A multi-sensor gait dataset collected under non-standardized dual-task conditions

Non-standardized dual-tasks have recently gained attention in health monitoring and post-operative rehabilitation. By collecting data with multiple sensors, we can quantify motion characteristics from different perspectives and explore the complementarity and interchangeability between sensors. Currently, there is a lack of publicly available non-standardized dual-task gait datasets collected with multiple sensors, thus we proposed a dataset (NONSD-Gait) from 23 healthy adults walking back and forth over 7 meters under three dual-task conditions, collected by three types of sensors: optical motion capture (MOCAP) system, depth camera and inertial measurement unit (IMU). MoCap captured the 3D trajectories of 22 markers attached to the subject using 8 optical cameras, while the depth camera recorded the 3D trajectories of 25 joints through a non-contact depth camera. The IMU was placed on the left ankle to record 3-axis acceleration and angular velocity data. Each participant underwent tw..., This study recruited 23 healthy adults aged between 21 and 30 years old (9 males, 14 females). All participants had no neuromuscular diseases or skeletal injuries, and without any hearing or vision impairment. In the experiment, participants were required to walk back and forth on a 7m × 1m mat under a single-task condition and three non-standardized dual-task conditions. This study utilized eight MOCAP cameras (NOKOV MARS 2H HD cameras, 100Hz, resolution 2048 × 1088), one depth camera (Microsoft Kinect V2.0, 30Hz, resolution 512 × 424), and one inertial sensor (Witmotion BWT901BLECL5.0C, 100Hz) for data collection.
 
For the walking data from each task recorded by MOCAP, 22 reflective markers  were firstly labeled using  MOCAP's software and the 3D trajectories of the markers were then exported. The data collected by IMU were exported using IMU's software, and the data collected by Kinect were exported using its proprietary SDK. The data collected by the three sensors we..., , # A multi-sensor gait dataset collected under non-standardized dual-task conditions

[https://doi.org/10.5061/dryad.2rbnzs7z3](https://doi.org/10.5061/dryad.2rbnzs7z3)

## Description of the data and file structure

### File: Data.zip

### **Description:**

* The **\"Raw\"** folder contains the complete experimental data collected by the three sensors.
* The **\"Processed\"** folder includes segmented data from the three sensors.
* The **\"Parameters\"** folder contains the spatio-temporal gait parameters and kinematic parameters extracted separately by the three sensors.
* The demographic information of the subjects is stored in a file named **Demographics.csv. **All participants signed informed consent and agreed to the open publication of the data. This study does not involve sensitive data.

Each participant’s folder is named: **sampleID**, with ID ranging from 01 to 23.

The folders for the two repeated experiments are named with **timeID**, with ID ranging from 1 to 2.

The tasks are na...,