269 research outputs found

    Patient-Specific Prosthetic Fingers by Remote Collaboration - A Case Study

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    The concealment of amputation through prosthesis usage can shield an amputee from social stigma and help improve the emotional healing process especially at the early stages of hand or finger loss. However, the traditional techniques in prosthesis fabrication defy this as the patients need numerous visits to the clinics for measurements, fitting and follow-ups. This paper presents a method for constructing a prosthetic finger through online collaboration with the designer. The main input from the amputee comes from the Computer Tomography (CT) data in the region of the affected and the non-affected fingers. These data are sent over the internet and the prosthesis is constructed using visualization, computer-aided design and manufacturing tools. The finished product is then shipped to the patient. A case study with a single patient having an amputated ring finger at the proximal interphalangeal joint shows that the proposed method has a potential to address the patient's psychosocial concerns and minimize the exposure of the finger loss to the public.Comment: Open Access articl

    Safety experiments for small robots investigating the potential of soft materials in mitigating the harm to the head due to impacts

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    There is a growing interest in social robots to be considered in the therapy of children with autism due to their effectiveness in improving the outcomes. However, children on the spectrum exhibit challenging behaviors that need to be considered when designing robots for them. A child could involuntarily throw a small social robot during meltdown and that could hit another person's head and cause harm (e.g. concussion). In this paper, the application of soft materials is investigated for its potential in attenuating head's linear acceleration upon impact. The thickness and storage modulus of three different soft materials were considered as the control factors while the noise factor was the impact velocity. The design of experiments was based on Taguchi method. A total of 27 experiments were conducted on a developed dummy head setup that reports the linear acceleration of the head. ANOVA tests were performed to analyze the data. The findings showed that the control factors are not statistically significant in attenuating the response. The optimal values of the control factors were identified using the signal-to-noise (S/N) ratio optimization technique. Confirmation runs at the optimal parameters (i.e. thickness of 3 mm and 5 mm) showed a better response as compared to other conditions. Designers of social robots should consider the application of soft materials to their designs as it help in reducing the potential harm to the head

    Data for benchmarking low-cost, 3D printed prosthetic hands

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    In this article, three different data sets are presented to evaluate a representative of openly accessible 3D printed prosthetic hand. The first data set includes grasping force measurements of human hand and low-cost 3D printed hand. Three grasping functions were evaluated, spherical, cylindrical, and precision grasps. The experimental test was performed using a wearable tactile sensor. The second data set includes the numerical analysis of prosthetic fingers made from Acrylonitrile Butadiene Styrene (ABS) and Polylactic Acid (PLA) materials under different carrying loads. The numerical analyses were carried out by LS-DYNA software. The files can be used for the prosthetic fingers’ evaluation and for the selection of suitable material. The third data set includes the experimental tensile test of ABS and PLA materials. The mechanical properties were calculated from the results, which can be used in the design and fabrication of products from these materials. All the datasets are available from Harvard Dataverse: https://doi.org/10.7910/DVN/GCPAIL.The work is supported by an internal QUCG grant from Qatar University under the grant No. QUCG-CENG-2018/2019-3 . The statements made herein are solely the responsibility of the authors

    Head Impact Severity Measures for Small Social Robots Thrown During Meltdown in Autism

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    Social robots have gained a lot of attention recently as they have been reported to be effective in supporting therapeutic services for children with autism. However, children with autism may exhibit a multitude of challenging behaviors that could be harmful to themselves and to others around them. Furthermore, social robots are meant to be companions and to elicit certain social behaviors. Hence, the presence of a social robot during the occurrence of challenging behaviors might increase any potential harm. In this paper, we identified harmful scenarios that might emanate between a child and a social robot due to the manifestation of challenging behaviors. We then quantified the harm levels based on severity indices for one of the challenging behaviors (i.e. throwing of objects). Our results showed that the overall harm levels based on the selected severity indices are relatively low compared to their respective thresholds. However, our investigation of harm due to throwing of a small social robot to the head revealed that it could potentially cause tissue injuries, subconcussive or even concussive events in extreme cases. The existence of such behaviors must be accounted for and considered when developing interactive social robots to be deployed for children with autism.The work is supported by a research grant from Qatar University under the grant No. QUST-1-CENG-2018-7Scopu

    A Method for 3-D Printing Patient-Specific Prosthetic Arms with High Accuracy Shape and Size

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    Limb amputation creates serious emotional and functional damage to the one who lost a limb. For some upper limb prosthesis users, comfort and appearance are among the desired features. The objective of this paper is to develop a streamlined methodology for prosthesis design by recreating the shape and size of an amputated arm with high accuracy through 3-D printing and silicone casting. To achieve this, the computer tomography (CT) images of the patient's affected and non-affected arms were scanned. Next, the geometry of the socket and the prosthetic arm were designed according the mirrored geometry of the non-affected arm through computer-aided design software. The support structure and the moulds were 3-D printed, and the prosthetic arm was casted with a silicone material. To validate the replication, the shape of the socket and prosthetic arm were quantitatively compared with respect to the source CT scan from the patient. The prosthetic arm was found to have high accuracy on the basis of the Dice Similarity Coefficient (DSC; 0.96), percent error (0.67%), and relative mean distance (0.34 mm, SD = 0.48 mm). Likewise, the socket achieved high accuracy based on those measures: DSC (0.95), percent error (2.97%), and relative mean distance (0.46 mm, SD = 1.70 mm) The liner, socket, and prosthetic arm were then shipped to the patient for fitting. The patient found the fit of the socket and the replication of the shape and the size of the prosthesis to be desirable. Overall, this paper demonstrates that CT imaging, computed-aided design, desktop 3-D printing, and silicone casting can achieve patient-specific cosmetic prosthetic arms with high accuracy. - 2013 IEEE.This work was supported by the NPRP Grant from the Qatar National Research Fund under Grant NPRP 7-673-2-251. The statements made herein are solely the responsibility of the authors.Scopu

    Data on the impact of objects with different shapes, masses, and impact velocities on a dummy head

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    In this article, a data generated from impacts of objects with different shapes, masses, and impact velocities on a developed dummy head. The mass considered was in the range of 0.3-0.5 kg while the shapes considered were cube, wedge, and cylinder. The impact velocities levels were in the range of 1-3 m/s. A total of 144 experiments were conducted and the corresponding videos and raw data were analyzed for impact velocity, peak head linear acceleration, 3 ms criterion, and the Head Injury Criterion (HIC). This dataset includes the raw acceleration data and a summary of the overall processed data. The data is available on Harvard Dataverse: https://doi.org/10.7910/DVN/AVC8GG.The work is supported by a research grant from Qatar University under the Grant no. QUST-1-CENG-2018-7 .Scopu
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