Low-cost 3D Scanner Research Articles

Design and Fabrication of Low-Cost 3D Scanner Based on Photogrammetry for Mechanical Components

Design and Fabrication of Low-Cost 3D Scanner Based on Photogrammetry for Mechanical Components

Comparison of accuracy and speed between plaster casting, high-cost and low-cost 3D scanners to capture foot, ankle and lower leg morphology of children requiring ankle-foot orthoses.

Traditional plaster-cast fabrication of an ankle-foot orthosis (AFO), although robust, is time-consuming and cumbersome. 3D scanning is quickly gaining attention as an alternative to plaster casting the foot and ankle region for AFO fabrication. The aim of this study was to assess the accuracy and speed of two high-performing 3D scanners compared with plaster casting in pediatric patients requiring an AFO. Ten participants (mean age 10.0±3.9years) prescribed AFOs for a movement disorder were 3D scanned with the high-cost Artec Eva (Eva) and low-cost Structure Sensor II (SSII) using one-person (1p) and two-person (2p) protocols. Accuracy and speed for both 3D scanners were compared with corresponding plaster cast measures (≤5% acceptable difference). Bland and Altman plots were generated to show mean bias and limits of agreement. Overall, Eva and SSII were accurate for foot, ankle, and lower leg key clinical landmarks (Eva-1p: 4.4±7.3%; Eva-2p: 3.2±7.5%; SSII-1p: 0.6±7.4%; SSII-2p: 0.7±8.2%). Bland and Altman plots for the SSII demonstrated lower biases for 1p (bias 0.5mm, LoA: -12.4-13.5mm) and 2p (0.4mm, LoA: -11.4-12.2mm) protocols compared with Eva for 1p (bias 2.3mm, LoA: -8.0-12.7mm) and 2p (1.8mm, LoA: -10.7-14.3mm) protocols. The SSII 2p protocol was the fastest 3D scanning method (26.4±11.1s). The high-cost Eva and low-cost SSII 3D scanners using the 1p and 2p protocols produced comparable accuracy and faster capture of key clinical landmarks compared with plaster cast measures for the fabrication of AFOs in pediatric patients.

Performance Evaluation and Optimization of 3D Models from Low-Cost 3D Scanning Technologies for Virtual Reality and Metaverse E-Commerce

Virtual Reality (VR) is and will be a key driver in the evolution of e-commerce, providing an immersive and gamified shopping experience. However, for VR shopping spaces to become a reality, retailers’ product catalogues must first be digitised into 3D models. While this may be a simple task for retail giants, it can be a major obstacle for small retailers, whose human and financial resources are often more limited, making them less competitive. Therefore, this paper presents an analysis of low-cost scanning technologies for small business owners to digitise their products and make them available on VR shopping platforms, with the aim of helping improve the competitiveness of small businesses through VR and Artificial Intelligence (AI). The technologies to be considered are photogrammetry, LiDAR sensors and NeRF.In addition to investigating which technology provides the best visual quality of 3D models based on metrics and quantitative results, these models must also offer good performance in commercial VR headsets. In this way, we also analyse the performance of such models when running on Meta Quest 2, Quest Pro and Quest 3 headsets (Reality Labs, Reality Labs, CA, USA) to determine their feasibility and provide use cases for each type of model from a scalability point of view. Finally, our work describes a model optimisation process that reduce the polygon count and texture size of high-poly models, converting them into more performance-friendly versions without significantly compromising visual quality.

Design and analysis of solid ankle foot orthosis by employing mechanical characterization and a low-cost scanning approach for additive manufacturing

PurposeThis study aims to investigate the fabrication of solid ankle foot orthoses (SAFOs) using fused deposition modeling (FDM) printing technology. It emphasizes cost-effective 3D scanning with the Kinect sensor and conducts a comparative analysis of SAFO durability with varying thicknesses and materials, including polylactic acid (PLA) and carbon fiber-reinforced (PLA-C), to address research gaps from prior studies.Design/methodology/approachIn this study, the methodology comprises key components: data capture using a cost-effective Microsoft Kinect® Xbox 360 scanner to obtain precise leg dimensions for SAFOs. SAFOs are designed using CAD tools with varying thicknesses (3, 4, and 5 mm) while maintaining consistent geometry, allowing controlled thickness impact investigation. Fabrication uses PLA and PLA-C materials via FDM 3D printing, providing insights into material suitability. Mechanical analysis uses dual finite element analysis to assess force–displacement curves and fracture behavior, which were validated through experimental testing.FindingsThe results indicate that the precision of the scanned leg dimensions, compared to actual anthropometric data, exhibits a deviation of less than 5%, confirming the accuracy of the cost-effective scanning approach. Additionally, the research identifies optimal thicknesses for SAFOs, recommending a 4 and 5 mm thickness for PLA-C-based SAFOs and an only 5 mm thickness for PLA-based SAFOs. This optimization enhances the overall performance and effectiveness of these orthotic solutions.Originality/valueThis study’s innovation lies in its holistic approach, combining low-cost 3D scanning, 3D printing and computational simulations to optimize SAFO materials and thickness. These findings advance the creation of cost-effective and efficient orthotic solutions.

