Skip to main content
SpringerLink
Log in

Design and Implementation of Low Noise Amplifier in Neural Signal Analysis

  • Conference paper
  • First Online:
Information, Communication and Computing Technology (ICICCT 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1025))

Abstract

LNA is an important component of transceivers and is widely used in neural signal analysis. In this paper, we review the different topologies and configurations used for LNA in neural applications. We compare the different topologies and conclude which one is the best topology among the ones studied on basis of certain parameters that govern the performance of a LNA for neural applications. According to our analysis, CMOS bipotential amplifier is the most appropriate neural amplifier in terms of all design parameters taken into consideration for use of LNA in neural applications.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Bhalani, H.V., Prabhakar, N.M.: Rudimentary study and design process of low noise amplifier at Ka band. IJ Publ. 3(2), 1181–1183 (2015)

    Google Scholar 

  2. Imai, Y., Tokumitsu, M., Minakawa, A.: Design and performance of low-current GaAs MMIC’s for L-band front-end applications. IEEE Trans. Microw. Theory Tech. 39(2), 209–215 (1991)

    Article  Google Scholar 

  3. Mussa-Ivaldi, F.A., Miller, L.E.: Brain-machine interfaces: computational demands and clinical needs meet basic neuroscience. Trends Neurosci. 26(6), 329–334 (2003)

    Article  Google Scholar 

  4. Wise, K.D.: Silicon microsystems for neuroscience and neural prostheses. IEEE Eng. Med. Biol. Mag. 24(5), 22–29 (2005)

    Article  Google Scholar 

  5. Butson, C.R., McIntyre, C.C.: Role of electrode design on the volume of tissue activated during deep brain stimulation. J. Neural Eng. 3(1), 1–8 (2006)

    Article  Google Scholar 

  6. Logothetis, N.K.: The neural basis of the blood-oxygen-level-dependent functional magnetic resonance imaging signal. Philos. Trans. Roy. Soc. Lond. B Biol. Sci. 357(1424), 1003–1037 (2002)

    Article  Google Scholar 

  7. Gosselin, B.: Recent advances in neural recording microsystems. Sensors 11, 4572–4597 (2011)

    Article  Google Scholar 

  8. Chaturvedi, V., Amrutur, B.: An area efficient noise-adaptive neural amplifier in 130 nm CMOS technology. IEEE J. Emerg. Sel. Top. Circuits Syst. 1, 536–545 (2011)

    Article  Google Scholar 

  9. Ng, K.A., Xu, Y.P.: A compact, low input capacitance neural recording amplifier. IEEE Trans. Biomed. Circuits Syst. 7, 610–620 (2013)

    Article  Google Scholar 

  10. Saberhosseini, S.S.: A micro-power low-noise amplifier for neural recording microsystems. In: ICEE 2012 - 20th Iranian Conference on Electrical Engineering, pp. 314–317 (2012)

    Google Scholar 

  11. Blalock, B.J., Allen, P.E., Rincon-Mora, G.A.: Designing 1-V Op amps using standard digital CMOS technology. IEEE Trans. Circuits Syst. II Analog Digit. Signal Process. 45, 769–780 (1998)

    Article  Google Scholar 

  12. Kim, H.S., Cha, H.-K.: A low power, low-noise neural recording amplifier for implantable devices. In: Proceedings of International SoC Design Conference (ISOCC), pp. 275–276 (2016)

    Google Scholar 

  13. Dwivedi, S., Gogoi, A.K.: Local field potential measurement with low-power area-efficient neural recording amplifier. In: Proceedings of IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES), pp. 1–5 (2015)

    Google Scholar 

  14. Ahmed, M., Shah, I., Tang, F., Bermak, A.: An improved recycling folded cascode amplifier with gain boosting and phase margin enhancement. In: Proceedings of IEEE International Symposium on Circuits and Systems (ISCAS), pp. 2473–2476 (2015)

