Cuff less Blood Pressure Estimation Algorithms for Continuous Health care Monitoring

Data availability

The complete dataset supporting the findings of this study is available via the PhysioNet data repository at https://doi.org/10.13026/qcc8-n557. The associated preprocessed raw data are available and can be shared with interested parties upon reasonable request. Source data are provided with this paper.

Code availability

The machine learning algorithm is publicly available via GitHub at https://github.com/TAMU-ESP/Graphene_BP. The custom codes used for data visualization are available from the corresponding authors upon request.

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Acknowledgements

The work was supported in part by the Office of Naval Research under grant number N00014-18-1-2706, the Temple Foundation Endowed Professorship, the National Science Foundation under grant number 1738293 and the National Institute of Health under grant number 1R01EB028106. R.J. acknowledges useful discussions with the former founding director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) at the NIH, R. I. Pettigrew. We acknowledge J. Wozniak at the Texas Advanced Computing Center (TACC) at The University of Texas at Austin (http://www.tacc.utexas.edu) for creating Fig. 1a. The authors have permission to use and publish the image.

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Contributions

D.K., K.S., R.J. and D.A. conceived the idea of using GET and designed the experiments. B.I. and R.J. designed the instrumentation for bioimpedance acquisition. D.K. fabricated and characterized the GETs. K.S. and B.I. optimized the XL-board. D.K., K.S., B.I. and N.K. performed the BP experiments. B.I. and A.A. developed and utilized the machine learning algorithm. D.K. and K.S. compiled and analysed the data. The manuscript was written with the contributions of all authors. All authors have approved the final version of the manuscript.

Corresponding authors

Correspondence to Roozbeh Jafari or Deji Akinwande.

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Competing interests

R.J. and B.I. filed a patent (US 2020/0138303 titled 'System and method for cuff-less blood pressure monitoring') related to this research; this patent is licensed to SpectroBeat LLC.

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Nature Nanotechnology thanks Yingying Zhang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Kireev, D., Sel, K., Ibrahim, B. et al. Continuous cuffless monitoring of arterial blood pressure via graphene bioimpedance tattoos. Nat. Nanotechnol. 17, 864–870 (2022). https://doi.org/10.1038/s41565-022-01145-w

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