ARSIP: Automated Robotic System for Industrial Painting

This manuscript addresses the critical need for precise paint application to ensure product durability and aesthetics. While manual work carries risks, robotic systems promise accuracy, yet programming diverse product trajectories remains a challenge. This study aims to develop an autonomous system capable of generating paint trajectories based on object geometries for user-defined spraying processes. By emphasizing energy efficiency, process time, and coating thickness on complex surfaces, a hybrid optimization technique enhances overall efficiency. Extensive hardware and software development results in a robust robotic system leveraging the Robot Operating System (ROS). Integrating a low-cost 3D scanner, calibrator, and trajectory optimizer creates an autonomous painting system. Hardware components, including sensors, motors, and actuators, are seamlessly integrated with a Python and ROS-based software framework, enabling the desired automation. A web-based GUI, powered by JavaScript, allows user control over two robots, facilitating trajectory dispatch, 3D scanning, and optimization. Specific nodes manage calibration, validation, process settings, and real-time video feeds. The use of open-source software and an ROS ecosystem makes it a good choice for industrial-scale implementation. The results indicate that the proposed system can achieve the desired automation, contingent upon surface geometries, spraying processes, and robot dynamics.

Comparative evaluation of low-cost 3D scanning devices for ear acquisition

Autologous ear reconstruction is a surgical procedure performed in the case of defects of the outer ear in which the malformed anatomy is reconstructed with autologous cartilage tissue and often involves the use of surgical guides modelled from a digital reconstruction of the ear anatomy. To obtain such three-dimensional anatomy, traditional imaging methods, which are expensive and invasive, can be replaced by professional 3D scanners or low-cost commercial devices. In this context, this paper focuses on the evaluation of two devices for the acquisition of the outer ear, the Intel® RealSense D405™ (stereo camera) and the TrueDepth camera of the iPhone® 13 (structured light camera), proposing a comparison based on four parameters: accuracy, precision, deviation range and point-to-point distance, in order to assess their usability in the medical field, and in particular in the context of autologous ear reconstruction. The results show that, despite significantly different handling of the raw data, the performance of the two devices is comparable: average accuracy is 0.76 mm for the D405 and 0.95 mm for the iPhone 13, average precision is 0.071 mm for the D405 and 0.065 mm for the iPhone 13, average range of deviation is 3.12 mm for the D405 and 3.64 mm for the iPhone 13.

Performance of Photogrammetry-Based Makeshift 3D Scanning System for Geometrical Object in Reverse Engineering

A three-dimension (3D) scanner is one of the important tools for digital reproduction of physical objects in reverse engineering. In some cases, a makeshift 3D scanner is needed immediately, such as for emergency spare parts reproduction. Thus, this research aims to investigate the feasibility of a low-cost makeshift 3D scanner using a mobile phone and the photogrammetry method in reconstructing digital 3D models of geometrical objects. A focus is given to the dimension accuracy of the reconstructed 3D models, which have been reproduced using images taken by a mobile phone, in comparison with the actual dimension of the scanned test pieces. To do so, four types of actual geometrical test pieces with dimension from 5 to 175 mm had been fabricated using CNC machine. 3D models of each test pieces had been developed using the photogrammetry method and compared with those developed using an industrial-grade high-end 3D scanner. It was found that mobile photogrammetry achieved an average accuracy of 97.2%, with minimum and maximum values of 83.3% and 99.9%, respectively. Geometrical dimensions less than 10 mm tend to have lower accuracy, while it was the opposite for dimensions over 150 mm. Furthermore, the scanning limit for either method was found to be a surface with a small tilting angle (less than 3 degrees). Nevertheless, photogrammetry method in combination with a mobile phone has the potential to be utilized as an alternative of a makeshift 3D scanning system with sufficient accuracy using commonly available tools.

Automatic Multiview Alignment of RGB-D Range Maps of Upper Limb Anatomy.