    Google Scholar 

  15. Li, Y.L., Han, K.F., Tan, X., Yan, N., Min, H.: Transconductance enhancement method for operational transconductance amplifiers. Electron. Lett. 46(19), 1321–1323 (2010)

    Article  Google Scholar 

  16. Cerida, S., Raygada, E., Silva, C., Monge, M.: Low noise differential recycling folded cascade neural amplifier. In: Proceedings of IEEE 6th Latin America Symposium on Circuits and Systems (LASCAS), pp. 1–4 (2015)

    Google Scholar 

  17. Assaad, R.S., Silva-Martinez, J.: The recycling folded cascode: a general enhancement of the folded cascode amplifier. IEEE J. Solid State Circuits 44(9), 2535–2542 (2009)

    Article  Google Scholar 

  18. Majidzadeh, V., Schmid, A., Leblebici, Y.: Energy efficient low-noise neural recording amplifier with enhanced noise efficiency factor. IEEE Trans. Biomed. Circuits Syst. 5(3), 262–271 (2011)

    Article  Google Scholar 

  19. IEEE Standard for Safety Levels With Respect to Human Exposure to Radio Frequency Electromagnetic Fields, 3 kHz to 300 GHz. IEEE Std. C95.1-2005 (2006)

    Google Scholar 

  20. Lopez, C.M., et al.: A multichannel integrated circuit for electrical recording of neural activity with independent channel programmability. IEEE Trans. Biomed. Circuits Syst. 6(2), 101–110 (2012)

    Article  Google Scholar 

  21. Harrison, R.R., Charles, C.: A low-power low-noise CMOS amplifier for neural record ing applications. IEEE J. Solid-State Circuits 38(6), 958–965 (2003)

    Article  Google Scholar 

  22. Ghaderi, N., Kazemi-Ghahfarokhi, S.-M.: A low noise neural amplifer using bulk driven cascode current mirror load. In: Proceedings of 9th International Conference on Electrical and Electronics Engineering (ELECO), pp. 76–80 (2015)

    Google Scholar 

  23. Razavi, B.: Design of Analog CMOS Integrated Circuits. McGraw-Hill, New York (2001)

    Google Scholar 

  24. Yang, T., Hollemann, J.: An ultralow-power low noise CMOS bipotential amplifier for neural recording. IEEE Trans. Circuits Syst. II Express Briefs 62(10), 927–931 (2015)

    Article  Google Scholar 

  25. Holleman, J., Otis, B.: A sub-microwatt low-noise amplifier for neural recording. In: Proceedings of 29th Annual International Conference on IEEE Engineering in Medicine and Biology Society, pp. 3930–3933 (2007)

    Google Scholar 

  26. Valtierra, J.L., Rodríguez-Vázquez, Á., Delgado-Restituto, M.: 4 mode reconfigurable low noise amplifier for implantable neural recording channels. In: 12th Conference on PhD Research in Microelectronics and Electronics (PRIME), pp. 1–4 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Delhi Technological University (DTU), Delhi, 110042, India

    Malti Bansal & Diksha Singh

Authors
  1. Malti Bansal
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Diksha Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Malti Bansal .

Editor information

Editors and Affiliations

  1. University of Malaya, Kuala Lumpur, Malaysia

    Abdullah Bin Gani

  2. Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, Guwahati, India

    Pradip Kumar Das

  3. Department of IT, Jagan Institute of Management Studies, New Delhi, India

    Latika Kharb

  4. Department of IT, Jagan Institute of Management Studies, New Delhi, India

    Deepak Chahal

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bansal, M., Singh, D. (2019). Design and Implementation of Low Noise Amplifier in Neural Signal Analysis. In: Gani, A., Das, P., Kharb, L., Chahal, D. (eds) Information, Communication and Computing Technology. ICICCT 2019. Communications in Computer and Information Science, vol 1025. Springer, Singapore. https://doi.org/10.1007/978-981-15-1384-8_2

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-1384-8_2

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1383-1

  • Online ISBN: 978-981-15-1384-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation