Challenges and Opportunities in Wearable Biomedical Interfaces

  • Venkata Rajesh Pamula
  • Chris Van Hoof
  • Marian Verhelst
Part of the Analog Circuits and Signal Processing book series (ACSP)


This chapter provides an overview of the challenges and opportunities in wearable biomedical interfaces. Specifically, the challenges involved in acquiring biosignals with high fidelity in limited power budgets are highlighted. This chapter also introduces electrocardiogram (ECG) and photoplethysmogram (PPG) signal acquisition and processing as modalities for estimating the cardiovascular state. Assisted signal processing architectures, specifically analog and algorithmic assisted approaches, are introduced as opportunities to mitigate the challenges in low-power biosignal acquisition platforms. Finally, the organization of the rest of the chapters of the book is presented.


  1. 1.
    “European cardiovascular disease statistics,” 2012 [Online]. Available:
  2. 2.
    A.S. Go, D. Mozaffarian, V.L. Roger, E.J. Benjamin, J.D. Berry, W.B. Borden, D.M. Bravata, S. Dai, E.S. Ford, C.S. Fox et al., Heart disease and stroke statistics-2013 update. Circulation 127(1), e6–e245 (2013)Google Scholar
  3. 3.
    G. Williams, K. Doughty, D. Bradley, A systems approach to achieving CarerNet-an integrated and intelligent telecare system. IEEE Trans. Inf. Technol. Biomed. 2(1), 1–9 (1998)CrossRefGoogle Scholar
  4. 4.
    L.I. Galindez Olascoaga, K. Badami, V.R. Pamula, S. Lauwereins, W. Meert, M. Verhelst, Exploiting system configurability towards dynamic accuracy-power trade-offs in sensor front-ends, in Proceedings of the 50th Asilomar Conference on Signals, Systems, and Computers (IEEE, Piscataway, 2016), pp. 1027–1031Google Scholar
  5. 5.
    H. Kim, S. Kim, N.V. Helleputte, A. Artes, M. Konijnenburg, J. Huisken, C.V. Hoof, R.F. Yazicioglu, A configurable and low-power mixed signal SoC for portable ECG monitoring applications. IEEE Trans. Biomed. Circuits Syst. 8(2), 257–267 (2014)CrossRefGoogle Scholar
  6. 6.
    P. Harpe, H. Gao, R. van Dommele, E. Cantatore, A.H.M. van Roermund, A 0.20 3 nW signal acquisition IC for miniature sensor nodes in 65 nm CMOS. IEEE J. Solid State Circuits 51(1), 240–248 (2016)Google Scholar
  7. 7.
    M. Steyaert, W. Sansen, A micropower low-noise monolithic instrumentation amplifier for medical purposes. IEEE J. Solid State Circuits 22(6), 1163–1168 (1987)CrossRefGoogle Scholar
  8. 8.
    J. Kwong, A.P. Chandrakasan, An energy-efficient biomedical signal processing platform. IEEE J. Solid State Circuits 46(7), 1742–1753 (2011)CrossRefGoogle Scholar
  9. 9.
    A. Ba, M. Vidojkovic, K. Kanda, N.F. Kiyani, M. Lont, X. Huang, X. Wang, C. Zhou, Y.-H. Liu, M. Ding, B. Busze, S. Masui, M. Hamaminato, H. Sato, K. Philips, H. de Groot, A 0.33 nJ/bit IEEE802.15.6/proprietary MICS/ISM wireless transceiver with scalable data rate for medical implantable applications. IEEE J. Biomed. Health Inform. 19(3), 920–929 (2015)CrossRefGoogle Scholar
  10. 10.
    N. Verma, A. Shoeb, J. Bohorquez, J. Dawson, J. Guttag, A.P. Chandrakasan, A micro-power EEG acquisition SoC with integrated feature extraction processor for a chronic seizure detection system. IEEE J. Solid State Circuits 45(4), 804–816 (2010)CrossRefGoogle Scholar
  11. 11.
    H. Kim, R.F. Yazicioglu, T. Torfs, P. Merken, H.-J. Yoo, C.V. Hoof, A low power ECG signal processor for ambulatory arrhythmia monitoring system, in 2010 Symposium on VLSI Circuits (Institute of Electrical and Electronics Engineers (IEEE), Piscataway, 2010)Google Scholar
  12. 12.
