research-article

A 36μW heartbeat-detection processor for a wireless sensor node

Authors:

Harmke De GrootAuthors Info & Claims

ACM Transactions on Design Automation of Electronic Systems (TODAES), Volume 16, Issue 4

Article No.: 51, Pages 1 - 19

https://doi.org/10.1145/2003695.2003711

Published: 27 October 2011 Publication History

Abstract

In order to provide better services to elderly people, home healthcare monitoring systems have been increasingly deployed. Typically, these systems are based on wireless sensor nodes, and should utilize very low energy during their lifetimes, as they are powered by scavengers. In this article, we present an ultra-low power processing system for a wireless sensor node for very low duty cycle applications. In the CoolBio system-on-chip, we utilized several power reduction techniques at both the architecture level and the circuit level. These techniques include feature extraction, voltage and frequency scaling, clock and power gating and a redesign of key standard cells. In the design of the ultra-low power processing system, we paid special attention to the memory subsystem, as it is one of the most power-consuming modules in a design. We also designed a clock manager in order to reduce the power consumed by clocking, and a power manager that is able to power-off unutilized modules. The proposed wireless sensor node processing system consumes 36.4μW at 100MHz and 1.2V supply voltage, for a heartbeat-detection algorithm with a 0.01% duty cycle.

References

[1]

Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., and Cayirci, E. 2002. A survey on sensor networks. IEEE Comm. Mag. 40, 8, 102--114.

Digital Library

[2]

Albu, D., Lukkien, J. J., and Verhoeven, R. 2010a. Energy effect of on-node processing of ECG signals. In Proceedings of the International Conference on Consumer Electronics. 7--8.

[3]

Albu, D., Lukkien, J. J., and Verhoeven, R. 2010b. On-node processing of ECG signals. In Proceedings of the 7th IEEE Consumer Communications and Networking Conference. IEEE, Los Alamitos, CA, 15.

Digital Library

[4]

Alioto, M. 2009. Understanding DC behavior of sub-threshold CMOS logic through closed-form analysis. IEEE Trans. Circuits Syst. PP, 99, 1--11.

Digital Library

[5]

Atmel. 2010. http://www.atmel.com/dyn/products/product_card.asp?part_id=2018.

[6]

Chen, S.-L., Lee, H.-Y., Chen, C.-A., Huang, H.-Y., and Luo, C.-H. 2009. Wireless body sensor network with adaptive low-power design for biometrics and healthcare applications. IEEE Syst. J. 3, 4, 398--409.

[7]

Crossbow. 2010. http://www.xbow.com/Industry_solutions/Overview.aspx.

[8]

Ekanayake, V., Kelly, C., and Manohar, R. 2004. An ultra low-power processor for sensor networks. ACM SIGOPS Oper. Syst. Rev. 38, 5, 27--36.

Digital Library

[9]

Hempstead, M., Wei, G.-Y., and Brooks, D. 2009. An accelerator-based wireless sensor network processor in 130nm CMOS. In Proceedings of the International Conference on Compilers, Architecture, and Synthesis for Embedded Systems. 215--222.

Digital Library

[10]

Hill, J., Horton, M., Kling, R., and Krishnamurthy, L. 2004. The platforms enabling wireless sensor networks. Comm. ACM 47, 6, 41--46.

Digital Library

[11]

Hive, S. 2010. http://www.siliconhive.com.

[12]

Hu, F., Xiao, Y., and Hao, Q. 2009. Congestion-aware, loss-resilient bio-monitoring sensor networking for mobile health applications. IEEE J. Select. Areas Comm. 27, 4, 450--465.

Digital Library

[13]

Kew, H.-P. and Jeong, D.-U. 2009. Wearable patch-type ECG using ubiquitous wireless sensor network for healthcare monitoring applications. In Proceedings of the 2nd International Conference on Interaction Sciences. 624--630.

Digital Library

[14]

Kumar, V., Sonavane, S. S., and Patil, B. P. 2009. Designing ultra low power wireless sensor network with TCP/IP link. In Proceedings of the 2nd International Conference on Adaptive Science and Technology. 86--91.

