The Use of Smartphone Photogrammetry to Digitise Transtibial Sockets: Optimisation of Method and Quantitative Evaluation of Suitability

A Review on 3D Scanners Studies for Producing Customized Orthoses

When a limb suffers a fracture, rupture, or dislocation, it is traditionally immobilized with plaster. This may induce discomfort in the patient, as well as excessive itching and sweating, which creates the growth of bacteria, leading to an unhygienic environment and difficulty in keeping the injury clean during treatment. Furthermore, if the plaster remains for a long period, it may cause lesions in the joints and ligaments. To overcome all of these disadvantages, orthoses have emerged as important medical devices to help patients in rehabilitation, as well as for self-care of deficiencies in clinics and daily life. Traditionally, these devices are produced manually, which is a time-consuming and error-prone method. From another point of view, it is possible to use imageology (X-ray or computed tomography) to scan the human body; a process that may help orthoses manufacturing but which induces radiation to the patient. To overcome this great disadvantage, several types of 3D scanners, without any kind of radiation, have emerged. This article describes the use of various types of scanners capable of digitizing the human body to produce custom orthoses. Studies have shown that photogrammetry is the most used and most suitable 3D scanner for the acquisition of the human body in 3D. With this evolution of technology, it is possible to decrease the scanning time and it will be possible to introduce this technology into clinical environment.

3D Motion Analysis for the Assessment of Dynamic Coupling in Transtibial Prosthetics: A Proof of Concept

Assessment of coupling between transtibial sockets and users is historically based on clinicians' observations and experience, but can be inaccurate and unreliable. Therefore, we present a proof of concept, for five out of six possible degrees of freedom coupling metric system for a socket, using motion analysis calibrated on a 3D printed limb substitute. The method is compatible with any socket suspension method and does not require prior modifications to the socket. Calibration trials were used to locate the axis of rotation of the knee joint referenced against a marker cluster on the thigh; this allowed for the identification of the limb during test trials despite the entire residuum being obscured from view by the socket. The error in the technique was found to be within 0.7 mm in displacement and 0.7 degrees in rotation, based on the control data. Dynamic testing showed the Inter Quartile Range (IQR) of inter time step variance was <0.5 mm/deg for all metrics. The method can form a basis for objective socket evaluation, improve clinical practice and the quality of life for amputees.

Phone cam array - An open-source, modular photogrammetry system made of Android phones

Photogrammetry is a 3D reconstruction technique using photographs of the target from multiple angles. Taking pictures around a static object with a single camera can yield high-quality models, but if the subject moves between images, 3D reconstruction might fail. One way to mitigate this is to use multiple cameras. This project aimed to develop a tool for fast and precise wound documentation for clinical forensic medicine. This paper describes a simple, low-cost modular system, where smartphones of different manufacturers are used as networked cameras. Exposure is initiated at the same time in all the phones with a simple circuit emulating a headset button press. A proof-of-concept device was built, where four phones (Huawei nova 8i (2 pcs), Samsung Galaxy S7 Edge, Oukitel K4000 Pro) were attached to a curved, 3D-printed, handheld frame. The average delay of image capture was 636 ms between the quickest and the slowest phones. When compared to the single-camera approach, the use of different cameras did not reduce the quality of the 3D model. The phone cam array was less susceptible to movement artefacts caused by breathing. Wound assessment was possible based on the 3D models created with this device.

A Simple Way to Reduce 3D Model Deformation in Smartphone Photogrammetry

Recently, the term smartphone photogrammetry gained popularity. This suggests that photogrammetry may become a simple measurement tool by virtually every smartphone user. The research was undertaken to clarify whether it is appropriate to use the Structure from Motion-Multi Stereo View (SfM-MVS) procedure with self-calibration as it is done in Uncrewed Aerial Vehicle photogrammetry. First, the geometric stability of smartphone cameras was tested. Fourteen smartphones were calibrated on the checkerboard test field. The process was repeated multiple times. These observations were found: (1) most smartphone cameras have lower stability of the internal orientation parameters than a Digital Single-Lens Reflex (DSLR) camera, and (2) the principal distance and position of the principal point are constantly changing. Then, based on images from two selected smartphones, 3D models of a small sculpture were developed. The SfM-MVS method was used, with self-calibration and pre-calibration variants. By comparing the resultant models with the reference DSLR-created model it was shown that introducing calibration obtained in the test field instead of self-calibration improves the geometry of 3D models. In particular, deformations of local concavities and convexities decreased. In conclusion, there is real potential in smartphone photogrammetry, but it also has its limits.

Analysis of the Influence of the Geometrical Parameters of the Body Scanner on the Accuracy of Reconstruction of the Human Figure Using the Photogrammetry Technique

This article concerns the research of the HUBO full-body scanner, which includes the analysis and selection of the scanner's geometrical parameters in order to obtain the highest possible accuracy of the reconstruction of a human figure. In the scanner version analyzed in this paper, smartphone cameras are used as sensors. In order to process the collected photos into a 3D model, the photogrammetry technique is applied. As part of the work, dependencies between the geometrical parameters of the scanner are derived, which allows to significantly reduce the number of degrees of freedom in the selection of its geometrical parameters. Based on these dependencies, a numerical analysis is carried out, as a result of which the initial values of the geometrical parameters are pre-selected and distribution of scanner cameras is visualized. As part of the experimental research, the influence of selected scanner parameters on the scanning accuracy is analyzed. For the experimental research, a specially prepared dummy was used instead of the participation of a real human, which allowed to ensure the constancy of the scanned object. The accuracy of the object reconstruction was assessed in relation to the reference 3D model obtained with a scanner of superior measurement uncertainty. On the basis of the conducted research, a method for the selection of the scanner's geometrical parameters was finally verified, leading to the arrangement of cameras around a human, which guarantees high accuracy of the reconstruction. Additionally, to quantify the results, the quality rates were used, taking into account not only the obtained measurement uncertainty of the scanner, but also the processing time and the resulting efficiency.

ARACAM: A RGB-D Multi-View Photogrammetry System for Lower Limb 3D Reconstruction Applications

In the world, there is a growing need for lower limb prostheses due to a rising number of amputations caused primarily, by diabetic foot. Researchers enable functional and comfortable prostheses through prosthetic design by integrating new technologies applied to the traditional handcrafted method for prosthesis fabrication that is still current. That is why computer vision shows to be a promising tool for the integration of 3D reconstruction that may be useful for prosthetic design. This work has the objective to design, prototype, and test a functional system to scan plaster cast molds, which may serve as a platform for future technologies for lower limb reconstruction applications. The image capture system comprises 5 stereoscopic color and depth cameras, each with 4 DOF mountings on an enveloping frame, as well as algorithms for calibration, segmentation, registration, and surface reconstruction. The segmentation metrics of dice coefficient and Hausdorff distance (HD) show strong visual similarity with an average similarity of 87% and average error of 6.40 mm, respectively. Moving forward, the system was tested on a known 3D printed model obtained from a computer tomography scan to which comparison results via HD show an average error of ≤1.93 mm thereby making the system competitive against the systems reviewed from the state-of-the-art.