An Energy-Efficient ECG Processor in 45-nm CMOS Using Statistical Error Compensation

A subthreshold ECG processor in 45-nm IBM SOI CMOS is designed to operate at the minimum energy operating point (MEOP). Statistical error compensation (SEC) is employed to further reduce energy (Emin) at the MEOP. SEC is shown to reduce Emin by 28% compared with the conventional (error-free) case while maintaining acceptable beat-detection performance. SEC enables the supply voltage to be scaled to 15% below its critical value at MEOP, while compensating for a 58% precorrection error rate pe. These results represent an improvement of 19× in beat-detection performance and 600× in pe over conventional (error-free) systems. The prototype IC consumes 14.5 fJ/cycle/1k-gate and exhibits 4.7× better energy efficiency than the state of the art while tolerating 16× more voltage variations.

[1]  David Blaauw,et al.  Razor II: In Situ Error Detection and Correction for PVT and SER Tolerance , 2008, 2008 IEEE International Solid-State Circuits Conference - Digest of Technical Papers.

[2]  J. Barendregt,et al.  Global burden of disease , 1997, The Lancet.

[3]  R. Hegde,et al.  A voltage overscaled low-power digital filter IC , 2004, IEEE Journal of Solid-State Circuits.

[4]  Naresh R. Shanbhag,et al.  A 14.5 fJ/cycle/k-gate, 0.33 V ECG processor in 45nm CMOS using statistical error compensation , 2012, Proceedings of the IEEE 2012 Custom Integrated Circuits Conference.

[5]  Mohamed Najim,et al.  ECG Beat Detection Using a Geometrical Matching Approach , 2007, IEEE Transactions on Biomedical Engineering.

[6]  Trevor Mudge,et al.  A self-tuning DVS processor using delay-error detection and correction , 2005, VLSIC 2005.

[7]  Ross Ward.  Promoting Cardiovascular Health in the Developing World , 2011 .

[8]  Mario Konijnenburg,et al.  A voltage-scalable biomedical signal processor running ECG using 13pJ/cycle at 1MHz and 0.4V , 2011, 2011 IEEE International Solid-State Circuits Conference.

[9]  Kaushik Roy,et al.  Ultra-low power DLMS adaptive filter for hearing aid applications , 2001, ISLPED '01.

[10]  Dimitrios I. Fotiadis,et al.  An arrhythmia classification system based on the RR-interval signal , 2005, Artif. Intell. Medicine.

[11]  David M. Bull,et al.  RazorII: In Situ Error Detection and Correction for PVT and SER Tolerance , 2009, IEEE Journal of Solid-State Circuits.

[12]  Naresh R. Shanbhag,et al.  Soft digital signal processing , 2001, IEEE Trans. Very Large Scale Integr. Syst..

[13]  Douglas L. Jones,et al.  Stochastic computation , 2010, Design Automation Conference.

[14]  Chi-Sang Poon,et al.  Analysis of First-Derivative Based QRS Detection Algorithms , 2008, IEEE Transactions on Biomedical Engineering.

[15]  Anantha Chandrakasan,et al.  Variation-Driven Device Sizing for Minimum Energy Sub-threshold Circuits , 2006, ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design.

[16]  Seok-Jun Lee,et al.  Microwatt Embedded Processor Platform for Medical System-on-Chip Applications , 2011, IEEE Journal of Solid-State Circuits.

[17]  Willis J. Tompkins,et al.  A Real-Time QRS Detection Algorithm , 1985, IEEE Transactions on Biomedical Engineering.

[18]  David Blaauw,et al.  A Super-Pipelined Energy Efficient Subthreshold 240 MS/s FFT Core in 65 nm CMOS , 2012, IEEE Journal of Solid-State Circuits.

[19]  Soo-Won Kim,et al.  A low complexity, low power, programmable QRS detector based on wavelet transform for Implantable Pacemaker IC , 2006, 2006 IEEE International SOC Conference.

[20]  Stuart N. Wooters,et al.  A 2.6-µW sub-threshold mixed-signal ECG SoC , 2009, 2009 Symposium on VLSI Circuits.

[21]  J. Kwong,et al.  An Energy-Efficient Biomedical Signal Processing Platform , 2010, IEEE Journal of Solid-State Circuits.

[22]  Mingoo Seok,et al.  Nanometer Device Scaling in Subthreshold Logic and SRAM , 2008, IEEE Transactions on Electron Devices.

[23]  David Blaauw,et al.  Energy Optimality and Variability in Subthreshold Design , 2006, ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design.

[24]  Luca Benini,et al.  A multiprocessor system-on-chip for real-time biomedical monitoring and analysis: ECG prototype architectural design space exploration , 2008, TODE.

[25]  Refet Firat Yazicioglu,et al.  A 30 $\mu$ W Analog Signal Processor ASIC for Portable Biopotential Signal Monitoring , 2011, IEEE Journal of Solid-State Circuits.

[26]  Xin Liu,et al.  Power and Area Efficient Wavelet-Based On-chip ECG Processor for WBAN , 2010, 2010 International Conference on Body Sensor Networks.

[27]  Zhao Yan.  MIT-BIH Arrhythmia Database Signal Generator Based on MSP430 , 2009 .

[28]  Naresh R. Shanbhag,et al.  Minimum-Energy Operation Via Error Resiliency , 2010, IEEE Embedded Systems Letters.

[29]  K.A. Bowman,et al.  Energy-Efficient and Metastability-Immune Resilient Circuits for Dynamic Variation Tolerance , 2009, IEEE Journal of Solid-State Circuits.

[30]  Brian Otis,et al.  A Low-Power ECoG/EEG Processing IC With Integrated Multiband Energy Extractor , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[31]  H. T. Nagle,et al.  A comparison of the noise sensitivity of nine QRS detection algorithms , 1990, IEEE Transactions on Biomedical Engineering.

[32]  Meng-chou Chang,et al.  Design of a system-on-chip for ECG signal processing , 2004, The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, 2004. Proceedings..

[33]  A. Amann,et al.  Reliability of old and new ventricular fibrillation detection algorithms for automated external defibrillators , 2005, Biomedical engineering online.

[34]  Douglas L. Jones,et al.  Low power and error resilient PN code acquisition filter via statistical error compensation , 2011, 2011 IEEE Custom Integrated Circuits Conference (CICC).

[35]  Naveen Verma,et al.  A Micro-Power EEG Acquisition SoC With Integrated Feature Extraction Processor for a Chronic Seizure Detection System , 2010, IEEE Journal of Solid-State Circuits.

[36]  David Bol,et al.  Nanometer MOSFET Effects on the Minimum-Energy Point of Sub-45nm Subthreshold Logic---Mitigation at Technology and Circuit Levels , 2010, TODE.

[37]  R. Orglmeister,et al.  The principles of software QRS detection , 2002, IEEE Engineering in Medicine and Biology Magazine.

[38]  Paul Rubel,et al.  Toward a Personal Health Society in Cardiology , 2010, IEEE Transactions on Information Technology in Biomedicine.