ArticleScientific data2026
A Wearable Motion Capture Dataset for Gait Analysis Using IMUs and Shank-Mounted Egocentric Cameras.
Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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
1 citing paper in PubMed.
- A Wearable Motion Capture Dataset for Gait Analysis Using IMUs and Shank-Mounted Egocentric Cameras.Scientific data · 2026Article
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Walking kinematics offer critical insights into human gait, enabling clinicians to assess motor function, diagnose impairments, and monitor rehabilitation progress. With the rise of machine learning, wearable sensors are increasingly used to estimate joint kinematics. To advance these fields, we introduce a dataset comprising 14 walking trials performed by 10 healthy participants across various speeds and trial types on overground, treadmill, slope, and stair locomotion modes. The dataset includes inertial measurement unit (IMU) data and shank-mounted egocentric video, synchronized with joint kinematics derived from optical motion capture and musculoskeletal modeling. It provides 327 minutes of recordings, including IMU signals, motion capture marker trajectories, joint angles, and 588k egocentric video frames per foot with corresponding histogram of optical flow (HOF) features. To the best of our knowledge, this is the first dataset offering multimodal wearable IMU and shank-mounted video data with ground-truth joint kinematics across a wide range of walking tasks. This dataset is intended to support a wide range of applications in both biomechanics and machine learning research.
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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.