Boo Junyo, Seo Dongwook, Kim Minseung, Koo Seungbum
Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
Sci Data. 2025 Jun 18;12(1):1023. doi: 10.1038/s41597-025-05391-0.
Understanding human locomotion patterns and their variations requires comprehensive data across different age groups and movement tasks, given the complexity of the human musculoskeletal system. This study presents a dataset of human locomotion during daily activities, collected from 120 healthy male participants (age range: 20-59 years). The experimental protocol included seven distinct tasks: level walking, stair ascent/descent, slope walking (ascent/descent), and sit-to-stand/stand-to-sit movements. Data were collected using an optical motion capture system, force plates, and surface electromyography sensors on the right lower limb. The final dataset includes 6,882 movement cycles across all tasks, including full-body joint kinematics and muscle activity patterns. This comprehensive dataset will contribute to understanding the variations in movement patterns and muscle activation during common daily activities across a broad adult male population.
鉴于人类肌肉骨骼系统的复杂性，了解人类的运动模式及其变化需要不同年龄组和运动任务的全面数据。本研究展示了一个日常活动中人类运动的数据集，该数据集来自120名健康男性参与者（年龄范围：20 - 59岁）。实验方案包括七个不同的任务：平地行走、上下楼梯、斜坡行走（上坡/下坡）以及坐立/立坐动作。使用光学运动捕捉系统、测力板和右下肢表面肌电图传感器收集数据。最终数据集包括所有任务的6882个运动周期，涵盖全身关节运动学和肌肉活动模式。这个全面的数据集将有助于理解广大成年男性群体在日常常见活动中的运动模式变化和肌肉激活情况。