Digital representations of anatomical parts are crucial for various biomedical applications. This paper presents an automatic alignment procedure for creating accurate 3D models of upper limb anatomy using a low-cost handheld 3D scanner. The goal is to overcome the challenges associated with forearm 3D scanning, such as needing multiple views, stability requirements, and optical undercuts. While bulky and expensive multi-camera systems have been used in previous research, this study explores the feasibility of using multiple consumer RGB-D sensors for scanning human anatomies. The proposed scanner comprises three Intel® RealSenseTM D415 depth cameras assembled on a lightweight circular jig, enabling simultaneous acquisition from three viewpoints. To achieve automatic alignment, the paper introduces a procedure that extracts common key points between acquisitions deriving from different scanner poses. Relevant hand key points are detected using a neural network, which works on the RGB images captured by the depth cameras. A set of forearm key points is meanwhile identified by processing the acquired data through a specifically developed algorithm that seeks the forearm's skeleton line. The alignment process involves automatic, rough 3D alignment and fine registration using an iterative-closest-point (ICP) algorithm expressly developed for this application. The proposed method was tested on forearm scans and compared the results obtained by a manual coarse alignment followed by an ICP algorithm for fine registration using commercial software. Deviations below 5 mm, with a mean value of 1.5 mm, were found. The obtained results are critically discussed and compared with the available implementations of published methods. The results demonstrate significant improvements to the state of the art and the potential of the proposed approach to accelerate the acquisition process and automatically register point clouds from different scanner poses without the intervention of skilled operators. This study contributes to developing effective upper limb rehabilitation frameworks and personalized biomedical applications by addressing these critical challenges.

Minimal Required Resolution to Capture the 3D Shape of the Human Back-A Practical Approach.

Adolescent idiopathic scoliosis (AIS) is a prevalent musculoskeletal disorder that causes abnormal spinal deformities. The early screening of children and adolescents is crucial to identify and prevent the further progression of AIS. In clinical examinations, scoliometers are often used to noninvasively estimate the primary Cobb angle, and optical 3D scanning systems have also emerged as alternative noninvasive approaches for this purpose. The recent advances in low-cost 3D scanners have led to their use in several studies to estimate the primary Cobb angle or even internal spinal alignment. However, none of these studies demonstrate whether such a low-cost scanner satisfies the minimal requirements for capturing the relevant deformities of the human back. To practically quantify the minimal required spatial resolution and camera resolution to capture the geometry and shape of the deformities of the human back, we used multiple 3D scanning methodologies and systems. The results from an evaluation of 30 captures of AIS patients and 76 captures of healthy subjects showed that the minimal required spatial resolution is between 2 mm and 5 mm, depending on the chosen error tolerance. Therefore, a minimal camera resolution of 640 × 480 pixels is recommended for use in future studies.

Introduction and validation of an automatic and low-cost three-dimensional facial imaging system: a comparison to direct anthropometry and Vectra H1.

Three-dimensional (3D) imaging is a powerful tool for the analysis of soft tissue morphology. 3D photogrammetry outperforms conventional photogrammetric methods and gains popularity among plastic surgeons. However, commercial 3D imaging systems bundled with analytical software are costly. This study intends to introduce and validate an automatic, low-cost, and user-friendly 3D facial scanner. An automatic and low-cost 3D facial scanning system was developed. The system consisted of a 3D facial scanner running automatically on a sliding track and a 3D data processing tool. Fifteen human subjects underwent 3D facial imaging by the novel scanner. Eighteen anthropometric parameters were measured on the 3D virtual models and compared with caliper measurements (the gold standard). Further, the novel 3D scanner was compared to the commonly used commercial 3D facial scanner Vectra H1. Heat map analysis was used to evaluate the deviation between the 3D models obtained by the two imaging systems. The 3D photogrammetric results were highly correlated with the direct measurement results (P<0.001). The mean absolute differences (MADs) were less than 2 mm. Bland-Altman analysis indicated that, for 17 of the 18 parameters, the largest differences within the 95% limits of agreement margin were within the 2.0 mm clinical acceptance. Heat map analysis showed the average distance between the 3D virtual models was 0.15 mm, with a root mean square of 0.71 mm. The novel 3D facial scanning system is proven to be highly reliable. It provides a good alternative to commercial 3D facial scanners.

