NONAN GaitPrint: An IMU gait database of healthy older adults

The continued effort to study gait kinematics and the increased interest in identifying individuals based on their gait patterns, could be strengthened by the inclusion of data from older groups. To address this need and complement our previous database on healthy young adults, we present an addition to the Nonlinear Analysis Core (NONAN) GaitPrint database. We offer full-body inertial measurement data during self-paced overground walking on a 200 m indoor track of 41 older adults (56+ years old; 20 men and 21 women; age: 64.7 ± 7.5 years; height: 1.7 ± 0.1 m; body mass: 81.1 ± 17.8 kg) across 18 four-minute trials conducted over two days. The multiple recordings are supported by a range of pre-calculated spatiotemporal variables, a list of each subject’s anthropometrics, notes for each walking trial, and template scripts for easier application of our data to classroom assignments or laboratory research. In addition, a preliminary Bayesian analysis found a range of evidence supporting age-related gait changes between this database and our database on young adults.

当前针对步态运动学（gait kinematics）的持续研究，以及基于步态模式开展个体识别的研究兴趣日益增长，而纳入老年人群体的数据可进一步强化这两大研究方向的推进。为满足这一研究需求并补充我们此前针对健康青年群体构建的数据库，我们对非线性分析核心（Nonlinear Analysis Core, NONAN）GaitPrint数据库进行了扩展。本数据集包含41名老年受试者（56岁及以上，其中男性20名、女性21名，年龄为64.7±7.5岁，身高1.7±0.1m，体质量81.1±17.8kg）在200米室内跑道上自定步速平地行走时采集的全身惯性测量数据，相关测试共开展18次时长4分钟的行走试验，分两天完成。本次多组测试数据配套提供了一系列预计算的时空参数、每位受试者的人体测量学参数清单、每一次行走测试的备注文档，以及便于将本数据集应用于课堂作业或实验室研究的模板脚本。此外，一项初步贝叶斯分析结果显示，相较于我们此前的青年群体步态数据库，本数据集存在多项支持年龄相关步态差异的证据。