TY - JOUR
T1 - Dataset of lower extremity joint angles, moments and forces in distance running
AU - Mei, Qichang
AU - Fernandez, Justin
AU - Xiang, Liangliang
AU - Gao, Zixiang
AU - Yu, Peimin
AU - Baker, Julien S.
AU - Gu, Yaodong
N1 - This study was sponsored by National Natural Science Foundation of China (No. 12202216), NSFC (Natural Science Foundation of China) - RSE (The Royal Society of Edinburgh) Joint Project (No. 81911530253) and K. C. Wong Magna Fund in Ningbo University. QM of this paper was supported by the New Zealand-China Doctoral Research Scholarship issued from the Ministry of Foreign Affairs and Trade (New Zealand). LX, ZG and PM are currently supported by the China Scholarship Council (CSC).
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/11
Y1 - 2022/11
N2 - 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.
AB - 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.
KW - Running biomechanics
KW - Lower extremity
KW - Contact forces
KW - Principal component analysis
KW - Statistical parametric mapping
UR - http://www.scopus.com/inward/record.url?scp=85143285243&partnerID=8YFLogxK
UR - https://www.sciencedirect.com/science/article/pii/S2405844022028055?via%3Dihub
U2 - 10.1016/j.heliyon.2022.e11517
DO - 10.1016/j.heliyon.2022.e11517
M3 - Journal article
AN - SCOPUS:85143285243
SN - 2405-8440
VL - 8
JO - Heliyon
JF - Heliyon
IS - 11
M1 - e11517
ER -