Three-Dimensional Immersion Scanning Technique: A Scalable Low-Cost Solution for 3D Scanning Using Water-Based Fluid

Three-dimensional scanning technology has been traditionally used in the medical and engineering industries, but these scanners can be expensive or limited in their capabilities. This research aimed to develop low-cost 3D scanning using rotation and immersion in a water-based fluid. This technique uses a reconstruction approach similar to CT scanners but with significantly less instrumentation and cost than traditional CT scanners or other optical scanning techniques. The setup consisted of a container filled with a mixture of water and Xanthan gum. The object to be scanned was submerged at various rotation angles. A stepper motor slide with a needle was used to measure the fluid level increment as the object being scanned was submerged into the container. The results showed that the 3D scanning using immersion in a water-based fluid was feasible and could be adapted to a wide range of object sizes. The technique produced reconstructed images of objects with gaps or irregularly shaped openings in a low-cost fashion. A 3D printed model with a width of 30.7200 ± 0.2388 mm and height of 31.6800 ± 0.3445 mm was compared to its scan to evaluate the precision of the technique. Its width/height ratio (0.9697 ± 0.0084) overlaps the margin of error of the width/height ratio of the reconstructed image (0.9649 ± 0.0191), showing statistical similarities. The signal-to-noise ratio was calculated at around 6 dB. Suggestions for future work are made to improve the parameters of this promising, low-cost technique.

Comparing Direct Measurements and Three-Dimensional (3D) Scans for Evaluating Facial Soft Tissue

The inspection of patients' soft tissues and the effects of various dental procedures on their facial physiognomy are quite challenging. To minimise discomfort and simplify the process of manual measuring, we performed facial scanning and computer measurement of experimentally determined demarcation lines. Images were acquired using a low-cost 3D scanner. Two consecutive scans were obtained from 39 participants, to test the scanner repeatability. An additional ten persons were scanned before and after forward movement of the mandible (predicted treatment outcome). Sensor technology that combines red, green, and blue (RGB) data with depth information (RGBD) integration was used for merging frames into a 3D object. For proper comparison, the resulting images were registered together, which was performed with ICP (Iterative Closest Point)-based techniques. Measurements on 3D images were performed using the exact distance algorithm. One operator measured the same demarcation lines directly on participants; repeatability was tested (intra-class correlations). The results showed that the 3D face scans were reproducible with high accuracy (mean difference between repeated scans <1%); the actual measurements were repeatable to some extent (excellent only for the tragus-pogonion demarcation line); computational measurements were accurate, repeatable, and comparable to the actual measurements. Three dimensional (3D) facial scans can be used as a faster, more comfortable for patients, and more accurate technique to detect and quantify changes in facial soft tissue resulting from various dental procedures.

Evaluation of Geometric Data Registration of Small Objects from Non-Invasive Techniques: Applicability to the HBIM Field.

Reverse engineering and the creation of digital twins are advantageous for documenting, cataloging, and maintenance control tracking in the cultural heritage field. Digital copies of the objects into Building Information Models (BIM) add cultural interest to every artistic work. Low-cost 3D sensors, particularly structured-light scanners, have evolved towards multiple uses in the entertainment market but also as data acquisition and processing techniques for research purposes. Nowadays, with the development of structured-light data capture technologies, the geometry of objects can be recorded in high-resolution 3D datasets at a very low cost. On this basis, this research addresses a small artifact with geometric singularities that is representative of small museum objects. For this, the precision of two structured-light scanners is compared with that of the photogrammetric technique based on short-range image capture: a high-cost Artec Spider 3D scanner, and the low-cost Revopoint POP 3D scanner. Data capture accuracy is evaluated through a mathematical algorithm and point set segmentation to verify the spatial resolution. In addition, the precision of the 3D model is studied through a vector analysis in a BIM environment, an unprecedented analysis until now. The work evaluates the accuracy of the devices through algorithms and the study of point density at the submillimeter scale. Although the results of the 3D geometry may vary in a morphometric analysis depending on the device records, the results demonstrate similar accuracies in that submillimeter range. Photogrammetry achieved an accuracy of 0.70 mm versus the Artec Spider and 0.57 mm against the Revopoint POP 3D scanner.

