University of Campinas, Institute of Computing, Campinas, Brazil.
McGill, Music Tech, Montreal, Canada.
Sci Data. 2022 Sep 7;9(1):545. doi: 10.1038/s41597-022-01638-2.
Different technologies can acquire data for gait analysis, such as optical systems and inertial measurement units (IMUs). Each technology has its drawbacks and advantages, fitting best to particular applications. The presented multi-sensor human gait dataset comprises synchronized inertial and optical motion data from 25 participants free of lower-limb injuries, aged between 18 and 47 years. A smartphone and a custom micro-controlled device with an IMU were attached to one of the participant's legs to capture accelerometer and gyroscope data, and 42 reflexive markers were taped over the whole body to record three-dimensional trajectories. The trajectories and inertial measurements were simultaneously recorded and synchronized. Participants were instructed to walk on a straight-level walkway at their normal pace. Ten trials for each participant were recorded and pre-processed in each of two sessions, performed on different days. This dataset supports the comparison of gait parameters and properties of inertial and optical capture systems, whereas allows the study of gait characteristics specific for each system.
不同的技术可以获取步态分析数据，例如光学系统和惯性测量单元 (IMU)。每种技术都有其缺点和优点，最适合特定的应用。本研究提出的多传感器人体步态数据集包含 25 名无下肢损伤、年龄在 18 至 47 岁的参与者的同步惯性和光学运动数据。在参与者的一条腿上贴上智能手机和带有 IMU 的定制微控制器设备，以获取加速度计和陀螺仪数据，并在整个身体上贴上 42 个反射标记，以记录三维轨迹。轨迹和惯性测量同时记录并同步。参与者被要求以正常的步速在直道上行走。每个参与者在两次不同的会话中分别进行了 10 次试验记录和预处理。该数据集支持对步态参数和惯性与光学采集系统特性的比较，同时允许对每个系统特有的步态特征进行研究。