    A.Y. Dogan, J. Constantin, M. Ruggiero, A. Burg, D. Atienza, Multi-core architecture design for ultra-low-power wearable health monitoring systems, in 2012 Design, Automation and Test in Europe Conference and Exhibition (DATE) (Mar 2012)Google Scholar
  13. 13.
    J. Webster, Medical Instrumentation: Application and Design (Wiley, Hoboken, 2009)Google Scholar
  14. 14.
    R.F. Yazicioglu, S. Kim, T. Torfs, H. Kim, C. Van Hoof, A 30 μW analog signal processor ASIC for portable biopotential signal monitoring. IEEE J. Solid State Circuits 46(1), 209–223 (2011)CrossRefGoogle Scholar
  15. 15.
    N.V. Thakor, J.G. Webster, W.J. Tompkins, Estimation of QRS complex power spectra for design of a QRS filter. IEEE Trans. Biomed. Eng. BME-31(11), 702–706 (1984)CrossRefGoogle Scholar
  16. 16.
    E.S. Winokur, Single-site, noninvasive, blood pressure measurements at the ear using ballistocardiogram (BCG), and photoplethysmogram (PPG), and a low-power, reflectance-mode PPG SoC, Ph.D. dissertation, Massachusetts Institute of Technology, 2014Google Scholar
  17. 17.
    J. Allen, Photoplethysmography and its application in clinical physiological measurement. Physiol. Meas. 28(3), R1 (2007)CrossRefGoogle Scholar
  18. 18.
    C. Poon, Y. Zhang, Cuff-less and noninvasive measurements of arterial blood pressure by pulse transit time, in 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference (2005)Google Scholar
  19. 19.
    J.G. Webster, Design of Pulse Oximeters (CRC Press, Boca Raton, 1997)Google Scholar
  20. 20.
    K.N. Glaros, Low-power pulse oximetry and transimpedance amplifiers, Ph.D. dissertation, Imperial College London, 2011Google Scholar
  21. 21.
    R. Sarpeshkar, Universal principles for ultra low power and energy efficient design. IEEE Trans. Circuits Syst. Express Briefs 59(4), 193–198 (2012)CrossRefGoogle Scholar
  22. 22.
    N.V. Helleputte, S. Kim, H. Kim, J.P. Kim, C.V. Hoof, R.F. Yazicioglu, A 160 μA biopotential acquisition IC with fully integrated IA and motion artifact suppression. IEEE Trans. Biomed. Circuits Syst. 6(6), 552–561 (2012)CrossRefGoogle Scholar
  23. 23.
    J.L. Bohorquez, M. Yip, A.P. Chandrakasan, J.L. Dawson, A biomedical sensor interface with a sinc filter and interference cancellation. IEEE J. Solid State Circuits 46(4), 746–756 (2011)CrossRefGoogle Scholar
  24. 24.
    S. Kawahito, M. Yoshida, M. Sasaki, K. Umehara, D. Miyazaki, Y. Tadokoro, K. Murata, S. Doushou, A. Matsuzawa, A CMOS image sensor with analog two-dimensional DCT-based compression circuits for one-chip cameras. IEEE J. Solid State Circuits 32(12), 2030–2041 (1997)CrossRefGoogle Scholar
  25. 25.
    E.H. Lee, S.S. Wong, Analysis and design of a passive switched-capacitor matrix multiplier for approximate computing. IEEE J. Solid State Circuits 52(1), 261–271 (2017)CrossRefGoogle Scholar
  26. 26.
    L. Yan, P. Harpe, V.R. Pamula, M. Osawa, Y. Harada, K. Tamiya, C.V. Hoof, R.F. Yazicioglu, A 680 nA ECG acquisition IC for leadless pacemaker applications. IEEE Trans. Biomed. Circuits Syst. 8(6), 779–786 (2014)CrossRefGoogle Scholar
  27. 27.
    E. Candes, J. Romberg, T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. Inf. Theory 52(2), 489–509 (2006)MathSciNetCrossRefGoogle Scholar
  28. 28.
    D. Donoho, Compressed sensing. IEEE Trans. Inf. Theory 52(4), 1289–1306 (2006)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Venkata Rajesh Pamula
    • 1
  • Chris Van Hoof
    • 1
  • Marian Verhelst
    • 2
  1. 1.imecLeuvenBelgium
  2. 2.KU Leuven ESAT-MICASLeuvenBelgium

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