{"title":"Adaptive detection of action potentials using ultra low-power CMOS circuits","authors":"B. Gosselin, M. Sawan","doi":"10.1109/BIOCAS.2008.4696911","DOIUrl":null,"url":null,"abstract":"We present ultra low-power CMOS analog circuits for automatic detection of action potentials (APs). The proposed detection strategy locates AP waveforms and completely preserves their integrity. An adaptive threshold is implemented using a local time-averaging filter presenting a large time constant. The filter uses very small transconductances implemented by means of dedicated circuit techniques and subthreshold operation of MOS transistors. Also, a compact voltage squarer pre-processor is introduced to emphasize neural APs prior to detection. The proposed circuits were implemented in a CMOS 0.18-mum process and achieve ultra low-power consumption. Both circuits have been validated in simulations with synthetic neural waveforms. The adaptive threshold circuit dissipates only 27.2 nW, whereas the voltage squarer dissipates 76.7 nW.","PeriodicalId":415200,"journal":{"name":"2008 IEEE Biomedical Circuits and Systems Conference","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE Biomedical Circuits and Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOCAS.2008.4696911","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20
Abstract
We present ultra low-power CMOS analog circuits for automatic detection of action potentials (APs). The proposed detection strategy locates AP waveforms and completely preserves their integrity. An adaptive threshold is implemented using a local time-averaging filter presenting a large time constant. The filter uses very small transconductances implemented by means of dedicated circuit techniques and subthreshold operation of MOS transistors. Also, a compact voltage squarer pre-processor is introduced to emphasize neural APs prior to detection. The proposed circuits were implemented in a CMOS 0.18-mum process and achieve ultra low-power consumption. Both circuits have been validated in simulations with synthetic neural waveforms. The adaptive threshold circuit dissipates only 27.2 nW, whereas the voltage squarer dissipates 76.7 nW.