Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters

Abstract

Many biomechanical and medical analyses rely on the availability of reliable body segment parameter estimates. Current techniques typically take many manual measurements of the human body, in conjunction with geometric models or regression equations. However, such techniques are often criticised. 3D scanning offers many advantages, but current systems are prohibitively complex and costly. The recent interest in natural user interaction (NUI) has led to the development of low cost (~£200) sensors capable of 3D body scanning, however, there has been little consideration of their validity. A scanning system comprising four Microsoft Kinect sensors (a typical NUI sensor) was used to scan twelve living male participants three times. Volume estimates from the system were compared to those from a geometric modelling technique. Results demonstrated high reliability (ICC>0.7, TEM<1 %) and presence of a systematic measurement offset (0.001m $^{3}$ ), suggesting the system would be well received by healthcare and sports communities.

Cite

Text

Clarkson et al. "Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters." European Conference on Computer Vision Workshops, 2014. doi:10.1007/978-3-319-16178-5_26

Markdown

[Clarkson et al. "Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters." European Conference on Computer Vision Workshops, 2014.](https://mlanthology.org/eccvw/2014/clarkson2014eccvw-assessing/) doi:10.1007/978-3-319-16178-5_26

BibTeX

@inproceedings{clarkson2014eccvw-assessing,
  title     = {{Assessing the Suitability of the Microsoft Kinect for Calculating Person Specific Body Segment Parameters}},
  author    = {Clarkson, Sean and Wheat, Jon and Heller, Ben W. and Choppin, Simon},
  booktitle = {European Conference on Computer Vision Workshops},
  year      = {2014},
  pages     = {372-385},
  doi       = {10.1007/978-3-319-16178-5_26},
  url       = {https://mlanthology.org/eccvw/2014/clarkson2014eccvw-assessing/}
}