A 400 MHz Wireless Neural Signal Processing IC with 625 × On-Chip Data Reduction and Reconfigurable BFSK/QPSK Transmitter Based on Sequential Injection Locking

Kok Hin Teng, Tong Wu, Xiayun Liu, Zhi Yang, Chun Huat Heng

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

An 8-channel wireless neural signal processing IC, which can perform real-time spike detection, alignment, and feature extraction, and wireless data transmission is proposed. A reconfigurable BFSK/QPSK transmitter (TX) at MICS/MedRadio band is incorporated to support different data rate requirement. By using an Exponential Component-Polynomial Component (EC-PC) spike processing unit with an incremental principal component analysis (IPCA) engine, the detection of neural spikes with poor SNR is possible while achieving 625× data reduction. For the TX, a dual-channel at 401 MHz and 403.8 MHz are supported by applying sequential injection locked techniques while attaining phase noise of -102 dBc/Hz at 100 kHz offset. From the measurement, error vector magnitude (EVM) of 4.60%/9.55% with power amplifier (PA) output power of -15 dBm is achieved for the QPSK at 8 Mbps and the BFSK at 12.5 kbps. Fabricated in 65 nm CMOS with an active area of 1 mm2, the design consumes a total current of 5 ∼5.6 mA with a maximum energy efficiency of 0.7 nJ/b.

Original languageEnglish (US)
Article number7870624
Pages (from-to)547-557
Number of pages11
JournalIEEE transactions on biomedical circuits and systems
Volume11
Issue number3
DOIs
StatePublished - Jun 2017

Keywords

  • Exponential component-polynomial component (EC-PC)
  • feature extraction
  • incremental principal component analysis (IPCA)
  • injection locking
  • neural signal processing
  • reconfigurable
  • spike detection
  • spike sorting
  • transmitter

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