Magnetic Hammer Actuation for Tissue Penetration using a Millirobot

Untethered magnetic navigation of millirobots within a human body using a magnetic resonance imaging (MRI) scanner is a promising technology for minimally invasive surgery or drug delivery. Because MRI scanners have a large static magnetic field, they cannot generate torque on magnetic millirobots and must instead use gradient-based pulling. However, gradient values are too small to produce forces large enough to penetrate tissue. This letter presents a method to produce large pulsed forces on millirobots. A ferromagnetic sphere is placed inside a hollow robot body and can move back and forth. This movement is created by alternating the magnetic gradient direction. On the posterior side, a spring allows the sphere to change direction smoothly. On the anterior side, a hard rod creates a surface for the sphere to impact. This impact results in a large pulsed force. The purpose of this study was to understand the functioning of magnetic hammer actuation and control, as well as demonstrate the viability of this mechanism for tissue penetration. This letter begins with modeling and simulating this system. Next, different control strategies are presented and tested. The system successfully penetrated lamb brain samples. Finally, preliminary tests inside a clinical MRI scanner demonstrate the potential of this actuation system

A Multiuser, Multisite, and Platform-Independent On-the-Cloud Framework for Interactive Immersion in Holographic XR

Background: The ever-growing extended reality (XR) technologies offer unique tools for the interactive visualization of images with a direct impact on many fields, from bioinformatics to medicine, as well as education and training. However, the accelerated integration of artificial intelligence (AI) into XR applications poses substantial computational processing demands. Additionally, the intricate technical challenges associated with multilocation and multiuser interactions limit the usability and expansion of XR applications. Methods: A cloud deployable framework (Holo-Cloud) as a virtual server on a public cloud platform was designed and tested. The Holo-Cloud hosts FI3D, an augmented reality (AR) platform that renders and visualizes medical 3D imaging data, e.g., MRI images, on AR head-mounted displays and handheld devices. Holo-Cloud aims to overcome challenges by providing on-demand computational resources for location-independent, synergetic, and interactive human-to-image data immersion. Results: We demonstrated that Holo-Cloud is easy to implement, platform-independent, reliable, and secure. Owing to its scalability, Holo-Cloud can immediately adapt to computational needs, delivering adequate processing power for the hosted AR platforms. Conclusion: Holo-Cloud shows the potential to become a standard platform to facilitate the application of interactive XR in medical diagnosis, bioinformatics, and training by providing a robust platform for XR applications

Robotic Systems on the Frontline Against the Pandemic

Robotic systems have been effectively used in healthcare while a new role for them has emerged during the COVID-19 pandemic. Robots were used as part of prevention, screening and diagnosis of the disease, but also to assist with the treatment of patients. The purpose of the paper is to provide an overview of the relevant applications for robots and highlight their potential