From Lab to Real World: Assessing the Effectiveness of Human Activity Recognition and Optimization through Personalization

From Lab to Real World: Assessing the Effectiveness of Human Activity Recognition and Optimization through Personalization

Human activity recognition (HAR) algorithms today are designed and evaluated on data collected in controlled settings, providing limited insights into their performance in real-world situations with noisy and missing sensor data and natural human activities. We present a real-world HAR open dataset...

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Bibliographic Details
Main Authors: Marija Stojchevska, Mathias De Brouwer, Martijn Courteaux, Femke Ongenae, Sofie Van Hoecke
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Sensors
Subjects:
human activity recognition
HAR
transfer learning
personalization
real-world data
convolutional neural networks
Online Access:https://www.mdpi.com/1424-8220/23/10/4606

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