Human Fatigue and Recovery Data from Controlled Order-Picking Experiments

3.6 GB of sensor data collected during a controlled laboratory experiment investigating human fatigue development during repetitive order-picking tasks. The dataset includes timestamped wearable sensor measurements, Rating of Perceived Exertion (RPE), activity labels, and participant anthropometric data. It was authored by Setareh Kazemi Kheiri and last updated on June 1, 2026.

Use Cases

• Modeling human fatigue development based on sensor data and Rating of Perceived Exertion.
• Analyzing the impact of workload and work pace on performance and recovery.
• Training machine learning models for activity recognition from body-mounted sensor streams.
• Developing human-centered digital twins for ergonomic assessment of manual tasks.

Strengths

• Data volume is 3.6 GB, indicating a substantial collection of sensor readings.
• Includes multiple data types: time-series sensor data, anthropometric details, and controlled experiment settings.
• Data was collected under controlled laboratory conditions with varying workload and pace parameters.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to a controlled lab experiment rather than real-world field conditions.

Provenance

Source

Setareh Kazemi Kheiri via figshare

Collection Method

Collected during a controlled laboratory experiment where participants performed order-picking tasks under different workload and pace conditions while wearing body-mounted sensors.

Freshness

Last updated 2026-06-01 19:29:08