Krishnasamy S, Mokhtar RAR, Singh R, Sivallingam S, Aziz YFA, and Mathaneswaran V
Brazilian journal of cardiovascular surgery [Braz J Cardiovasc Surg] 2021 Jan 01. Date of Electronic Publication: 2021 Jan 01.
Introduction: Rapid prototyping is a process by which threedimensional (3D) computerized surface models are converted into physical models. In this study, a 3D heart bio model was created using the rapid prototyping method and the accuracy of this heart model was assessed by clinicians. Methods: The two-dimensional images of normal heart from gated computed tomography scan datasets were used to create a 3D model of the heart. The slices were then processed using the software BioModroid and printed with the 3D printer. The evaluation of the model was performed by a questionnaire answered by four cardiothoracic surgeons, 12 cardiologists, five radiologists, and nine surgical registrars. Results: Eighty-six percent of the anatomy structures showed in this model scored 100% accuracy. Structures such as circumflex branch of left coronary artery, great cardiac vein, papillary muscle, and coronary sinus were each rated 77%, 70%, 70%, and 57% accurate. Among 30 clinicians, a total of 93% rated the model accuracy as good and above; 64% of the clinicians evaluated this model as an excellent teaching tool for anatomy class. As a visual aid for surgery or interventional procedures, the model was rated excellent (40%), good (50%), average (23%), and poor (3%); 70% of the clinicians scored the model as above average for training purpose. Overall, this 3D rapid prototyping cardiac model was rated as excellent (33%), good (50%), and average (17%). Conclusion: This 3D rapid prototyping heart model will be a valuable source of anatomical education and cardiac interventional management.
Boutiette AL, Toothaker C, Corless B, Boukaftane C, and Howell C
PloS one [PLoS One] 2020 Dec 28; Vol. 15 (12), pp. e0244324. Date of Electronic Publication: 2020 Dec 28 (Print Publication: 2020).
Microfluidic technologies have enormous potential to offer breakthrough solutions across a wide range of applications. However, the rate of scale-up and commercialization of these technologies has lagged significantly behind promising breakthrough developments in the lab, due at least in part to the problems presented by transitioning from benchtop fabrication methods to mass-manufacturing. In this work, we develop and validate a method to create functional microfluidic prototype devices using 3D printed masters in an industrial-scale roll-to-roll continuous casting process. There were no significant difference in mixing performance between the roll-to-roll cast devices and the PDMS controls in fluidic mixing tests. Furthermore, the casting process provided information on the suitability of the prototype microfluidic patterns for scale-up. This work represents an important step in the realization of high-volume prototyping and manufacturing of microfluidic patterns for use across a broad range of applications.
Grigorescu S, Cocias T, Trasnea B, Margheri A, Lombardi F, and Aniello L
Sensors (Basel, Switzerland) [Sensors (Basel)] 2020 Sep 23; Vol. 20 (19). Date of Electronic Publication: 2020 Sep 23.
Self-driving cars and autonomous vehicles are revolutionizing the automotive sector, shaping the future of mobility altogether. Although the integration of novel technologies such as Artificial Intelligence (AI) and Cloud/Edge computing provides golden opportunities to improve autonomous driving applications, there is the need to modernize accordingly the whole prototyping and deployment cycle of AI components. This paper proposes a novel framework for developing so-called AI Inference Engines for autonomous driving applications based on deep learning modules, where training tasks are deployed elastically over both Cloud and Edge resources, with the purpose of reducing the required network bandwidth, as well as mitigating privacy issues. Based on our proposed data driven V-Model, we introduce a simple yet elegant solution for the AI components development cycle, where prototyping takes place in the cloud according to the Software-in-the-Loop (SiL) paradigm, while deployment and evaluation on the target ECUs (Electronic Control Units) is performed as Hardware-in-the-Loop (HiL) testing. The effectiveness of the proposed framework is demonstrated using two real-world use-cases of AI inference engines for autonomous vehicles, that is environment perception and most probable path prediction.
Materials (Basel, Switzerland) [Materials (Basel)] 2020 Dec 19; Vol. 13 (24). Date of Electronic Publication: 2020 Dec 19.
