ArticleIEEE transactions on bio-medical engineering2011
Determining energy expenditure from treadmill walking using hip-worn inertial sensors: an experimental study.
Article in IEEE transactions on bio-medical engineering, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 45 citations in OpenAlex.
- Intelligent Estimation of Exercise Induced Energy Expenditure Including Excess Post-Exercise Oxygen Consumption (EPOC) with Different Exercise Intensity.Sensors (Basel, Switzerland) · 2023Article
- Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation.Sensors (Basel, Switzerland) · 2021Article
- The potential of artificial intelligence in enhancing adult weight loss: a scoping review.Public health nutrition · 2021Article
- Sport Biomechanics Applications Using Inertial, Force, and EMG Sensors: A Literature Overview.Applied bionics and biomechanics · 2020Review
- Quantifying Human Movement Using the Movn Smartphone App: Validation and Field Study.JMIR mHealth and uHealth · 2017Article
- Estimation of Energy Expenditure Using a Patch-Type Sensor Module with an Incremental Radial Basis Function Neural Network.Sensors (Basel, Switzerland) · 2016Article
- Article
- Identifying typical physical activity on smartphone with varying positions and orientations.Biomedical engineering online · 2015Article
- Using Smartphone Sensors for Improving Energy Expenditure Estimation.IEEE journal of translational engineering in health and medicine · 2015Article
- Hierarchical Linear Models for Energy Prediction using Inertial Sensors: A Comparative Study for Treadmill Walking.Journal of ambient intelligence and humanized computing · 2013Article
- Intelligent predictor of energy expenditure with the use of patch-type sensor module.Sensors (Basel, Switzerland) · 2012Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
We describe an experimental study to estimate energy expenditure during treadmill walking using a single hip-mounted inertial sensor (triaxial accelerometer and triaxial gyroscope). Typical physical-activity characterization using commercial monitors use proprietary counts that do not have a physically interpretable meaning. This paper emphasizes the role of probabilistic techniques in conjunction with inertial data modeling to accurately predict energy expenditure for steady-state treadmill walking. We represent the cyclic nature of walking with a Fourier transform and show how to map this representation to energy expenditure (VO(2), mL/min) using three regression techniques. A comparative analysis of the accuracy of sensor streams in predicting energy expenditure reveals that using triaxial information leads to more accurate energy-expenditure prediction compared to only using one axis. Combining accelerometer and gyroscope information leads to improved accuracy compared to using either sensor alone. Nonlinear regression methods showed better prediction accuracy compared to linear methods but required an order of higher magnitude run time.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.