Step-Wise Annotated Multi-Gait IMU Dataset from Smartphone, Smartwatch, and Earbuds

Dataset Overview:

This dataset contains step-wise annotated inertial measurement unit (IMU) data collected from three consumer-grade wearable devices: a smartphone, a smartwatch, and a pair of wireless earbuds. Participants performed walking, running, and stair-related activities in natural settings without constraint. The IMU signals include synchronized tri-axial accelerometer, gyroscope, and (in smartphones) magnetometer data, with manually annotated step-level labels identifying gait type and foot side (left/right).

Key Details:

- Participants: 16 (7 females, 9 males, average age 27.7)- Devices: iPhone 14, Apple Watch Series 10, AirPods Pro Gen 2- Sampling Rates: 100 Hz (phone/watch), 25 Hz (earbuds)- Smartphone Placements: Pocket, backpack, shoulder bag- Annotations: Manual per-step labels including gait type and foot side

Directory Structure:

Each participant folder (01 to 16) contains recordings under different smartphone placements:  pocket/    XX_data_pocket.csv    XX_groundTruth_pocket.csv  backpack/    XX_data_backpack.csv    XX_groundTruth_backpack.csv  shoulderBag/    XX_data_shoulderBag.csv    XX_groundTruth_shoulderBag.csv

Global files:- group_definition.txt: Defines gait labels (e.g., 1 = left foot walk, 8 = right foot run)- participant_age.csv: Lists participant age metadata

Applications:

This dataset supports research in gait segmentation, wearable computing, and human activity recognition. It can be used to evaluate multi-device fusion, analyze real-world motion signals, and develop gait-based health assessment tools.

Ethics:

All participants provided written informed consent. The study was approved by the appropriate institutional review board.

License:

Creative Commons Attribution 4.0 International (CC BY 4.0)

This dataset is part of an ongoing study currently under peer review.A related publication will be added here once available.