Supporting data for "3D Printed Deformable Sensors"
2020-04-28
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2019-04-01
2020-04-01
2020-04-01
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2020-04-01
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Title
Supporting data for "3D Printed Deformable Sensors"
Published Date
2020-04-28
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Author Contact
McAlpine, Michael C
mcalpine@umn.edu
mcalpine@umn.edu
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Dataset
Experimental Data
Programming Software Code
Experimental Data
Programming Software Code
Abstract
The data set includes the experimental data and the corresponding code files supporting the results reported in Zhijie Zhu; Hyun Soo Park; Michael C. McAlpine. 3D Printed Deformable Sensors. Sci. Adv., 2020, DOI: 10.1126/sciadv.aba5575.
The ability to directly print compliant biomedical devices on live human organs could benefit patient monitoring and wound treatment, which requires the 3D printer to adapt to the various deformations of the biological surface. We developed an in situ 3D printing system that estimates the motion and deformation of the target surface to adapt the toolpath in real time. With this printing system, a hydrogel-based sensor was printed on a porcine lung under respiration-induced deformation. The sensor was compliant to the tissue surface and provided continuous spatial mapping of deformation via electrical impedance tomography. This adaptive 3D printing approach may enhance robot-assisted medical treatments with additive manufacturing capabilities, enabling autonomous and direct printing of wearable electronics and biological materials on and inside the human body.
Description
Full description in the file "ZhuReadme.txt".
Referenced by
Zhu Z., Park, H. S., and McAlpine, M. C. (2020). 3D Printed Deformable Sensors. Science Advances, 6(25).
https://doi.org/10.1126/sciadv.aba5575
https://doi.org/10.1126/sciadv.aba5575
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Funding information
National Institutes of Health, Grant 1DP2EB020537
Medtronic
The graduate school of the University of Minnesota, 2019-20 Doctoral Dissertation Fellowship
Medtronic
The graduate school of the University of Minnesota, 2019-20 Doctoral Dissertation Fellowship
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Suggested citation
Zhu, Zhijie; Park, Hyun Soo; McAlpine, Michael C. (2020). Supporting data for "3D Printed Deformable Sensors". Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/vqfp-vq57.
View/Download file
| File View/Open | Description | Size |
|---|---|---|
| Figure 2 data.rar | Raw data for Figure 2 | 19.97 MB |
| Figure 3 data_rev.tar.gz | Raw data for Figure 3 | 1.58 MB |
| Figure 4 data_rev.rar | Raw data for Figure 4 | 32.09 MB |
| Figure S1 data.rar | Raw data for Figure S1 | 29.26 KB |
| Figure S2 data.opj | Raw data for Figure S2 | 104.45 KB |
| Figure S3 data.opj | Raw data for Figure S3 | 840.55 KB |
| Figure S6 data.rar | Raw data for Figure S6 | 1.33 MB |
| Figure S7 data.rar | Raw data for Figure S7 | 3.96 MB |
| Figure S8 data.opj | Raw data for Figure S8 | 299.53 KB |
| Code files for adaptive printing controller_rev.rar | C++ Code Files for adaptive printing controller | 9.55 MB |
| Code files for EIT sensor operation_rev.rar | Code files for EIT sensor operation | 4.64 KB |
| ZhuReadme.txt | Read me file | 4.14 KB |
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