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Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch

Nature Biomedical Engineering volume 4, pages 148–158 (2020)Cite this article

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Abstract

Skin-mounted soft electronics that incorporate high-bandwidth triaxial accelerometers can capture broad classes of physiologically relevant information, including mechano-acoustic signatures of underlying body processes (such as those measured by a stethoscope) and precision kinematics of core-body motions. Here, we describe a wireless device designed to be conformally placed on the suprasternal notch for the continuous measurement of mechano-acoustic signals, from subtle vibrations of the skin at accelerations of around 10−3 m s−2 to large motions of the entire body at about 10 m s−2, and at frequencies up to around 800 Hz. Because the measurements are a complex superposition of signals that arise from locomotion, body orientation, swallowing, respiration, cardiac activity, vocal-fold vibrations and other sources, we exploited frequency-domain analysis and machine learning to obtain—from human subjects during natural daily activities and exercise—real-time recordings of heart rate, respiration rate, energy intensity and other essential vital signs, as well as talking time and cadence, swallow counts and patterns, and other unconventional biomarkers. We also used the device in sleep laboratories and validated the measurements using polysomnography.

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Fig. 1: A wireless, skin-interfaced MA measurement technology designed for mounting on the SN.
Fig. 2: Representative MA data in the form of accelerations measured along three orthogonal axes from the MA device mounted on the SN of a healthy subject.
Fig. 3: Flow diagram of signal processing and corresponding results from representative MA data acquired from healthy subjects.
Fig. 4: Results from MA data recorded at the SN in field studies with comparisons to reference measurements.
Fig. 5: Application of MA sensing from the SN in clinical sleep studies.
Fig. 6: Insights into sleep patterns determined by MA sensing from the SN.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated for the studies in Figs. 2–6 are available for research purposes from the corresponding authors upon reasonable request.

Code availability

The codes used for the embedded system and data collection are available on GitHub at https://github.com/johnrogersgroup/Wireless_MA. The analysis codes used in this study are available from the authors upon request.

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Acknowledgements

The materials and device-engineering aspects of the research were supported by the Material Science and Engineering Department and Center for Bio-Integrated Electronics at Northwestern University. K.L. acknowledges support from the Samsung Scholarship. K.L. acknowledges the help from A. Sahakian on radio frequency communication and antenna tuning. Z.X. acknowledges support from the National Natural Science Foundation of China (grant no.11402134). S.X. and J.A.R. recognizes support from the National Institute on Aging of the National Institutes of Health under R41AG062023 and R43AG060812. R.A. acknowledges support from National Science Foundation (NSF) Graduate Research Fellowship under grant no. 1842165 and the Ford Foundation Predoctoral Fellowship. Y.H. acknowledges support from the NSF (CMMI1635443). S.M. is grateful to Indo-U.S. Science and Technology Forum (SERB-IUSSTF) for her SERB Indo-U.S. Postdoctoral Award. X.N. thanks D. Lu for helpful discussions. K.L. thanks the Dion family for volunteering for the data collection.

Author information

Author notes

  1. These authors contributed equally: KunHyuck Lee, Xiaoyue Ni, Jong Yoon Lee.

Authors and Affiliations

  1. Simpson Querry Institute, Northwestern University, Chicago, IL, USA

    KunHyuck Lee, Hany Arafa, Shuai Xu, Masahiro Irie, Ha Uk Chung, Claire Liu, Ivy Huang & John A. Rogers

  2. Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA

    KunHyuck Lee, Raudel Avila, Jonathan T. Reeder, Ivy Huang, Yujun Deng, Zhaoqian Xie, Yonggang Huang & John A. Rogers

  3. Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA

    Xiaoyue Ni, Jong Yoon Lee, Shuai Xu, Raudel Avila, Joo Hee Lee, Hokyung Jang, Jungwoo Kim, Sunita Mehta, Jonathan T. Reeder, Yujun Deng, Zhaoqian Xie, Yonggang Huang & John A. Rogers

  4. Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA

    Hany Arafa, Omolara O. Olabisi, Esther Chung, Marc Hill, Claire Liu & John A. Rogers

  5. Department of Chemistry, Northwestern University, Evanston, IL, USA

    David J. Pe & John A. Rogers

  6. Department of Dermatology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Shuai Xu

  7. Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL, USA

    Raudel Avila, Yujun Deng, Zhaoqian Xie & Yonggang Huang

  8. Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA

    Raudel Avila, Selam Getaneh, Yujun Deng, Zhaoqian Xie, Yonggang Huang & John A. Rogers

  9. Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA

    Masahiro Irie, Ha Uk Chung & John A. Rogers

  10. Department of Molecular Biosciences, Northwestern University, Evanston, IL, USA

    Ryder L. Easterlin

  11. Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Dong Hyun Kim

  12. Department of Economics, Northwestern University, Evanston, IL, USA

    Jeremy Bell

  13. Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Jun Bin Park

  14. Department of Materials Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA

    Sung Bong Kim

  15. Department of Mechanical Engineering, Texas A&M University, College Station, TX, USA

    Matt Pharr

  16. Medical Scientist Training Program, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA

    Andreas Tzavelis

  17. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China

    Yujun Deng

  18. State Key Laboratory of Structural Analysis for Industrial Equipment, Department of Engineering Mechanics, Dalian University of Technology, Dalian, China

    Zhaoqian Xie

  19. Carle Neuroscience Institute, Carle Physician Group, Urbana, IL, USA

    Charles R. Davies

  20. Department of Neurological Surgery, Northwestern University, Evanston, IL, USA

    John A. Rogers

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  1. KunHyuck Lee
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Contributions

K.L., Z.X. and J.A.R. performed the structural design of the system. Z.X., R.A., Y.D. and Y.H. performed mechanical and electromagnetic modelling and theoretical studies. K.L., J.Y.L., J.H.L., J.B.P. and J.K. developed the embedded system and the user interface. K.L., X.N. and J.A.R. designed and performed the experimental studies on the technology. X.N., K.L. and J.A.R. designed and performed the human subject studies. X.N., K.L., M.I., R.L.E., D.J.P. and D.H.K developed the signal-processing algorithms and performed the data analysis. K.L., H.A., D.J.P., H.U.C., O.O.O., S.G., E.C., M.H., J.B., H.J., C.L., S.B.K., S.M., J.T.R and I.H. manufactured the devices. S.X., A.T. and C.R.D. provided clinical advice. X.N. and J.A.R. wrote the signal processing algorithm part of the manuscript. K.L., X.N., Z.X., Y.H. and J.A.R. contributed to the other sections.

Corresponding authors

Correspondence to Zhaoqian Xie, Charles R. Davies, Yonggang Huang or John A. Rogers.

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Lee, K., Ni, X., Lee, J.Y. et al. Mechano-acoustic sensing of physiological processes and body motions via a soft wireless device placed at the suprasternal notch. Nat Biomed Eng 4, 148–158 (2020). https://doi.org/10.1038/s41551-019-0480-6

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