Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data

Published:2017-01-20 Issue:2 Volume:38 Page:343-357
ISSN:0967-3334
Container-title:Physiological Measurement
language:
Short-container-title:Physiol. Meas.

Author:

Montoye Alexander H K,Begum Munni,Henning Zachary,Pfeiffer Karin A

Funder

Blue Cross Blue Shield of Michigan Foundation

Publisher

IOP Publishing

Subject

Physiology (medical),Biomedical Engineering,Physiology,Biophysics

Link

http://stacks.iop.org/0967-3334/38/i=2/a=343/pdf

Reference47 articles.

1. Activity Recognition from User-Annotated Acceleration Data

2. Behavioral Periodicity Detection from 24 h Wrist Accelerometry and Associations with Cardiometabolic Risk and Health-Related Quality of Life

3. Optimal Placement of Accelerometers for the Detection of Everyday Activities

4. A novel method for using accelerometer data to predict energy expenditure

Cited by 48 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Composite activity type and stride-specific energy expenditure estimation model for thigh-worn accelerometry;International Journal of Behavioral Nutrition and Physical Activity;2024-09-10

2. Estimation of Energy Expenditure in Wearable Healthcare Technology by Quantum-Based LSTM Modeling (Invited Paper);2024 International Conference on Quantum Communications, Networking, and Computing (QCNC);2024-07-01

3. Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks;Sensors;2024-04-14

4. Comparative Analysis between IMU Signal-based Neural Network Models for Energy Expenditure Estimation;Journal of the Korean Society for Precision Engineering;2024-03-01

5. IMU-Based Energy Expenditure Estimation for Various Walking Conditions Using a Hybrid CNN–LSTM Model;Sensors;2024-01-10

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3