This paper is in the following e-collection/theme issue:

mHealth for Wellness, Behavior Change and Prevention (2754) Innovations and Technology for Physical Activity Education (703) Wearable Devices and Sensors (825)

Published on in Vol 7, No 10 (2019): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12335, first published .
Predicting Energy Expenditure During Gradient Walking With a Foot Monitoring Device: Model-Based Approach

Predicting Energy Expenditure During Gradient Walking With a Foot Monitoring Device: Model-Based Approach

Predicting Energy Expenditure During Gradient Walking With a Foot Monitoring Device: Model-Based Approach

Authors of this article:

Soon Ho Kim1 Author Orcid Image ;   Jong Won Kim2 Author Orcid Image ;   Jung-Jun Park3 Author Orcid Image ;   Myung Jun Shin4 Author Orcid Image ;   MooYoung Choi1 Author Orcid Image
Article Authors Cited by (4) Tweetations (1) Metrics

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  1. Seo M, Shin M, Park T, Park J. Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study. JMIR mHealth and uHealth 2020;8(9):e22208 View
  2. Kim S, Kim J, Chung H, Choi M. A least action principle for interceptive walking. Scientific Reports 2021;11(1) View
  3. Perrett T, Masullo A, Damen D, Burghardt T, Craddock I, Mirmehdi M. Personalized Energy Expenditure Estimation: Visual Sensing Approach With Deep Learning. JMIR Formative Research 2022;6(9):e33606 View

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