Skip to main content

Embedded Medical Microsystems

Neural Recording Implants

  • Chapter
Book cover Design Technology for Heterogeneous Embedded Systems
  • 1236 Accesses

Abstract

This chapter presents dedicated circuit techniques and strategies to design and assemble dense embedded microsystems intended for bioelectrical signals recording applications. Efficient interfacing circuits to measure the weak bioelectrical signal from several cells in the cortical tissues are covered, and high-fidelity data-reduction strategies are demonstrated. Also, on-chip power management schemes based on automatic biopotential detection are presented to decrease power consumption of neural recording implants by an order of magnitude. In addition, low-power design techniques, ultra-low-power neural signal processing circuits, and dedicated implementation strategies enabling for high-density multi-channel neural recording microsystem integration are also covered.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Coulombe, J., Sylvain, C., Mohamad, S.: A power efficient electronic implant for a visual cortical neuroprosthesis. Artif. Organs 29, 233–238 (2005)

    Article  Google Scholar 

  2. Hu, Y., Sawan, M.: A fully integrated low-power BPSK demodulator for implantable medical devices. IEEE Trans. Circuits Syst. I, Regul. Pap. 52, 2552–2562 (2005)

    Article  Google Scholar 

  3. Hu, Y., Sawan, M., El-Gamal, M.N.: An integrated power recovery module dedicated to implantable electronic devices. Analog Integr. Circuits Signal Process. 43, 171–181 (2005)

    Article  Google Scholar 

  4. Sawan, M., Yamu, H., Coulombe, J.: Wireless smart implants dedicated to multichannel monitoring and microstimulation. IEEE Circuits Syst. Mag. 5, 21–39 (2005)

    Article  Google Scholar 

  5. Djemouai, A., Sawan, M.: Circuit techniques dedicated to effectively wireless transfer power and data to electronic implants. J. Circuits Syst. Comput. 16, 801–818 (2007)

    Article  Google Scholar 

  6. Harb, A., Hu, Y., Sawan, M., Abdelkerim, A., Elhilali, M.M.: Low-power CMOS interface for recording and processing very low amplitude signals. Analog Integr. Circuits Signal Process. 39, 39–54 (2004)

    Article  Google Scholar 

  7. Sawan, M., Mounaim, F., Lesbros, G.: Wireless monitoring of electrode-tissues interfaces for long term characterization. Analog Integr. Circuits Signal Process. 55, 103–114 (2008)

    Article  Google Scholar 

  8. Gosselin, B., Ayoub, A.E., Roy, J.F., Sawan, M., Lepore, F., Chaudhuri, A., Guitton, D.: A mixed-signal multichip neural recording interface with bandwidth reduction. IEEE Trans. Biomed. Circuits Syst. 3, 129–141 (2009)

    Article  Google Scholar 

  9. Ghafar-Zadeh, E., Sawan, M.: Charge based capacitive sensor array for CMOS based laboratory-on-chip applications. In: 5th IEEE Conference on Sensors, pp. 378–381 (2006)

    Google Scholar 

  10. Boyer, S., Sawan, M., Abdel-Gawad, M., Robin, S., Elhilali, M.M.: Implantable selective stimulator to improve bladder voiding: design and chronic experiments in dogs. IEEE Trans. Rehabil. Eng. 8, 464–470 (2000)

    Article  Google Scholar 

  11. Coulombe, J., Sawan, M., Gervais, J.F.: A highly flexible system for microstimulation of the visual cortex: design and implementation. IEEE Trans. Biomed. Circuits Syst. 1, 258–269 (2007)

    Article  Google Scholar 

  12. Mandal, S., Sarpeshkar, R.: Power-efficient impedance-modulation wireless data links for biomedical implants. IEEE Trans. Biomed. Circuits Syst. 2, 301–315 (2008)

    Article  Google Scholar 

  13. Gosselin, B., Sawan, M., Chapman, C.A.: A low-power integrated bioamplifier with active low-frequency suppression. IEEE Trans. Biomed. Circuits Syst. 1, 184–192 (2007)

    Article  Google Scholar 

  14. Olsson, R.H. III, Wise, K.D.: A three-dimensional neural recording microsystem with implantable data compression circuitry. IEEE J. Solid-State Circuits 40, 2796–2804 (2005)

    Article  Google Scholar 

  15. Harrison, R.R., Watkins, P.T., Kier, R.J., Lovejoy, R.O., Black, D.J., Greger, B., Solzbacher, F.: A low-power integrated circuit for a wireless 100-electrode neural recording system. IEEE J. Solid-State Circuits 42, 123–133 (2007)

    Article  Google Scholar 

  16. Sodagar, A.M., Wise, K.D., Najafi, K.: A fully integrated mixed-signal neural processor for implantable multichannel cortical recording. IEEE Trans. Biomed. Eng. 54, 1075–1088 (2007)

    Article  Google Scholar 

  17. Sarpeshkar, R., Wattanapanitch, W., Arfin, S.K., Rapoport, B.I., Mandal, S., Baker, M.W., Fee, M.S., Musallam, S., Andersen, R.A.: Low-power circuits for brain–machine interfaces. IEEE Trans. Biomed. Circuits Syst. 2, 173–183 (2008)

    Article  Google Scholar 

  18. Harrison, R.R., Charles, C.: A low-power low-noise CMOS amplifier for neural recording applications. IEEE J. Solid-State Circuits 38, 958–965 (2003)

    Article  Google Scholar 

  19. Wattanapanitch, W., Fee, M., Sarpeshkar, R.: An energy-efficient micropower neural recording amplifier. IEEE Trans. Biomed. Circuits Syst. 1, 136–147 (2007)

