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A 4×32-Channel Neural Recording System for Deep Brain Stimulation Systems

  • Kim, Susie (Department of Electrical and Computer Engineering, Seoul National University) ;
  • Na, Seung-In (System LSI, Semiconductor Business Group, Samsung Electronics Co. Ltd.) ;
  • Yang, Youngtae (Department of Electrical and Computer Engineering, Seoul National University) ;
  • Kim, Hyunjong (Department of Electrical and Computer Engineering, Seoul National University) ;
  • Kim, Taehoon (Department of Electrical and Computer Engineering, Seoul National University) ;
  • Cho, Jun Soo (Department of Electrical and Computer Engineering, Seoul National University) ;
  • Kim, Jinhyung (Department of Neurosurgery, Yonsei University College of Medicine) ;
  • Chang, Jin Woo (Department of Neurosurgery, Yonsei University College of Medicine) ;
  • Kim, Suhwan (Department of Electrical and Computer Engineering, Seoul National University)
  • Received : 2016.03.27
  • Accepted : 2016.11.01
  • Published : 2017.02.28

Abstract

In this paper, a $4{\times}32$-channel neural recording system capable of acquiring neural signals is introduced. Four 32-channel neural recording ICs, complex programmable logic devices (CPLDs), a micro controller unit (MCU) with USB interface, and a PC are used. Each neural recording IC, implemented in $0.18{\mu}m$ CMOS technology, includes 32 channels of analog front-ends (AFEs), a 32-to-1 analog multiplexer, and an analog-to-digital converter (ADC). The mid-band gain of the AFE is adjustable in four steps, and have a tunable bandwidth. The AFE has a mid-band gain of 54.5 dB to 65.7 dB and a bandwidth of 35.3 Hz to 5.8 kHz. The high-pass cutoff frequency of the AFE varies from 18.6 Hz to 154.7 Hz. The input-referred noise (IRN) of the AFE is $10.2{\mu}V_{rms}$. A high-resolution, low-power ADC with a high conversion speed achieves a signal-to-noise and distortion ratio (SNDR) of 50.63 dB and a spurious-free dynamic range (SFDR) of 63.88 dB, at a sampling-rate of 2.5 MS/s. The effectiveness of our neural recording system is validated in in-vivo recording of the primary somatosensory cortex of a rat.

Keywords

References

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