EVALUATION OF AZURE KINECT DERIVED POINT CLOUDS TO DETERMINE THE PRESENCE OF MICROHABITATS ON SINGLE TREES BASED ON THE SWISS STANDARD PARAMETERS

Abstract. In the last few years, a number of low-cost 3D scanning sensors have been developed to reconstruct the real-world environment. These sensors were primarily designed for indoor use, making them highly unpredictable in terms of their performance and accuracy when used outdoors. The Azure Kinect belongs to this category of low-cost 3D scanners and has been successfully employed in outdoor applications. In addition, this sensor possesses features such as portability and live visualization during data acquisition that makes it extremely interesting in the field of forestry. In the context of forest inventory, these advantages would allow to facilitate the task of tree parameters acquisition in an efficient manner. In this paper, a protocol was established for the acquisition of 3D data in forests using the Azure Kinect. A comparison of the resulting point cloud was performed against photogrammetry. Results demonstrated that the Azure Kinect point cloud was of suitable quality for extracting tree parameters such as diameter at breast height (DBH, with a standard deviation of 2.2cm). Furthermore, the quality of the visual and geometric information of the point cloud was evaluated in terms of its feasibility to identify microhabitats. Microhabitats represent valuable information on forest biodiversity and are included in Swiss forest inventory measurements. In total, five different microhabitats were identified in the Azure Kinect Point cloud. The measurements were therefore comparable to sensors such as terrestrial laser scanning and photogrammetry. Therefore, we argue that the Azure Kinect point cloud can efficiently identify certain types of microhabitats and this study presents a first approach of its application in forest inventories.

Open source 3D phenotyping of chickpea plant architecture across plant development

BackgroundBeing able to accurately assess the 3D architecture of plant canopies can allow us to better estimate plant productivity and improve our understanding of underlying plant processes. This is especially true if we can monitor these traits across plant development. Photogrammetry techniques, such as structure from motion, have been shown to provide accurate 3D reconstructions of monocot crop species such as wheat and rice, yet there has been little success reconstructing crop species with smaller leaves and more complex branching architectures, such as chickpea.ResultsIn this work, we developed a low-cost 3D scanner and used an open-source data processing pipeline to assess the 3D structure of individual chickpea plants. The imaging system we developed consists of a user programmable turntable and three cameras that automatically captures 120 images of each plant and offloads these to a computer for processing. The capture process takes 5–10 min for each plant and the majority of the reconstruction process on a Windows PC is automated. Plant height and total plant surface area were validated against “ground truth” measurements, producing R2 > 0.99 and a mean absolute percentage error < 10%. We demonstrate the ability to assess several important architectural traits, including canopy volume and projected area, and estimate relative growth rate in commercial chickpea cultivars and lines from local and international breeding collections. Detailed analysis of individual reconstructions also allowed us to investigate partitioning of plant surface area, and by proxy plant biomass.ConclusionsOur results show that it is possible to use low-cost photogrammetry techniques to accurately reconstruct individual chickpea plants, a crop with a complex architecture consisting of many small leaves and a highly branching structure. We hope that our use of open-source software and low-cost hardware will encourage others to use this promising technique for more architecturally complex species.

Haptic Manipulation of 3D Scans for Geometric Feature Enhancement.

Localisation of geometric features like holes, edges, slots, etc. is vital to robotic planning in industrial automation settings. Low-cost 3D scanners are crucial in terms of improving accessibility, but pose a practical challenge to feature localisation because of poorer resolution and consequently affect robotic planning. In this work, we address the possibility of enhancing the quality of a 3D scan by a manual ’touch-up’ of task-relevant features, to ensure their automatic detection prior to automation. We propose a framework whereby the operator (i) has access to both the actual work-piece and its 3D scan; (ii) evaluates the missing salient features from the scan; (iii) uses a haptic stylus to physically interact with the actual work-piece, around such specific features; (iv) interactively updates the scan using the position and force information from the haptic stylus. The contribution of this work is the use of haptic mismatch for geometric update. Specifically, the geometry from the 3D scan is used to predict haptic feedback at a point on the work-piece surface. The haptic mismatch is derived as a measure of error between this prediction and the real interaction forces from physical contact at that point on the work-piece. The geometric update is driven until the haptic mismatch is minimised. Convergence of the proposed algorithm is first numerically verified on an analytical surface with simulated physical interaction. Error analysis of the surface position and orientations were also plotted. Experiments were conducted using a motion capture system providing sub-mm accuracy in position and a 6 axis F/T sensor. Missing features are successfully detected after the update of the scan using the proposed method in an experiment.

