Harvard Dataverse hosts a dataset associated with a study comparing functional mobility kinematics and perceived cognitive load between adults with visual impairment and sighted controls. The data includes kinematic variables derived from a smartphone inertial sensor and assessments of cognitive load using an adapted NASA Task Load Index (NASA-TLX). The dataset was last updated on May 12, 2026.
Use Cases
- Compare kinematic gait patterns between visually impaired and sighted individuals based on inertial sensor data.
- Model the relationship between cognitive load and mobility performance under varying visual conditions.
- Validate assessment tools like the NASA-TLX for use with visually impaired populations.
- Train machine learning classifiers to detect mobility difficulty or cognitive demand from sensor-derived features.
Strengths
- Dataset is directly associated with a peer-reviewed manuscript, suggesting a research-grade collection.
- Includes data from both a visually impaired population and a sighted control group for comparative analysis.
- Combines objective kinematic measurements from an inertial sensor with subjective cognitive load assessments.
Limitations
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment for large-scale modeling.
Provenance
- Source
- Harvard Dataverse
- Collection Method
- Data gathered from a study investigating the effects of modifying visual and cognitive demands on functional mobility.
- Freshness
- Last updated 2026-05-12 16:31:19; freshness should be verified.