Database (splitted 1/9)

The database presented here provides recordings of everyday walk scenarios in a natural urban environment, including synchronized IMU-, FSR-, and gaze data. Twenty healthy participants (five females, fifteen males, between 18 and 69 years old, 178.5 $\pm$ 7.64 cm, 72.9 $\pm$ 8.7 kg) wore a full-body Lycra suit with 17 IMU sensors, insoles with eight pressure sensing cells per foot, and a mobile eye tracker. They completed three different walk courses, where each trial consisted of several minutes of walking, including a variety of common elements such as ramps, stairs, and pavements. The data is annotated in detail to enable machine-learning-based analysis and prediction.

本数据集提供了自然城市环境中日常步行场景的同步录制数据，涵盖同步采集的惯性测量单元（Inertial Measurement Unit, IMU）、力敏电阻（Force Sensitive Resistor, FSR）及视线数据。20名健康受试者（5名女性、15名男性，年龄介于18至69岁，身高178.5±7.64 cm，体重72.9±8.7 kg）身着搭载17个IMU传感器的全身莱卡（Lycra）紧身服、每只脚内置8个压力感应单元的鞋垫，以及移动式眼动追踪设备。受试者完成3条不同的步行路线，每次试验包含数分钟的步行过程，涵盖坡道、楼梯、人行道等各类常见路况。本数据集已完成详尽标注，可支持基于机器学习的分析与预测研究。