3D Scanning of the Forearm for Orthosis and HMI Applications

Perry, Joel C.; Brower, Jacob R.; Carne, Robert H. R.; Bogert, Melissa A.

doi:10.3389/frobt.2021.576783

Cited by 5 publications

(3 citation statements)

References 25 publications

(25 reference statements)

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“…In this study, there are 55 UC-ITN patients with NVC on the unaffected side, indicating that the presence of NVC did not necessitate the UC-ITN condition. The results showed that SALGLE (19), Coarseness (20), MAL (21), DV (22), Maximum (23), Correlation (17), and the Ofv were the risk factors for UC-ITN with bilateral NVC. UC-ITN patients with bilateral NVC only suffered from unilateral pain, probably due to different degrees of trigeminal degeneration and demyelination between the affected and unaffected side, which might lead to changes in the above-mentioned texture features.…”

Section: Discussionmentioning

confidence: 95%

Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning

Wang

Pan

et al. 2022

Front. Neurol.

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PurposeNeurovascular compression (NVC) is considered as the main factor leading to the classical trigeminal neuralgia (CTN), and a part of idiopathic TN (ITN) may be caused by NVC (ITN-nvc). This study aimed to explore the risk factors for unilateral CTN or ITN-nvc (UC-ITN), which have bilateral NVC, using machine learning (ML).MethodsA total of 89 patients with UC-ITN were recruited prospectively. According to whether there was NVC on the unaffected side, patients with UC-ITN were divided into two groups. All patients underwent a magnetic resonance imaging (MRI) scan. The bilateral cisternal segment of the trigeminal nerve was manually delineated, which avoided the offending vessel (Ofv), and the features were extracted. Dimensionality reduction, feature selection, model construction, and model evaluation were performed step-by-step.ResultsFour textural features with greater weight were selected in patients with UC-ITN without NVC on the unaffected side. For UC-ITN patients with NVC on the unaffected side, six textural features with greater weight were selected. The textural features (rad_score) showed significant differences between the affected and unaffected sides (p < 0.05). The nomogram model had optimal diagnostic power, and the area under the curve (AUC) in the training and validation cohorts was 0.76 and 0.77, respectively. The Ofv and rad_score were the risk factors for UC-ITN according to nomogram.ConclusionBesides NVC, the texture features of trigeminal-nerve cisternal segment and Ofv were also the risk factors for UC-ITN. These findings provided a basis for further exploration of the microscopic etiology of UC-ITN.

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Section: Discussionmentioning

confidence: 95%

Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning

Wang

Pan

et al. 2022

Front. Neurol.

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“…To optimize the pHMI fit, a design approach could be to account for human anthropometric heterogeneity and changes in volume during movement by performing anthropometric studies specifically tailored to the body region of a certain interface with the aid of 3D shape analysis [55,61]. In a second step, it is necessary to ensure that interfaces remain in position, either through active control (active exoskeletons) [62,63] or biomechanical measurements of relative movements (passive exoskeletons) [50].…”

Section: Considerations On the Design Of Phmismentioning

confidence: 99%

The Influence of Circular Physical Human–Machine Interfaces of Three Shoulder Exoskeletons on Tissue Oxygenation

Linnenberg,

Reimeir,

Eberle

et al. 2023

Applied Sciences

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Occupational shoulder exoskeletons need to provide meaningful torques to achieve the desired support, thereby high pressures can occur within the physical human–machine interface (pHMI) of exoskeletons that may lead to discomfort, pain, or soft tissue injuries. This pilot study investigates the effects of occurring circumferential pressures within the pHMI in three different shoulder exoskeletons on the tissue oxygenation underneath the interfaces in resting position and dynamic use of the exoskeletons in 12 healthy subjects using near-infrared spectroscopy. Similar to standard Vascular Occlusion Tests, the tissue oxygen decreases while wearing the exoskeletons at rest (−2.1 (1.4) %/min). Dynamic use of the exoskeleton enhances the decrease in tissue oxygen (−7.3 (4.1) %/min) significantly and leads to greater resaturation after reopening the interface compared to resting position. This can be a sign of restricted blood supply to the upper extremity while wearing the exoskeleton. The shape and width of the circular interfaces showed no effect on the tissue oxygenation during use. Tissue oxygenation can be established as an additional safety criterion of exoskeletal pHMIs. The design of pHMI of shoulder exoskeletons should be reconsidered, e.g., in terms of open structures or the elasticity of closure straps to avoid occlusion effects.

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“…Digital representations of anatomical structures play a crucial role in various applications within the biomedical field. For example, an accurate 3D model depicting the anatomy of the upper limb can be utilized to design customized devices for personalized rehabilitation or human–machine interfaces (HMIs) [ 1 ]. Enhancing upper limb functionality holds immense importance for patients afflicted with sports injuries, strokes, or dystonia disorders, as the upper limb is extensively involved in daily activities.…”

Section: Introductionmentioning

confidence: 99%

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

Di Angelo,

Di Stefano,

Guardiani

et al. 2023

Sensors

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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.

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3D Scanning of the Forearm for Orthosis and HMI Applications

Cited by 5 publications

References 25 publications

Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning

Risk Factors for Unilateral Trigeminal Neuralgia Based on Machine Learning

The Influence of Circular Physical Human–Machine Interfaces of Three Shoulder Exoskeletons on Tissue Oxygenation

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

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