IoMT: Human Activity Recognition (HAR) via Wearables
Catalog Summary
"Inertial sensor data (Accelerometer/Gyroscope) for detecting human activities like walking, sitting, and standing for health monitoring."
Catalog Notes
This dataset tracks the movement of 30 volunteers wearing smartphones with embedded inertial sensors. It is a benchmark for Internet of Medical Things (IoMT) device development.
Sensor Data:
- Triaxial Acceleration: Total acceleration from the accelerometer.
- Triaxial Angular Velocity: Readings from the gyroscope.
- Feature Vector: 561 features with time and frequency domain variables.
ML Applications:
Ideal for Deep Learning (CNN/LSTM) classification tasks to identify physical health patterns and elderly fall detection.
Source: Smartlab - Non-Conventional Robotics and Artificial Intelligence.
View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on External.
Preview on ExternalCite This Catalog Record
IoTDataset.com (2026). IoMT: Human Activity Recognition (HAR) via Wearables — catalog record. [Dataset]. IoTDataset.com. https://iotdataset.com/data/human-activity-recognition-wearables
The publisher's preferred dataset citation is not recorded. The text above cites this IoTDataset.com catalog record, not the underlying dataset.
Catalog publisher: IoTDataset.com (2026)
Indexed by IoTDataset.com on Jan 06, 2026
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