用于灵活应用的嵌入式低功耗心率估计处理器

Hui Qiu, Huajing Qin, Jiahao Liu, Liang Zhou, L. Chang, Jun Zhou
{"title":"用于灵活应用的嵌入式低功耗心率估计处理器","authors":"Hui Qiu, Huajing Qin, Jiahao Liu, Liang Zhou, L. Chang, Jun Zhou","doi":"10.1109/IFETC53656.2022.9948467","DOIUrl":null,"url":null,"abstract":"In this work, a photoplethysmography (PPG)-based heart rate (HR) estimation processor is designed and implemented for embedded signal processing of flexible heart rate monitoring devices. Compared with the exiting embedded signal processing solutions using Microcontrollers, this customized hardware solution is able to achieve much lower power consumption for long-term wearable health monitoring. Evaluated using the SPC dataset of 12 and 22 PPG recordings, the proposed design achieves a low mean absolute error (MAE) of 1.12 BPM and 2.14 BPM respectively. It consumes only 34.7 μW with a low processing latency of 6.2 ms, which is suitable for long-term wearable health monitoring.","PeriodicalId":289035,"journal":{"name":"2022 IEEE International Flexible Electronics Technology Conference (IFETC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Embedded Low Power Heart Rate Estimation Processor for Flexible Applications\",\"authors\":\"Hui Qiu, Huajing Qin, Jiahao Liu, Liang Zhou, L. Chang, Jun Zhou\",\"doi\":\"10.1109/IFETC53656.2022.9948467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, a photoplethysmography (PPG)-based heart rate (HR) estimation processor is designed and implemented for embedded signal processing of flexible heart rate monitoring devices. Compared with the exiting embedded signal processing solutions using Microcontrollers, this customized hardware solution is able to achieve much lower power consumption for long-term wearable health monitoring. Evaluated using the SPC dataset of 12 and 22 PPG recordings, the proposed design achieves a low mean absolute error (MAE) of 1.12 BPM and 2.14 BPM respectively. It consumes only 34.7 μW with a low processing latency of 6.2 ms, which is suitable for long-term wearable health monitoring.\",\"PeriodicalId\":289035,\"journal\":{\"name\":\"2022 IEEE International Flexible Electronics Technology Conference (IFETC)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Flexible Electronics Technology Conference (IFETC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IFETC53656.2022.9948467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Flexible Electronics Technology Conference (IFETC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFETC53656.2022.9948467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

在这项工作中,设计并实现了一个基于光电容积脉搏波(PPG)的心率(HR)估计处理器,用于柔性心率监测设备的嵌入式信号处理。与现有使用微控制器的嵌入式信号处理解决方案相比,该定制硬件解决方案能够实现更低的功耗,实现长期可穿戴健康监测。使用12和22 PPG记录的SPC数据集进行评估,所提出的设计分别实现了1.12 BPM和2.14 BPM的低平均绝对误差(MAE)。功耗仅为34.7 μW,处理延迟低至6.2 ms,适合长期可穿戴式健康监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Embedded Low Power Heart Rate Estimation Processor for Flexible Applications
In this work, a photoplethysmography (PPG)-based heart rate (HR) estimation processor is designed and implemented for embedded signal processing of flexible heart rate monitoring devices. Compared with the exiting embedded signal processing solutions using Microcontrollers, this customized hardware solution is able to achieve much lower power consumption for long-term wearable health monitoring. Evaluated using the SPC dataset of 12 and 22 PPG recordings, the proposed design achieves a low mean absolute error (MAE) of 1.12 BPM and 2.14 BPM respectively. It consumes only 34.7 μW with a low processing latency of 6.2 ms, which is suitable for long-term wearable health monitoring.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信