Smartphone photogrammetry for prosthetics and orthotics: accuracy and reliability across upper-limb, lower-limb, and AFO casts

Plus Medica AFOs detail. Ottobock, Duderstadt, Germany, acquired a majority stake in plus medica OT, Düsseldorf, Germany, a start-up that produces 3D-printed orthoses, including dynamic AFOs fabricated primarily for children. The business will be run under the Ottobock name. May 24, 2018

Abstract
Background

Conventional shape capture in prosthetics and orthotics (P&O) relies on plaster casting of a positive mold, which is then hand-rectified to the desired shape. While effective under expert practice, this workflow is labor-intensive, equipment-dependent, and difficult to archive or share. Digital approaches using structured-light scanners address some of these limitations but remain costly and require dedicated training. This study evaluated whether smartphone photogrammetry can accurately and reliably capture prosthetic and orthotic cast geometries, and assessed its usability in comparison to a clinical structured-light scanner for integration into clinical workflows.

Results

A clinical-grade structured-light scanner (EinScan H2) served as the reference and demonstrated small volumetric and dimensional errors, at 0.21 ± 0.15% and 0.35 ± 0.18 mm, with intraclass correlation coefficients (ICCs) greater than 0.9999. Relative to this reference, across 12 cast models (upper limb, lower limb, and ankle-foot orthosis), smartphone photogrammetry achieved a volumetric error of 0.89 ± 0.68% and a dimensional error of 0.89 ± 0.51 mm; the mean surface point-to-point distance was 0.24 ± 0.19 mm. Reliability across operators was near-perfect (ICCs ≥ 0.9997). Usability data showed approximately 62 photographs and 88 s per capture for photogrammetry (about 12 min cloud processing) versus 34 s capture (about 85 s desktop processing) for the reference scanner. Photogrammetry scored higher on the System Usability Scale (79 versus 58).

Conclusions

On casts, smartphone photogrammetry produced accurate and reliable meshes with favorable perceived usability and minimal hardware demands. These findings support its integration into digital workflows in P&O, particularly for scanning rectified positive casts and other stable geometries. Further multi-site evaluations on live limbs should determine acceptable capture-time thresholds and effective stabilization strategies to ensure clinical feasibility in routine practice.

References

Smartphone photogrammetry for prosthetics and orthotics: accuracy and reliability across upper-limb, lower-limb, and AFO casts, Ellis A, Pendse V, Ngan CC, Andrysek J. Biomed Eng Online. 2026 Jan 16. doi: 10.1186/s12938-026-01515-8. Epub ahead of print.

 

Further reading

A Comparative Study on the Use of Smartphone Cameras in Photogrammetry Applications, Patonis P. Sensors (Basel). 2024 Nov 15;24(22):7311. doi: 10.3390/s24227311. PDF, Full text

A smartphone photogrammetry method for digitizing prosthetic socket interiors. Hernandez A, Lemaire E. Prosthet Orthot Int. 2017 Apr;41(2):210-214. doi: 10.1177/0309364616664150. Epub 2016 Sep 24.

A comparative evaluation of photogrammetry software programs and conventional impression techniques for the fabrication of nasal maxillofacial prostheses. Buzayan MM, Elkezza AH, Ahmad SF, Mohd Salleh N, Sivakumar I. J Prosthet Dent. 2025 Jul;134(1):268-274. doi: 10.1016/j.prosdent.2023.08.027. Epub 2023 Sep 23.

Smartphone scanning is a reliable and accurate alternative to contemporary residual limb measurement techniques. Walters S, Metcalfe B, Twiste M, Seminati E, Bailey NY. PLoS One. 2024 Dec 2;19(12):e0313542. doi: 10.1371/journal.pone.0313542. eCollection 2024.

Comparison of 3D scanning versus traditional methods of capturing foot and ankle morphology for the fabrication of orthoses: a systematic review. Farhan M, Wang JZ, Bray P, Burns J, Cheng TL. J Foot Ankle Res. 2021 Jan 7;14(1):2. doi: 10.1186/s13047-020-00442-8. 

Reliability of range of motion measurements obtained by goniometry, photogrammetry and smartphone applications in lower limb: A systematic review. Canever JB, Nonnenmacher CH, Lima KMM. J Bodyw Mov Ther. 2025 Jun;42:793-802. doi: 10.1016/j.jbmt.2025.01.009. Epub 2025 Jan 16.

Also see
Engineering: Smart Manufacturing Meets Intelligent Materials: Innovations in Synthesis and Application Springer Nature

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