Posture Classification Data from Capacitive Chair Cover

A dataset containing sensor readings from an aluminium-foil capacitive chair cover designed to detect sitting posture. The data includes labeled states for Good Posture, Slouching, and an Empty chair. The author, organization, and collection details are unknown.

Use Cases

• Classify 'Good Posture' vs. 'Slouching' states from capacitive sensor time-series data.
• Train a model to detect an 'Empty' chair state for occupancy sensing applications.
• Analyze temporal patterns in the capacitive readings to identify posture transition events.

Strengths

• Data includes three distinct, labeled classes: Good Posture, Slouching, and Empty.
• Sensor data originates from a specific, described hardware setup: an aluminium-foil capacitive chair cover.

Limitations

• The sample size, number of rows, and feature count are unknown, limiting assessment of statistical power.
• No information on data collection environment, participant demographics, or potential sensor noise is provided.

Provenance

Source

Kaggle user 'unknown'.

Collection Method

Collected via a custom aluminium-foil capacitive chair cover sensor.