Introducing a Human Activity Recognition Dataset Gathered on Real-Life Conditions

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http://hdl.handle.net/2183/34246
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Introducing a Human Activity Recognition Dataset Gathered on Real-Life ConditionsFecha
2023Resumen
[Abstract] Human activity recognition (HAR) has garnered significant scientific interest in recent
years. The widespread use of smartphones enabled convenient and cost-effective data collection,
eliminating the need for additional wearables. Given that, this paper introduces a novel HAR
dataset in which participants had freedom in choosing smartphone orientation and placement
during activities, ensuring data variability. It also includes contributions from diverse individuals,
reflecting unique smartphone usage habits. Moreover, it comprises measurements from
accelerometer, gyroscope, magnetometer, and GPS, corresponding to one of four activities: inactive,
active, walking, or driving. Unlike other datasets, the collected data in this study were
obtained from smartphones used in real-life scenarios
Palabras clave
Datos HAR
Smartphones
Dispositivos móviles
Smartphones
Dispositivos móviles
Descripción
Cursos e Congresos, C-155
Versión del editor
Derechos
Attribution 4.0 International (CC BY 4.0)