Prosthetics & Assistive DevicesAssistive devicesSupplemental record

Low-cost sensor-integrated 3D-printed personalized prosthetic hands for children with amniotic band syndrome: A case study in sensing pressure distribution on an anatomical human-machine interface (AHMI) using 3D-printed conformal electrode arrays

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Matched by doi · retrieved 2026-07-21

Abstract

Interfacing anatomically conformal electronic components, such as sensors, with biology is central to the creation of next-generation wearable systems for health care and human augmentation applications. Thus, there is a need to establish computer-aided design and manufacturing methods for producing personalized anatomically conformal systems, such as wearable devices and human-machine interfaces (HMIs). Here, we show that a three-dimensional (3D) scanning and 3D printing process enabled the design and fabrication of a sensor-integrated anatomical human-machine interface (AHMI) in the form of personalized prosthetic hands that contain anatomically conformal electrode arrays for children affected by amniotic band syndrome, a common birth defect. A methodology for identifying optimal scanning parameters was identified based on local and global metrics of registered point cloud data quality. This method identified an optimal rotational angle step size between adjacent 3D scans. The sensitivity of the optimization process to variations in organic shape (i.e., geometry) was examined by testing other anatomical structures, including a foot, an ear, and a porcine kidney. We found that personalization of the prosthetic interface increased the tissue-prosthesis contact area by 408% relative to the non-personalized devices. Conformal 3D printing of carbon nanotube-based polymer inks across the personalized AHMI facilitated the integration of electronic components, specifically, conformal sensor arrays for measuring the pressure distribution across the AHMI (i.e., the tissue-prosthesis interface). We found that the pressure across the AHMI exhibited a non-uniform distribution and became redistributed upon activation of the prosthetic hand's grasping action. Overall, this work shows that the integration of 3D scanning and 3D printing processes offers the ability to design and fabricate wearable systems that contain sensor-integrated AHMIs.

Bibliographic details

Published
2019-03-28
Journal/source
PLOS ONE
Publisher
Public Library of Science (PLoS)
DOI
10.1371/journal.pone.0214120
Type
journal-article
Language
en
Volume / issue
14 / 3
Pages
e0214120
ISSN
1932-6203

Access and metrics

Open access
Yes
OA status
gold
License
cc-by
Version
publishedVersion
Cited by
37
References
75
Retracted
No

Authors and affiliations

  1. Yuxin TongVirginia Tech
  2. Ezgi KüçükdeğerVirginia Tech
  3. Justin HalperVirginia Tech
  4. Ellen CesewskiVirginia Tech
  5. Elena KarakozoffVirginia Tech
  6. Alexander P. HaringVirginia Tech
  7. David McIlvainVirginia Tech
  8. Manjot SinghVirginia Tech
  9. Nikita KhandelwalVirginia Tech
  10. Alex MeholicVirginia Tech
  11. Sahil LaheriVirginia Tech
  12. Akshay SharmaVirginia Tech
  13. Blake N. JohnsonCorresponding authorVirginia Tech

Topics and keywords

Advanced Sensor and Energy Harvesting MaterialsTracheal and airway disordersTissue Engineering and Regenerative MedicineInterfacingComputer scienceInterface (matter)Wearable computerPressure sensorBiomedical engineering3D printingComputer hardwareEmbedded systemMechanical engineeringEngineering

Funding

  • Virginia Polytechnic Institute and State University · SEC-2018
  • Virginia Polytechnic Institute and State University · ICAT-2018
  • National Science Foundation · DUE-1644138