16 volunteers aged 19-26 recorded movement data across five activity classes including WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, and STANDING. The dataset captures motion signals using the embedded accelerometer and gyroscope of a Samsung Galaxy S8 smartphone carried in the pocket.
Use Cases
- Train a classification model to distinguish between static and dynamic activities using the accelerometer and gyroscope signals
- Develop an elevation detection algorithm to differentiate between WALKING_UPSTAIRS and WALKING_DOWNSTAIRS labels
- Analyze movement patterns specific to the 19-26 age demographic using the volunteer metadata
Strengths
- Includes motion data for 5 activity classes: WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, and STANDING
- Features sensor readings from both an embedded accelerometer and a gyroscope
- Data collected from 16 unique volunteers within a specific age bracket of 19-26 years
- Recorded using a standardized device placement with a Samsung Galaxy S8 in the pocket