    Article  Google Scholar 

  20. Aziz, J.N.Y., Genov, R., Bardakjian, B.L., Derchansky, M., Carlen, P.L.: Brain/silicon interface for high-resolution in vitro neural recording. IEEE Trans. Biomed. Circuits Syst. 1, 56–62 (2007)

    Article  Google Scholar 

  21. Kandel, E.R., Schwartz, J.H., Jessell, T.M.: Principles of Neural Science. McGraw-Hill Medical, New York (2000)

    Google Scholar 

  22. Vittoz, E.A.: Micropower techniques. In: Franca, J.E., Tsividis, Y. (eds.) Design of Analog-Digital VLSI Circuits for Telecommunications and Signal Processing, pp. 53–96. Prentice-Hall, Upper Saddle River (1994)

    Google Scholar 

  23. Enz, C., Krummenacher, F., Vittoz, E.A.: An analytical MOS transistor model valid in all regions of operation and dedicated to low-voltage and low-current applications. Analog Integr. Circuits Signal Process. 8, 83–114 (1995)

    Article  Google Scholar 

  24. Mohseni, P., Najafi, K.: A fully integrated neural recording amplifier with DC input stabilization. IEEE Trans. Biomed. Eng. 51, 832–837 (2004)

    Article  Google Scholar 

  25. Johns, D., Martin, K.: Analog Integrated Circuit Design:. Wiley, New York (1996)

    Google Scholar 

  26. Perelman, Y., Ginosar, R.: An integrated system for multichannel neuronal recording with spike/LFP separation, integrated A/D conversion and threshold detection. IEEE Trans. Biomed. Eng. 54, 130–137 (2007)

    Article  Google Scholar 

  27. Azin, M., Mohseni, P.: A 94-μW 10-b neural recording front-end for an implantable brain-machine-brain interface device. In: The 2008 IEEE Biomedical Circuits and Systems Conference, pp. 221–224 (2008)

    Chapter  Google Scholar 

  28. Horiuchi, T., Swindell, T., Sander, D., Abshier, P.: A low-power CMOS neural amplifier with amplitude measurements for spike sorting. In: The 2004 International Symposium on Circuits and Systems, vol. IV, pp. 29–32 (2004)

    Google Scholar 

  29. Rogers, C.L., Harris, J.G.: A low-power analog spike detector for extracellular neural recordings. In: The 2004 11th IEEE International Conference on Electronics, Circuits and Systems, pp. 290–293 (2004)

    Chapter  Google Scholar 

  30. Haas, A.M., Cohen, M.H., Abshire, P.A.: Real-time variance based template matching spike sorting system. In: The 2007 IEEE/NIH Life Science Systems and Applications Workshop, pp. 104–107 (2007)

    Chapter  Google Scholar 

  31. Gosselin, B., Sawan, M.: A low-power integrated neural interface with digital spike detection and extraction. Analog Integr. Circuits Signal Process. 64, 3–11 (2010). doi:10.1007/s10470-009-9371-1

    Article  Google Scholar 

  32. Gosselin, B., Zbrzeski, A., Sawan, M., Kerherve, E.: Low-power linear-phase delay filters for neural signal processing: comparison and synthesis. In: IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1261–1264 (2009)

    Google Scholar 

  33. Gosselin, B., Sawan, M.: Adaptive detection of action potentials using ultra low-power CMOS circuits. In: The 2008 IEEE Biomedical Circuits and Systems Conference (BIOCAS), pp. 209–212 (2008)

    Chapter  Google Scholar 

  34. Sarpeshkar, R., Lyon, R.F., Mead, C.: A low-power wide-linear-range transconductance amplifier. Analog Integr. Circuits Signal Process. 13, 123–151 (1997)

    Article  Google Scholar 

  35. Chun-Ming, C., Chun-Li, H., Wen-Yaw, C., Jiun-Wei, H., Chu-Kuei, T.: Analytical synthesis of high-order single-ended-input OTA-grounded C all-pass and band-reject filter structures. IEEE Trans. Circuits Syst. I 53, 489–498 (2006)

    Article  Google Scholar 

  36. Corbishley, P., Rodriguez-Villegas, E.: A nanopower bandpass filter for detection of an acoustic signal in a wearable breathing detector. IEEE Trans. Biomed. Circuits Syst. 1, 163–171 (2007)

    Article  Google Scholar 

  37. Bellaouar, A., Elmasry, M.: Low-Power Digital VLSI Design: Circuits and Systems. Springer, Berlin (1995)

    Book  Google Scholar 

  38. Gosselin, B., Sawan, M.: Event-driven data and power management in high-density neural recording microsystems. In: Joint IEEE North-East Workshop on Circuits and Systems (NEWCAS’09) and TAISA Conference, pp. 1–4 (2009). Invited paper

    Chapter  Google Scholar 

  39. Hyung-Ock, K., Youngsoo, S.: Semicustom design methodology of power gated circuits for low leakage applications. IEEE Trans. Circuits Syst. II 54, 512–516 (2007)

    Article  Google Scholar 

  40. Harrison, R.R.: A low-power integrated circuit for adaptive detection of action potentials in noisy signals. In: The 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 3325–3328 (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Benoit Gosselin .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Science+Business Media B.V.

About this chapter

Cite this chapter

Gosselin, B., Sawan, M. (2012). Embedded Medical Microsystems. In: Nicolescu, G., O'Connor, I., Piguet, C. (eds) Design Technology for Heterogeneous Embedded Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1125-9_17

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-1125-9_17

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-1124-2

  • Online ISBN: 978-94-007-1125-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics