TY - JOUR
T1 - A biomechanics and energetics dataset of neurotypical adults walking with and without kinematic constraints
AU - Baček, Tomislav
AU - Sun, Mingrui
AU - Liu, Hengchang
AU - Chen, Zhongxiang
AU - Manzie, Chris
AU - Burdet, Etienne
AU - Kulić, Dana
AU - Oetomo, Denny
AU - Tan, Ying
N1 - Funding Information:
The authors would like to thank Prof. Gavin Williams of the Epworth Hospital and the University of Melbourne, Prof. Jennifer McGinley of the Physiotherapy Department at the University of Melbourne, and Dr. Liuhua Peng, lecturer of the School of Mathematics and Statistics with the University of Melbourne for their expertise in designing the study. The authors would also like to express sincere gratitude to the 21 participants who volunteered their time and effort to participate in our study. Their contributions were invaluable and will be crucial in bettering our understanding of the underlying walking mechanisms. The authors thank them for their patience and cooperation throughout the study. Without their participation, this research would not have been possible.
Publisher Copyright:
© The Author(s) 2024.
PY - 2024/6/18
Y1 - 2024/6/18
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85196281772
U2 - 10.1038/s41597-024-03444-4
DO - 10.1038/s41597-024-03444-4
M3 - Article
C2 - 38890343
AN - SCOPUS:85196281772
SN - 2052-4463
VL - 11
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 646
ER -