M. Konijnenburg, Yeon-Gon Cho, M. Ashouei, T. Gemmeke, Changmoo Kim, J. Hulzink, J. Stuyt, Mookyung Jung, J. Huisken, Soojung Ryu, Jungwook Kim, H. D. Groot
{"title":"Reliable and energy-efficient 1MHz 0.4V dynamically reconfigurable SoC for ExG applications in 40nm LP CMOS","authors":"M. Konijnenburg, Yeon-Gon Cho, M. Ashouei, T. Gemmeke, Changmoo Kim, J. Hulzink, J. Stuyt, Mookyung Jung, J. Huisken, Soojung Ryu, Jungwook Kim, H. D. Groot","doi":"10.1109/ISSCC.2013.6487801","DOIUrl":null,"url":null,"abstract":"Wireless Sensor Nodes (WSN) have a wide range of applications in health care and life style monitoring. Their severe energy constraint is often addressed through minimizing the amount of transmitted data by way of energy-efficient on-node signal processing. The rationale for this approach is that a large portion of WSN energy is consumed by the radio communication even for very low-data-rate situations [1]. Efficient on-node processing has been the subject of recent work, with the common element being aggressive voltage scaling into the sub-threshold region [2-4]. A major assumption of the existing works is that the amount of required computation is low, justifying an on-node processor with limited computational capability. While this might be the case for many applications of WSNs, emerging ambulatory biomedical signal processing applications exceed the performance offered by today's on-node processors.","PeriodicalId":6378,"journal":{"name":"2013 IEEE International Solid-State Circuits Conference Digest of Technical Papers","volume":"28 1","pages":"430-431"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Solid-State Circuits Conference Digest of Technical Papers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCC.2013.6487801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30
Abstract
Wireless Sensor Nodes (WSN) have a wide range of applications in health care and life style monitoring. Their severe energy constraint is often addressed through minimizing the amount of transmitted data by way of energy-efficient on-node signal processing. The rationale for this approach is that a large portion of WSN energy is consumed by the radio communication even for very low-data-rate situations [1]. Efficient on-node processing has been the subject of recent work, with the common element being aggressive voltage scaling into the sub-threshold region [2-4]. A major assumption of the existing works is that the amount of required computation is low, justifying an on-node processor with limited computational capability. While this might be the case for many applications of WSNs, emerging ambulatory biomedical signal processing applications exceed the performance offered by today's on-node processors.