Suppr超能文献

用于剧烈运动的轻便腕部光电容积脉搏波描记法:运动稳健心率监测算法

Lightweight wrist photoplethysmography for heavy exercise: motion robust heart rate monitoring algorithm.

作者信息

Lai Po-Hsiang, Kim Insoo

机构信息

Samsung Research America - Dallas , Richardson , TX 75082 , USA.

出版信息

Healthc Technol Lett. 2015 Feb 24;2(1):6-11. doi: 10.1049/htl.2014.0097. eCollection 2015 Feb.

Abstract

The challenge of heart rate monitoring based on wrist photoplethysmography (PPG) during heavy exercise is addressed. PPG is susceptible to motion artefacts, which have to be mitigated for accurate heart rate estimation. Motion artefacts are particularly apparent for wrist devices, for example, a smart watch, because of the high mobility of the arms. Proposed is a low complexity highly accurate heart rate estimation method for continuous heart rate monitoring using wrist PPG. The proposed method achieved 2.57% mean absolute error in a test data set where subjects ran for a maximum speed of 17 km/h.

摘要

本文探讨了在剧烈运动期间基于手腕光电容积脉搏波描记法(PPG)进行心率监测的挑战。PPG容易受到运动伪影的影响,为了准确估计心率,必须减轻这些伪影。由于手臂的高活动性,运动伪影在手腕设备(如智能手表)中尤为明显。本文提出了一种低复杂度、高精度的心率估计方法,用于使用手腕PPG进行连续心率监测。在所提出的方法在一个测试数据集中实现了2.57%的平均绝对误差,在该数据集中受试者以最高17公里/小时的速度跑步。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4506/4614154/0146f0c1adfc/HTL.2014.0097.01.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验