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

mHealth for Wellness, Behavior Change and Prevention (2871) Innovations and Technology for Physical Activity Education (742) Wearable Devices and Sensors (888)

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

Journals

  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

Books/Policy Documents

  1. Shukla A, Gupta P. Hybrid Materials for Piezoelectric Energy Harvesting and Conversion. View