Construction of low-cost 3D scanner using triangulation and Screened Poisson Surface Reconstruction techniques

The application of 3D scanner technology among industrial practitioner in Indonesia and Malaysia is still at the beginning stage. Compared to others, this technology has already been adapted mostly by growing country such as China, Korea, US, Germany and Italy. This technology can be seen implemented in manufacturing, aerospace, medical and dentistry industries. The concept of 3D scanner technology is mainly to improve the reverse engineering process. Due to the high cost of 3D scanner machine available in the market, therefore a reasonable cost-effective 3D scanner is needed to be developed especially for education purposes. The objective of this project is to develop low-cost 3D scanning setup to create a mesh of a small-scale object with the help of open-sources software for 3D scanning and 3D mesh processing. Triangulation technique was used for the scanning process to capture the object surface. Screened Poisson Surface Reconstruction techniques was applied to improve the uncomplete and uneven surface mesh. In order to test the setup, 3D scanning was conducted on 4 different objects with different colours and surface finish. The scanning results show that the proposed method produced a good 3D mesh with less noise and less uncomplete surface.

X-ray-free protocol for pectus deformities based on magnetic resonance imaging and a low-cost portable three-dimensional scanning device: a preliminary study.

To compare a standard protocol using chest computed tomography (CT) to a non-irradiant protocol involving a low-cost portable 3D scanner and magnetic resonance imaging (MRI) for all pectus deformities based on the Haller index (HI). From April 2019 to March 2020, all children treated for pectus excavatum or carinatum at our institution were evaluated by chest CT, 3D scanning (iPad with Structure Sensor and Captevia-Rodin4D) and MRI. The main objectives were to compare the HI determined by CT or MRI to a derived index evaluated with 3D scanning, the external Haller index (EHI). The secondary objectives were to assess the inter-rater variability and the concordance between CT and MRI for the HI and the correction index. Eleven patients were evaluated. We identified a strong correlation between the HI with MRI and the EHI (Pearson correlation coefficient = 0.900; P < 0.001), with a strong concordance between a radiologist and a non-radiologist using intra-class correlation for the HI with MRI (intra-class correlation coefficient = 0.995; [0.983; 0.999]) and the EHI (intra-class correlation coefficient = 0.978; [0.823; 0.995]). We also identified a marked correlation between the HI with CT and the EHI (Pearson coefficient = 0.855; P = 0.002), with a strong inter-rater concordance (intra-class correlation coefficient = 0.975; [0.901; 0.993]), a reliable concordance between CT and MRI for the HI and the correction index (Pearson coefficient = 0.886; P = 0.033). Non-irradiant pectus deformity assessment is possible in clinical practice, replacing CT with MRI and 3D scanning as a possible readily-accessible monitoring tool.

Total body and regional surface area: Quantification with low-cost three-dimensional optical imaging systems.

Body surface area (SA) is a widely used physical measure incorporated into multiple thermophysiology and evolutionary biology models currently estimated in humans either with empirical prediction equations or costly whole-body laser imaging systems. The introduction of low-cost 3D scanners provides a new opportunity to quantify total body (TB) and regional SA, although a critical question prevails: can these devices acquire the quality of depth information and process this initial data to form a mesh that has the fidelity needed to generate accurate SA estimates? This question was answered by comparing SA estimates calculated using images from four commercial 3D scanners in 108 adults to corresponding estimates acquired with a whole-body laser system. This was accomplished by processing initial mesh data from all devices, including the laser system, with the same universal software adapted specifically for repairing mesh gaps, identifying landmarks, and generating SA measurements. TB SA measured on all four 3D scanners was highly correlated with corresponding laser system estimates (R2 s, 0.98-0.99; all p< 0.001) with some small but significant mean differences (-0.19 to 0.06 m2 ); root-mean square errors (RMSEs) were small (0.02-0.03 m2 ); and significant bias was present for one device. Qualitatively similar results (e.g., R2 s, 0.78-0.95; mean Δs, -0.05 to 0.02 m2 ; RMSEs, 0.01-0.03 m2 ) were present for trunk, arm, and leg SA comparisons. The current study observations demonstrate that low-cost and practical 3D optical scanners are capable of accurately quantifying TB and regional SA, thus opening new opportunities for evaluating human phenotypes and related physiological characteristics.

HAND 3D SCANNING POSSIBILITIES

3D scanning as an innovative method of obtaining specific substrates for the design of prosthetic-orthotic devices is now becoming increasingly popular. The advantages of this technology over the classic way of taking the dimensional and shape characteristics of parts of the human body are its non-invasiveness, speed, archiving and, more recently, the possibility of using a low-cost 3D scanner, thus reducing economic demands and making the technology available to most orthopaedic technicians. The article offers a comprehensive overview of the correct positioning of the hand and fingers for selected types of gripping as well as possible complications in their scanning, for the achievement of correct digital models applicable to the design of personalized orthotic devices.