BackgroundPrefabricated orthotic devices are currently designed to fit a range of patients and therefore they do not provide individualized comfort and function. Custom-fit orthoses are superior to prefabricated orthotic devices from both of the above-mentioned standpoints. However, creating a custom-fit orthosis is a laborious and time-intensive manual process performed by skilled orthotists. Besides, adjustments made to both prefabricated and custom-fit orthoses are carried out in a qualitative manner. So both comfort and function can potentially suffer considerably. A computerized technique for fabricating patient-specific orthotic devices has the potential to provide excellent comfort and allow for changes in the standard design to meet the specific needs of each patient.MethodsIn this paper, 3D laser scanning is combined with rapid prototyping to create patient-specific orthoses. A novel process was engineered to utilize patient-specific surface data of the patient anatomy as a digital input, manipulate the surface data to an optimal form using Computer Aided Design (CAD) software, and then download the digital output from the CAD software to a rapid prototyping machine for fabrication.ResultsTwo AFOs were rapidly prototyped to demonstrate the proposed process. Gait analysis data of a subject wearing the AFOs indicated that the rapid prototyped AFOs performed comparably to the prefabricated polypropylene design.ConclusionsThe rapidly prototyped orthoses fabricated in this study provided good fit of the subject's anatomy compared to a prefabricated AFO while delivering comparable function (i.e. mechanical effect on the biomechanics of gait). The rapid fabrication capability is of interest because it has potential for decreasing fabrication time and cost especially when a replacement of the orthosis is required.

The continuous technological progress of magnetic resonance imaging (MRI), as well as its widespread clinical use as a highly sensitive tool in diagnostics and advanced brain research, has brought a high demand for the development of magnetic resonance (MR)-compatible robotic/mechatronic systems. Revolutionary robots guided by real-time three-dimensional (3-D)-MRI allow reliable and precise minimally invasive interventions with relatively short recovery times. Dedicated robotic interfaces used in conjunction with fMRI allow neuroscientists to investigate the brain mechanisms of manipulation and motor learning, as well as to improve rehabilitation therapies. This paper gives an overview of the motivation, advantages, technical challenges, and existing prototypes for MR-compatible robotic/mechatronic devices.

Molecular machines are tiny energy conversion devices on the molecular-size scale. Whether naturally occurring or synthetic, these machines are generally more efficient than their macroscale counterparts. They have their own mechanochemistry, dynamics, workspace, and usability and are composed of nature's building blocks: namely proteins, DNA, and other compounds, built atom by atom. With modern scientific capabilities it has become possible to create synthetic molecular devices and interface them with each other. Countless such machines exist in nature, and it is possible to build artificial ones by mimicking nature. Here we review some of the known molecular machines, their structures, features, and characteristics. We also look at certain devices in their early development stages, as well as their future applications and challenges.

A computational platform has been developed to perform simulation, visualization, and postprocessing analysis of the aggregation process of magnetic particles within a fluid environment such as small arteries and arterioles or fluid-filled cavities of the human body. The mathematical models needed to describe the physics of the system are presented in detail and also computational algorithms needed for efficient computation of these models are described. A number of simulation results demonstrate the simulation capabilities of the platform and preliminary experimental results validate simulation predictions. The platform can be used to design optimal strategies for magnetic steering and magnetic targeting of drug-loaded magnetic microparticles.