A nano-watt ECG feature extraction engine in 65-nm technology

Temesghen Tekeste, Hani Saleh, Baker Mohammad, Ahsan Khandoker, Mohammed Ismail

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

This brief presents an ultralow power electrocardiography (ECG) feature extraction engine. ECG signal represents the cardiac cycle and contains key features, such as QRS complex, {P} -wave, and {T} -wave, which provide important diagnostic information about cardiovascular diseases. The ECG feature extraction is based on combined techniques of curve length transform (CLT) and discrete wavelet transform. A novel pipelined architecture for implementing CLT is proposed. The system was fabricated using GF-65-nm technology and consumed 642 nW only when operating at a frequency of 7.5 kHz from a supply voltage of 0.6 V. Ultralow power consumption of the SoC made it suitable for self-powered wearable devices.

Original languageBritish English
Article number7833083
Pages (from-to)1099-1103
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Volume65
Issue number8
DOIs
StatePublished - Aug 2018

Keywords

  • Curve length transform (CLT)
  • discrete wavelet transform (DWT)
  • electrocardiography (ECG) features
  • ultralow power

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