Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data

Application of machine learning to predict transport modes from GPS, accelerometer, and heart rate data

Abstract Background There has been an increased focus on active transport, but the measurement of active transport is still difficult and error-prone. Sensor data have been used to predict active transport. While heart rate data have very rarely been considered before, this study used random forests...

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Bibliographic Details
Main Authors: Santosh Giri, Ruben Brondeel, Tarik El Aarbaoui, Basile Chaix
Format: Article
Language:English
Published: BMC 2022-11-01
Series:International Journal of Health Geographics
Subjects:
Transport mode
Prediction models
Global Positioning System
Accelerometer
Heart rate
Machine Learning
Online Access:https://doi.org/10.1186/s12942-022-00319-y

Internet

https://doi.org/10.1186/s12942-022-00319-y

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