First Name
Walid
Last Name
Gomaa
Affiliation
Egypt Japan University of Science and Technology
External links
Dataset Entries from this Author
The EJUST-ADL-2 dataset (HAD-AW) is a benchmark dataset for human activity recognition (HAR) using wearable inertial sensors. It contains multivariate time-series data collected from a smartwatch worn on the right wrist of 16 participants performing 31 activities of daily living (ADL) in realistic, unsupervised settings.
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EJUST-ADL-1 is a wearable-sensor dataset designed for human activity recognition (HAR) in the context of Activities of Daily Living (ADLs). The dataset is collected using a smartwatch worn on the wrist, capturing tri-axial inertial signals including acceleration, angular velocity, and rotational displacement. It comprises recordings from multiple volunteers performing 14 distinct motion primitives corresponding to common daily activities such as walking, eating, grooming, and transitioning between postures.
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Recognition of human activities is one of the most promising research areas in artificial intelligence. This has come along with the technological advancement in sensing technologies as well as the high demand for applications that are mobile, context-aware, and real-time. We have used a smart watch (Apple iWatch) to collect sensory data for 14 ADL activities (Activities of Daily Living).
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