many existing techniques are not suitable for long-term dynamic heart sound monitoring since their large size, high-cost and uncomfortable to wear. This paper proposes a small, low-cost and wearable piezoelectric heart sound sensor, which is suitable for long-term dynamic monitoring and provides technical support for preliminary diagnosis of heart disease. First, the theoretical analysis and finite element method (FEM) simulation have been carried out to determine the optimum structure size of piezoelectric sensor. Subsequently, the sensor is embedded into the fabric-based chest strap to verify the detection performance in wearable scenarios. An existing piezoelectric sensor (TSD108) is used as reference. The designed sensor can acquire complete heart sound signals, and its signal-to-noise ratio is 2 dB higher than that of TSD108.

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Acknowledgements

This work is supported by National Key Research & Development Plan of China (NO. 2016YFB1001401) and National Natural Science Foundation of China (NO. 61572110).

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Correspondence to Dongyi Chen .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Chen, Z., Chen, D., Xue, L., Chen, L. (2019). A Piezoelectric Heart Sound Sensor for Wearable Healthcare Monitoring Devices. In: Mucchi, L., Hämäläinen, M., Jayousi, S., Morosi, S. (eds) Body Area Networks: Smart IoT and Big Data for Intelligent Health Management. BODYNETS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-030-34833-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-34833-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34832-8

  • Online ISBN: 978-3-030-34833-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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