Powered ankle-foot prostheses for walking often have limitations in the range of motion and in push-off power, if compared to a lower limb of a healthy person. A new design of a powered ankle-foot prosthesis is proposed to obtain a wide range of motion and an adequate power for a push-off step. The design methodology for this prosthesis has three points. In the first one, a dimensionless kinematic model of the lower limb in the sagittal plane is built, through an experimental campaign with healthy subjects, to calculate the angles of lower limb during the gait. In the second point a multibody inverse dynamic model of the lower limb is constructed to calculate the foot-ground contact force, its point of application and the ankle torque too, entering as input data the calculated angles of the lower limb in the previous point. The third point requires, as input of the inverse dynamic model, the first dimensioning data of the ankle-foot prosthesis to obtain the load acting on the components of the prosthesis and the angle torque of the actuator during the gait cycle. Finally, an iteration cycle begins with the inverse dynamic model modifying the ankle torque and angle until these quantities during the gait are as close as possible to the physiological quantities. After the mechanical design and the construction of the prototype of the prosthesis, an experimental methodology was used for preliminary validation of the design. The preliminary tests in the laboratory on the prototype alone show that the range of motion of the ankle angle during the gait is close to a healthy person's: 27.6° vs. 29°. The pushing force of the distal area of the prototype is 1.000 N, instead of 1.600 N, because a budget reduction forced us to choose components for the prototype with lower performance.
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine [Proc Inst Mech Eng H] 2020 Dec; Vol. 234 (12), pp. 1363-1369. Date of Electronic Publication: 2020 Jul 28.
The objective of this study was to evaluate a method for printing a custom radiocontrast agent mixture to develop computed tomography markers of various shapes and sizes for assisting physicians in computed tomography-guided procedures. The radiocontrast agent mixture was designed to be bright in a computed tomography image, able to be extruded from a nozzle as a liquid and transition into a solid, and sufficiently viscous to be extruded through the tip of a needle in a controlled manner. A mixture printing method was developed using a syringe to house the mixture, a syringe pump to extrude the mixture, and a computer numeric control laser cutter to direct the nozzle in the desired path. To assess the efficacy of printing the radiocontrast agent mixture, we printed several designs, collected computed tomography images, and evaluated various physical properties of the printing method and the resulting computed tomography markers. The average line thickness was 1.56 mm (standard deviation of 0.19 mm, n = 30), the infill percentage was 99.9%, and the deviation in roundness was 0.23 mm ( n = 30). These results demonstrated the ability of the proposed method to create various types of skin markers, such as dots, lines, and hollow or solid shapes. Additionally, flat printed patterns can be folded to form three-dimensional structures that can be used to guide and support needle insertions.
Tryggvason H, Starker F, Armannsdottir AL, Lecomte C, and Jonsdottir F
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society [IEEE Trans Neural Syst Rehabil Eng] 2020 Nov 05; Vol. PP. Date of Electronic Publication: 2020 Nov 05.
This paper presents a novel design of a prosthetic foot that features adaptable stiffness that changes according to the speed of ankle motion. The motivation is the natural graduation in stiffness of a biological ankle over a range of ambulation tasks. The device stiffness depends on rate of movement, ranging from a dissipating support at very slow walking speed, to efficient energy storage and return at normal walking speed. The objective here is to design a prosthetic foot that provides a compliant support for slow ambulation, without sacrificing the spring-like energy return beneficial in normal walking. The design is a modification of a commercially available foot and employs material properties to provide a change in stiffness. The velocity dependent properties of a non-Newtonian working fluid provide the rate adaptability. Material properties of components allow for a geometry shift that results in a coupling action, affecting the stiffness of the overall system. The function of an adaptive coupling was tested in linear motion. A prototype prosthetic foot was built, and the speed dependent stiffness measured mechanically. Furthermore, the prototype was tested by a user and body kinematics measured in gait analysis for varying walking speed, comparing the prototype to the original foot model (non-modified). Mechanical evaluation of stiffness shows increase in stiffness of about 60% over the test range and 10% increase between slow and normal walking speed in user testing.
3D printing in medicine [3D Print Med] 2020 Nov 02; Vol. 6 (1), pp. 32. Date of Electronic Publication: 2020 Nov 02.
Family doctors can have an active role in identifying significant population needs and solutions. During the COVID-19 epidemic, patient home monitoring with pulse oximetry has been a key aspect of care of patients. However, pandemics bring shortage of medical equipment such as pulse oximeters. Through the local maker community, in a matter of days four "smart" pulse oximeters were built. Following Internet of Things principles, the prototypes were programmed to transmit real-time data through Wi-Fi directly to the doctors. Each pulse oximeter served a family doctor during the pandemic. In this article we describe the process that led to the production of the technology and provide detailed instructions, which have also been shared in maker-oriented websites. Dissemination can potentially lead to additional small-scale productions, limiting future shortages.