ArticleScientific reports2024
Performance of Microsoft Azure Kinect DK as a tool for estimating human body segment lengths.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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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.
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Who cites it
6 citing papers in PubMed.
- Comparison of hip and knee range of motion measurements using Azure Kinect and a digital goniometer in elite female weightlifters.Scientific reports · 2026Article
- Analysis of anthropometric measurements in U-15 female weightlifters using Kinect camera and comparison with traditional methods.Medical & biological engineering & computing · 2025Article
- Operatic Singing Biomechanics: Skeletal Tracking Sensor Integration for Pedagogical Innovation.Sensors (Basel, Switzerland) · 2025Article
- Photogrammetry in Spinal Assessment: A Comparative Analysis with Traditional Clinical Methods.Journal of clinical medicine · 2025Article
- Kinect-based anthropometric measurements: a comparative analysis of traditional methods in youth female weightlifters.BMC sports science, medicine & rehabilitation · 2025Article
- Azure Kinect for joint range of motion analysis: A validity and reliability evaluation in elite female weightlifters.PloS one · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The Microsoft Kinect depth sensor, with its built-in software that automatically captures joint coordinates without markers, could be a potential tool for ergonomic studies. This study investigates the performance of Kinect in limb segment lengths using dual-energy X-ray absorptiometry (DXA) as a reference. Healthy children and adults (n = 76) were recruited for limb length measurements by Kinect and DXA. The results showed consistent ratios of arm, forearm, thigh, and leg lengths to height, which were 0.16, 0.14, 0.23, and 0.22 respectively, for both age groups and methods. Kinect exhibited perfect correlation among all limb lengths, indicating fixed proportions assumed by its algorithm. Comparing the two methods, there was a strong correlation (R = 0.850-0.985) and good to excellent agreement (ICC = 0.829-0.977), except for the right leg in adults, where agreement was slightly lower but still moderate (ICC = 0.712). The measurement bias between the methods ranged from - 1.455 to 0.536 cm. In conclusion, Kinect yields outcomes similar to DXA, indicating its potential utility as a tool for ergonomic studies. However, the built-in algorithm of Kinect assumes fixed limb proportions for individuals, which may not be ideal for studies focusing on investigating limb discrepancies or anatomical differences.
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Registered trials
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