• DocumentCode
    727042
  • Title

    A 1 V, compact, current-mode neural spike detector with detection probability estimator in 65 nm CMOS

  • Author

    Enyi Yao ; Basu, Arindam

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2015
  • fDate
    24-27 May 2015
  • Firstpage
    754
  • Lastpage
    757
  • Abstract
    In this paper, we describe a novel low power, compact, current-mode spike detector circuit for real-time neural recording systems where neural spikes or action potentials (AP) are of interest. Such a circuit can enable massive compression of data facilitating wireless transmission. This design operates by approximating the popularly used nonlinear energy operator (NEO) through standard current mode analog blocks that can operate at low voltages. To reduce sensitivity of threshold setting, this work uses a current-mode oscillator based detection probability estimator (DPE) to reject false positives caused by the background noise. The circuit is implemented in a 65 nm CMOS process and occupies 200 μm × 150 μm of chip area. Operating from a 1 V power supply, it consumes about 88 nW of static power and 10 nJ of dynamic energy per input spike.
  • Keywords
    CMOS integrated circuits; current-mode circuits; low-power electronics; oscillators; probability; real-time systems; CMOS process; NEO; action potentials; background noise; compact current-mode neural spike detector; current-mode oscillator; detection probability estimator; low power spike detector circuit; massive compression; nonlinear energy operator; real-time neural recording systems; size 65 nm; standard current mode analog blocks; voltage 1 V; wireless transmission; Cutoff frequency; Detectors; Feature extraction; Noise; Noise measurement; Oscillators; Power dissipation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems (ISCAS), 2015 IEEE International Symposium on
  • Conference_Location
    Lisbon
  • Type

    conf

  • DOI
    10.1109/ISCAS.2015.7168743
  • Filename
    7168743