Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework

Wearable Sensor Data Classification for Human Activity Recognition Based on an Iterative Learning Framework

The design of multiple human activity recognition applications in areas such as healthcare, sports and safety relies on wearable sensor technologies. However, when making decisions based on the data acquired by such sensors in practical situations, several factors related to sensor data alignment, d...

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Bibliographic Details
Main Authors: Juan Carlos Davila, Ana-Maria Cretu, Marek Zaremba
Format: Article
Language:English
Published: MDPI AG 2017-06-01
Series:Sensors
Subjects:
large wearable sensor dataset
human locomotion
inertial measurement units
3-axial acceleration sensors
finite impulse response
wavelet filters
iterative classifier
SVM
multi-class classification
Online Access:http://www.mdpi.com/1424-8220/17/6/1287

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http://www.mdpi.com/1424-8220/17/6/1287

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