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<p>The diagnosis and rehabilitation assessment of hip disorders require high-quality data that can reflect the true range of joint motion. However, most existing public datasets focus on gait scenarios, have limited angle coverage, and lack time-aligned joint angle and action labels. Therefore, we constructed and released the Hip-ROM-Y dataset, which includes 16 healthy male participants performing 6 characteristic hip ROM actions across 3 anatomical planes. During data collection, 8 wearable inertial measurement units (IMUs) were used to record acceleration, angular velocity, and orientation-related signals. An optical motion capture system was used to build a lower-limb kinematic model based on reflective skin markers and to calculate reference hip joint angle labels. In addition, action categories were annotated frame by frame by annotators, providing both action labels and joint angle labels. The dataset was then systematically validated in terms of angle coverage and cross-subject modeling usability. The open release of Hip-ROM-Y provides a new benchmark data resource for joint kinematics research, rehabilitation assessment, and wearable device development.</p>

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Hip-ROM-Y: An open IMU and motion capture dataset for hip joint range-of-motion analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月20日

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  • Jinan Dong,
  • Jianxin Liu,
  • Ziming Chen,
  • Dejin Yang,
  • Xiangyun Yin

摘要

The diagnosis and rehabilitation assessment of hip disorders require high-quality data that can reflect the true range of joint motion. However, most existing public datasets focus on gait scenarios, have limited angle coverage, and lack time-aligned joint angle and action labels. Therefore, we constructed and released the Hip-ROM-Y dataset, which includes 16 healthy male participants performing 6 characteristic hip ROM actions across 3 anatomical planes. During data collection, 8 wearable inertial measurement units (IMUs) were used to record acceleration, angular velocity, and orientation-related signals. An optical motion capture system was used to build a lower-limb kinematic model based on reflective skin markers and to calculate reference hip joint angle labels. In addition, action categories were annotated frame by frame by annotators, providing both action labels and joint angle labels. The dataset was then systematically validated in terms of angle coverage and cross-subject modeling usability. The open release of Hip-ROM-Y provides a new benchmark data resource for joint kinematics research, rehabilitation assessment, and wearable device development.