Dense 3D pressure discomfort threshold (PDT) map of the human head, face and neck [Dataset]
doi:10.4121/21482328.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/21482328
doi: 10.4121/21482328
Datacite citation style:
Smulders, Maxim; van Dijk, Lisanne N.M.; Song, Yu; Vink, Peter; Huysmans, Toon (2022): Dense 3D pressure discomfort threshold (PDT) map of the human head, face and neck [Dataset]. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/21482328.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
This dataset contains a dense 3D pressure discomfort threshold (PDT) map of the human head, face and neck of a mixed population (n=28), mapped on an average head model of all the participants. Datasets on nonNormalised and Normalised are available.
To aid designers and engineers, this PDT is also mapped on the human head Statistical Shape Model (SSM) (from Principal Component 1 to PC50, ±3σ) built on the CAESAR 3D Anthropometric Database (USA, Italy and The Netherlands, male and female, 18-65y, n=4309).
Files are available as *.vtk for further analysis, and as *.obj for further use as reference models for design engineering in e.g. CAD.
history
- 2022-11-15 first online, published, posted
publisher
4TU.ResearchData
format
*.csv; *.obj; *.pdf; *.vtk
associated peer-reviewed publication
Dense 3D pressure discomfort threshold (PDT) map of the human head, face and neck: a new method for mapping human sensitivity
funding
- Crescent Med
- Dutch Research Council (NWO) project number 18636
organizations
Delft University of Technology, Faculty of Industrial Design Engineering;Crescent Medical B.V.;
University of Antwerp, Department of Physics, Imec-Vision Lab
DATA
files (12)
- 42,407,795 bytesMD5:
b51627bd74820d7fcf24c893f6a4d67a
README.pdf - 22,868,981 bytesMD5:
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Smulders (2022) CAESAR PDT_Mean_nonNorm.csv - 29,240,366 bytesMD5:
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Smulders (2022) CAESAR PDT_Mean_nonNorm.vtk - 22,870,884 bytesMD5:
bb43484e6847e703126159414b3e0d10
Smulders (2022) CAESAR PDT_Mean_Norm.csv - 29,241,248 bytesMD5:
92598d0b14d852c8a45d3cadd9f0d33d
Smulders (2022) CAESAR PDT_Mean_Norm.vtk - 15,229,823 bytesMD5:
0988405ec9cab0d8f7a55cf8035e5372
Smulders (2022) OBJ PDT_maps.zip - 442,926 bytesMD5:
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Smulders (2022) Original PDT_data.zip - 812 bytesMD5:
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Smulders (2022) Participant_characteristics.csv - 2,423,461 bytesMD5:
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Smulders (2022) TUDELFT PDT_Mean_nonNorm.csv - 4,722,385 bytesMD5:
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Smulders (2022) TUDELFT PDT_Mean_nonNorm.vtk - 2,428,007 bytesMD5:
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Smulders (2022) TUDELFT PDT_Mean_Norm.csv - 4,732,621 bytesMD5:
188d602e077f1bb4ef57966acdf43504
Smulders (2022) TUDELFT PDT_Mean_Norm.vtk -
download all files (zip)
176,609,309 bytes unzipped