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. 2022 Nov 14;8(11):e11517.
doi: 10.1016/j.heliyon.2022.e11517. eCollection 2022 Nov.

Dataset of lower extremity joint angles, moments and forces in distance running

Qichang Mei  1   2   3 , Justin Fernandez  1   2   3   4 , Liangliang Xiang  1   2   3 , Zixiang Gao  1   2   5 , Peimin Yu  1   2   3 , Julien S Baker  6 , Yaodong Gu  1   2   3
Affiliations

Dataset of lower extremity joint angles, moments and forces in distance running

Qichang Mei et al. Heliyon. .

Abstract

This study presents a database of joint angles, moments, and forces of the lower extremity from distance running at a submaximal speed in recreational runners. Twenty recreational runners participated in two experimental sessions, specifically pre and post a 5k treadmill run, with a synchronous collection of markers trajectories and ground reaction forces for both limbs in walking and running trials. The raw data in C3D files could be used for musculoskeletal modelling. Extra datasets of joint angles, moments, and forces are presented ready-for-use in MAT files, which could be as reference for study of biomechanical alterations from distance running. Applying advanced data processing techniques (Machine Learning algorithms) to these datasets ( C3D & MAT ), such as Principal Component Analysis, could extract key features of variation, thus potentially being applied for correlation with accelerometric and gyroscope parameters from wearable sensors during field running. Dataset of multi-segmental foot could be another contribution for the investigation of foot complex biomechanics from distance running. The dataset from Asian males may also be used for population-based studies of running biomechanics.

Keywords: Contact forces; Lower extremity; Principal component analysis; Running biomechanics; Statistical parametric mapping.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Outline of the experimental protocols (including Runners Recruitment, Data Collection during Pre 5k and Post 5k Sessions, and Data Application).
Figure 2
Figure 2
Illustration of marker-set (left & central) and multi-segmental foot model (right).
Figure 3
Figure 3
Raw Joint angles in the sagittal plane (left: a, ankle; d, knee; g, hip) and scores of 4 PCs (central: b, e, h) and percentage explanation (right: c, f, i) during pre 5k and post 5k walking of the right limb.
Figure 4
Figure 4
Raw Joint angles in the sagittal plane (left: a, ankle; d, knee; g, hip) and scores of 4 PCs (central: b, e, h) and percentage explanation (right: c, f, i) of left and right limb during pre 5k walking.
Figure 5
Figure 5
Raw Joint angles in the sagittal plane (left: a, ankle; d, knee; g, hip) and scores of 4 PCs (central: b, e, h) and percentage explanation (right: c, f, i) during pre 5k and post 5k running of the right limb.
Figure 6
Figure 6
Raw Joint angles in the sagittal plane (left: a, ankle; d, knee; g, hip) and scores of 4 PCs (central: b, e, h) and percentage explanation (right: c, f, i) of left and right limb during pre 5k running.
See this image and copyright information in PMC

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