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Sensor Architectures and Technologies for Upper Limb 3D Surface Reconstruction: A Review

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2020 Nov 21
PMID 33217994
Citations 2
Authors
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Abstract

3D digital models of the upper limb anatomy represent the starting point for the design process of bespoke devices, such as orthoses and prostheses, which can be modeled on the actual patient's anatomy by using CAD (Computer Aided Design) tools. The ongoing research on optical scanning methodologies has allowed the development of technologies that allow the surface reconstruction of the upper limb anatomy through procedures characterized by minimum discomfort for the patient. However, the 3D optical scanning of upper limbs is a complex task that requires solving problematic aspects, such as the difficulty of keeping the hand in a stable position and the presence of artefacts due to involuntary movements. Scientific literature, indeed, investigated different approaches in this regard by either integrating commercial devices, to create customized sensor architectures, or by developing innovative 3D acquisition techniques. The present work is aimed at presenting an overview of the state of the art of optical technologies and sensor architectures for the surface acquisition of upper limb anatomies. The review analyzes the working principles at the basis of existing devices and proposes a categorization of the approaches based on handling, pre/post-processing effort, and potentialities in real-time scanning. An in-depth analysis of strengths and weaknesses of the approaches proposed by the research community is also provided to give valuable support in selecting the most appropriate solution for the specific application to be addressed.

Citing Articles

Computer Vision Meets Image Processing and UAS PhotoGrammetric Data Integration: From HBIM to the eXtended Reality Project of Arco della Pace in Milan and Its Decorative Complexity.

Banfi F, Mandelli A J Imaging. 2024; 7(7).

PMID: 39080906 PMC: 8321386. DOI: 10.3390/jimaging7070118.


Technical Consideration towards Robust 3D Reconstruction with Multi-View Active Stereo Sensors.

Jang M, Lee S, Kang J, Lee S Sensors (Basel). 2022; 22(11).

PMID: 35684765 PMC: 9185283. DOI: 10.3390/s22114142.

References
1.
Stefanovic B, Michalikova M, Bednarcikova L, Trebunova M, Zivcak J . Innovative approaches to designing and manufacturing a prosthetic thumb. Prosthet Orthot Int. 2021; 45(1):81-84. DOI: 10.1177/0309364620949717. View

2.
Chiu C, Thelwell M, Senior T, Choppin S, Hart J, Wheat J . Comparison of depth cameras for three-dimensional reconstruction in medicine. Proc Inst Mech Eng H. 2019; 233(9):938-947. DOI: 10.1177/0954411919859922. View

3.
Chu C, Wang I, Sun J, Liu C . Customized designs of short thumb orthoses using 3D hand parametric models. Assist Technol. 2020; 34(1):104-111. DOI: 10.1080/10400435.2019.1709917. View

4.
Koninckx T, Gool L . Real-time range acquisition by adaptive structured light. IEEE Trans Pattern Anal Mach Intell. 2006; 28(3):432-45. DOI: 10.1109/TPAMI.2006.62. View

5.
Zhong J, Weng J . Phase retrieval of optical fringe patterns from the ridge of a wavelet transform. Opt Lett. 2005; 30(19):2560-2. DOI: 10.1364/ol.30.002560. View