[15]

Lee, T.-S., Hong, J.-H., and Cho, M.-C. 2007. Biomedical digital assistant for ubiquitous healthcare. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, Los Alamitos, CA, 1790--1793.

[16]

Legarreta, I. R., Addison, P. S., Reed, M. J., Grubb, N., Clegg, G. R., Robertson, C. E., and Watson, J. N. 2005. Continuous wavelet transform modulus maxima analysis of the electrocardiogram: Beat characterisation and beat-to-beat measurement. Int. J. Wavelets, Multiresolution Inf. Process. 3, 1, 19--42.

[17]

Massagram, W., Hafner, N., Chen, M., Macchiarulo, L., Lubecke, V., and Lubecke, O. 2010. Digital heart-rate variability parameter monitoring and assessment ASIC. IEEE Trans. Biomed. Circuits Syst. 4, 1, 19--26.

[18]

Mathur, G., Desnoyers, P., Ganesan, D., and Shenoy, P. 2006. Ultra-low Power Data Storage for sensor networks. In Proceedings of the 5th International Conference on Information Processing in Sensor Networks. 374--381.

Digital Library

[19]

Noh, Y.-H. and Jeong, D.-U. 2009. Development and estimation of ubiquitous unconstrained BCG monitoring system using wireless sensor nodes. In Proceedings of the 2nd International Conference on Interaction Sciences. 514--520.

Digital Library

[20]

NXP. 2010. http://www.coolfluxdsp.com/index.cfm?id=89.

[21]

Park, C. and Chou, P. H. 2006. An ultra-wearable, wireless, low power ECG monitoring system. In Proceedings of the IEEE Biomedical Circuits and Systems Conference. IEEE, Los Alamitos, CA, 241--244.

[22]

Romero, I., Grundlehner, B., Penders, J., Huisken, J., and Yassin, Y. H. 2009. Low-power robust beat detection in ambulatory cardiac monitoring. In Proceedings of the IEEE Biomedical Circuits and Systems Conference. IEEE, Los Alamitos, CA, 249--252.

[23]

Sakaue, Y. and Makikawa, M. 2008. Development of wireless biosignal monitoring device. In Proceedings of the 6th International Special Topic Conference on Information Technology Applications in Biomedicine. 306--308.

[24]

Sakurai, T. and Newton, A. 1990. Alpha-power law MOSFET model and its applications to CMOS inverter delay and other formulas. IEEE J. Solid-State Circuits 25, 2, 584--594.

[25]

Sentilla. 2010. http://www.sentilla.com/moteiv-transition.html.

[26]

Sheets, M., Burghardt, F., Karalar, T., Ammer, J., Chee, Y., and Rabaey, J. 2006. A power-managed protocol processor for wireless sensor networks. In Proceedings of the Symposium on VLSI Circuits. 212--213.

[27]

Teo, T. H., Gopalakrishnan, P. K., Hwan, Y. S., Qian, X. B., Haridas, K., Pang, C. Y., and Je, M. 2009. A 700 μW single-chip IC for wireless continuous time health monitoring in 0.18 1m CMOS. In Proceedings of the IEEE Asian Solid-State Circuits Conference. IEEE, Los Alamitos, CA, 361--364.

[28]

TI. 2010. http://focus.ti.com/mcu/docs/mcugettingstarteddetail.tsp?sectionId=97&tabId=1511&familyId=342.

[29]

Xijun, C., Meng, M. Q. H., and Hongliang, R. 2005. Design of sensor node platform for wireless biomedical sensor networks. In Proceedings of the IEEE Engineering in Medicine and Biology Conference. IEEE, Los Alamitos, CA, 4662--4665.

[30]

Yick, J., Mukherjee, B., and Ghosal, D. 2008. Wireless sensor network survey. Comput. Netw. 52, 12, 2292--2330.

