ArticleScientific data2022
The Toronto older adults gait archive: video and 3D inertial motion capture data of older adults' walking.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- Markerless Motion Capture Parameters Associated with Fall Risk or Frailty: A Scoping Review.Sensors (Basel, Switzerland) · 2025Article
- DIODEM - A Diverse Inertial and Optical Dataset of kinEmatic chain Motion.Scientific data · 2025Article
- A Full-Body IMU-Based Motion Dataset of Daily Tasks by Older and Younger Adults.Scientific data · 2025Article
- Gait stability prediction through synthetic time-series and vision-based data.Frontiers in sports and active living · 2025Article
- Article
- A database with frailty, functional and inertial gait metrics for the research of fall causes in older adults.Scientific data · 2023Article
- The Toronto older adults gait archive: video and 3D inertial motion capture data of older adults' walking.Scientific data · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We introduce the Toronto Older Adults Gait Archive, a gait dataset of 14 older adults containing 2D video recordings, and 2D (video pose tracking algorithms) and 3D (inertial motion capture) joint locations of the lower body. Participants walked for 60 seconds. We also collected participants' scores on four clinical assessments of gait and balance, namely the Tinneti performance-oriented mobility assessment (POMA-gait and -balance), the Berg balance scale (BBS), and the timed-up-and-go (TUG). Three human pose tracking models (Alphapose, OpenPose, and Detectron) were used to detect body joint positions in 2D video frames and a number of gait parameters were computed using 2D video-based and 3D motion capture data. To show an example usage of our datasets, we performed a correlation analysis between the gait variables and the clinical scores. Our findings revealed that the temporal but not the spatial or variability gait variables from both systems had high correlations to clinical scores. This dataset can be used to evaluate, or to enhance vision-based pose-tracking models to the specifics of older adults' walking.
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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.