{"title":"An ECG-SoC with 535nW/channel lossless data compression for wearable sensors","authors":"Deepu John","doi":"10.1109/ASSCC.2013.6691003","DOIUrl":null,"url":null,"abstract":"This paper presents a low power ECG recording Sys-tem-on-Chip (SoC) with on-chip low complexity lossless ECG compression for data reduction in wireless/ambulatory ECG sensor devices. The proposed algorithm uses a linear slope predictor to estimate the ECG samples, and uses a novel low complexity dynamic coding-packaging scheme to frame the resulting estimation error into fixed-length 16-bit format. The proposed technique achieves an average compression ratio of 2.25× on MIT/BIH ECG database. Implemented in 0.35 μm process, the compressor uses 0.565 K gates/channel occupying 0.4 mm2 for 4-channel, and consumes 535 nW/channel at 2.4V for ECG sampled at 512 Hz. Small size and ultra-low power consumption makes the proposed technique suitable for wearable ECG sensor application.","PeriodicalId":296544,"journal":{"name":"2013 IEEE Asian Solid-State Circuits Conference (A-SSCC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Asian Solid-State Circuits Conference (A-SSCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASSCC.2013.6691003","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
This paper presents a low power ECG recording Sys-tem-on-Chip (SoC) with on-chip low complexity lossless ECG compression for data reduction in wireless/ambulatory ECG sensor devices. The proposed algorithm uses a linear slope predictor to estimate the ECG samples, and uses a novel low complexity dynamic coding-packaging scheme to frame the resulting estimation error into fixed-length 16-bit format. The proposed technique achieves an average compression ratio of 2.25× on MIT/BIH ECG database. Implemented in 0.35 μm process, the compressor uses 0.565 K gates/channel occupying 0.4 mm2 for 4-channel, and consumes 535 nW/channel at 2.4V for ECG sampled at 512 Hz. Small size and ultra-low power consumption makes the proposed technique suitable for wearable ECG sensor application.