Design and Implementation of Low Noise Amplifier in Neural Signal Analysis

  • Malti BansalEmail author
  • Diksha Singh
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1025)


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.


LNA SNR Neural Feedback amplifier Differential Impedance 


  1. 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. 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)CrossRefGoogle Scholar
  3. 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)CrossRefGoogle Scholar
  4. 4.
    Wise, K.D.: Silicon microsystems for neuroscience and neural prostheses. IEEE Eng. Med. Biol. Mag. 24(5), 22–29 (2005)CrossRefGoogle Scholar
  5. 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)CrossRefGoogle Scholar
  6. 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)CrossRefGoogle Scholar
  7. 7.
    Gosselin, B.: Recent advances in neural recording microsystems. Sensors 11, 4572–4597 (2011)CrossRefGoogle Scholar
  8. 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)CrossRefGoogle Scholar
  9. 9.
    Ng, K.A., Xu, Y.P.: A compact, low input capacitance neural recording amplifier. IEEE Trans. Biomed. Circuits Syst. 7, 610–620 (2013)CrossRefGoogle Scholar
  10. 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. 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)CrossRefGoogle Scholar
  12. 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. 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. 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. 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)CrossRefGoogle Scholar
  16. 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. 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)CrossRefGoogle Scholar
  18. 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)CrossRefGoogle Scholar
  19. 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. 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)CrossRefGoogle Scholar
  21. 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)CrossRefGoogle Scholar
  22. 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. 23.
    Razavi, B.: Design of Analog CMOS Integrated Circuits. McGraw-Hill, New York (2001)Google Scholar
  24. 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)CrossRefGoogle Scholar
  25. 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. 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

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© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Electronics and Communication EngineeringDelhi Technological University (DTU)DelhiIndia

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