A multi-sensor human gait dataset captured through an optical system and inertial measurement units

TL;DR

This paper introduces a comprehensive multi-sensor gait dataset combining optical and inertial data from 25 healthy subjects, enabling comparison and analysis of gait parameters across different capture technologies.

Contribution

It provides a synchronized multi-sensor dataset with optical and inertial data, facilitating gait analysis and comparison of capture system characteristics.

Findings

Dataset includes 25 subjects with 10 trials each

Data synchronization enables direct comparison of sensor modalities

Supports analysis of gait parameters specific to each system

Abstract

Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optical motion data from 25 subjects free of lower-limb injuries, aged between 18 and 47 years. A smartphone and a custom micro-controlled device with an IMU were attached to one of the subject's legs to capture accelerometer data, and 42 reflexive markers were taped over the whole body to record three-dimensional trajectories. The trajectories and accelerations were simultaneously recorded and synchronized. Participants were instructed to walk on a straight-level walkway at their normal pace. Ten trials for each participant were recorded and pre-processed in each of two sessions, performed on different days. This dataset supports the comparison of gait parameters and properties of inertial and optical capture systems, whereas allows the study of gait characteristics specific for each system.