Digital Library

[31]

Yseboodt, L., Nil, M., Huisken, J., Berekovic, M., Zhao, Q., Bouwens, F., Hulzink, J., and Meerbergen, J. 2009. Design of 100 μW wireless sensor nodes for biomedical monitoring. J. Signal Process. Syst. 57, 1, 107--119.

Digital Library

[32]

Zeng, M., Lee, J.-G., Choi, G.-S., and Lee, J.-A. 2009. Intelligent sensor node based a low power ECG monitoring system. IEICE Electron. Express 6, 9, 560--565.

Cited By

Zhao CChen CChen ZMeng J(2016)Value locality based storage compression memory architecture for ECG sensor nodeScience China Information Sciences10.1007/s11432-015-5371-159:4Online publication date: 1-Mar-2016
https://doi.org/10.1007/s11432-015-5371-1
Kim CChung MCho YKonijnenburg MRyu SKim J(2014)ULP-SRPACM Transactions on Reconfigurable Technology and Systems10.1145/26296107:3(1-15)Online publication date: 3-Sep-2014
https://dl.acm.org/doi/10.1145/2629610
Kim CChung MCho YKonijnenburg MRyu SKim J(2012)ULP-SRP: Ultra low power Samsung Reconfigurable Processor for biomedical applications2012 International Conference on Field-Programmable Technology10.1109/FPT.2012.6412157(329-334)Online publication date: Dec-2012
https://doi.org/10.1109/FPT.2012.6412157

Index Terms

A 36μW heartbeat-detection processor for a wireless sensor node
1. Applied computing
  1. Computers in other domains
2. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems

Recommendations

Circuit and system design guidelines for ultra-low power sensor nodes
DAC '12: Proceedings of the 49th Annual Design Automation Conference

Designing an ultra-low power sensor node requires careful consideration of the system-level energy budget. Depending on applications, various components can dominate total energy. In this paper, we review three different system energy budget scenarios ...
A Node's Life: Increasing WSN Lifetime by Dynamic Voltage Scaling
DCOSS '13: Proceedings of the 2013 IEEE International Conference on Distributed Computing in Sensor Systems

In mobile applications, like wireless sensor networks, it is often inevitable to use a location-independent source of energy. Wherever the batteries capacity or inefficient energy harvesting limits the lifetime, other solutions have to be implemented to ...
Demo: TWIN Node, A Flexible Wireless Sensor Network Testbed
EWSN '16: Proceedings of the 2016 International Conference on Embedded Wireless Systems and Networks

In recent years, there is substantial growth in research in the field of Wireless Sensor Networks (WSNs). The applications of WSNs include smart homes, smart grids, smart roads, intelligent buildings, assisted living etc. Recently, researchers have ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Design Automation of Electronic Systems

ACM Transactions on Design Automation of Electronic Systems Volume 16, Issue 4

October 2011

326 pages

ISSN:1084-4309

EISSN:1557-7309

DOI:10.1145/2003695

Issue’s Table of Contents

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 27 October 2011

Accepted: 01 March 2011

Revised: 01 March 2011

Received: 01 July 2010

Published in TODAES Volume 16, Issue 4

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
292
Total Downloads

Downloads (Last 12 months)3
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Zhao CChen CChen ZMeng J(2016)Value locality based storage compression memory architecture for ECG sensor nodeScience China Information Sciences10.1007/s11432-015-5371-159:4Online publication date: 1-Mar-2016
https://doi.org/10.1007/s11432-015-5371-1
Kim CChung MCho YKonijnenburg MRyu SKim J(2014)ULP-SRPACM Transactions on Reconfigurable Technology and Systems10.1145/26296107:3(1-15)Online publication date: 3-Sep-2014
https://dl.acm.org/doi/10.1145/2629610
Kim CChung MCho YKonijnenburg MRyu SKim J(2012)ULP-SRP: Ultra low power Samsung Reconfigurable Processor for biomedical applications2012 International Conference on Field-Programmable Technology10.1109/FPT.2012.6412157(329-334)Online publication date: Dec-2012
https://doi.org/10.1109/FPT.2012.6412157

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents