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

Reviews (296) Wearables and MHealth Reviews (709) Fitness Trackers and Smart Pedometers/Accelerometers (809) Machine Learning (3335)

Published on in Vol 15 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/76601, first published .
Silhouette of a runner with a digital overlay, representing data and technology in fitness.

Machine and Deep Learning for Detection of Moderate-to-Vigorous Physical Activity From Accelerometer Data: Systematic Scoping Review

Machine and Deep Learning for Detection of Moderate-to-Vigorous Physical Activity From Accelerometer Data: Systematic Scoping Review

Authors of this article:

Yahua Zi1 Author Orcid Image ;   Sjors RB van de Ven2 Author Orcid Image ;   Eco JC de Geus2 Author Orcid Image ;   Peijie Chen1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Srivastava P, Biswas S. Integrated Wearable Sensor Technologies for Real-Time Sports Performance Evaluation. Wireless Sensor Network 2026;18(02):23 View
  2. Doomen A, Felius R, Wittink H, Huijnen I, Punt M, Smeets R. An open-source deep learning model for classifying real-world activity intensities in persons with chronic pain using a wrist-worn accelerometer. Frontiers in Digital Health 2026;8 View