A Biomechanics and Energetics Dataset of Neurotypical Adults Walking with and Without Kinematic Constraints

Overview

Journal Sci Data

Specialty Science

Date 2024 Jun 18

PMID 38890343

Authors

Tomislav Bacek

Mingrui Sun

Hengchang Liu

Zhongxiang Chen

Chris Manzie

Etienne Burdet

Dana Kulic

Denny Oetomo

Ying Tan

Affiliations

Soon will be listed here.

Abstract

Numerous studies have explored the biomechanics and energetics of human walking, offering valuable insights into how we walk. However, prior studies focused on changing external factors (e.g., walking speed) and examined group averages and trends rather than individual adaptations in the presence of internal constraints (e.g., injury-related muscle weakness). To address this gap, this paper presents an open dataset of human walking biomechanics and energetics collected from 21 neurotypical young adults. To investigate the effects of internal constraints (reduced joint range of motion), the participants are both the control group (free walking) and the intervention group (constrained walking - left knee fully extended using a passive orthosis). Each subject walked on a dual-belt treadmill at three speeds (0.4, 0.8, and 1.1 m/s) and five step frequencies ( - 10% to 20% of their preferred frequency) for a total of 30 test conditions. The dataset includes raw and segmented data featuring ground reaction forces, joint motion, muscle activity, and metabolic data. Additionally, a sample code is provided for basic data manipulation and visualisation.

Citing Articles

A biomechanics and energetics dataset of neurotypical adults walking with and without kinematic constraints.

Bacek T, Sun M, Liu H, Chen Z, Manzie C, Burdet E Sci Data. 2024; 11(1):646.

PMID: 38890343 PMC: 11189391. DOI: 10.1038/s41597-024-03444-4.

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