ArticleScientific data2025
A Multi-sensor Gait Dataset Collected Under Non-standardized Dual-Task Conditions.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026Review
- A Multi-sensor Gait Dataset Collected Under Non-standardized Dual-Task Conditions.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Non-standardized dual-tasks have recently gained attention in gait analysis. Currently, there is a lack of publicly available non-standardized dual-task gait datasets collected with multiple sensors. To fill this gap, we present a dataset (NONSD-Gait) consisting of back and forth 7 m walks under three non-standardized dual-task conditions (texting, browsing the web, and holding a cup) from 23 healthy adults. These data were collected simultaneously by three common types of sensors: an optical motion capture (MOCAP) system, a depth camera and an inertial measurement unit (IMU). MOCAP captured the 3D trajectories of 22 markers using 8 optical cameras, while the depth camera recorded the 3D trajectories of 25 joints. The IMU was placed on the left ankle to record acceleration and angular velocity data. Moreover, we extracted 10 spatio-temporal gait parameters and 168 kinematic parameters. This dataset enables gait analysis under non-standardized dual-task conditions, supporting research on rehabilitation training for cognitive and motor impairments. Additionally, it facilitates cross-device comparisons, facilitating the exploration of low-cost sensor alternatives.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.