User acceptance of a touchless sterile system to control virtual orthodontic study models

Introduction In this article, we present an evaluation of user acceptance of our innovative hand-gesture-based touchless sterile system for interaction with and control of a set of 3-dimensional digitized orthodontic study models using the Kinect motion-capture sensor (Microsoft, Redmond, Wash). Methods The system was tested on a cohort of 201 participants. Using our validated questionnaire, the participants evaluated 7 hand-gesture-based commands that allowed the user to adjust the model in size, position, and aspect and to switch the image on the screen to view the maxillary arch, the mandibular arch, or models in occlusion. Participants' responses were assessed using Rasch analysis so that their perceptions of the usefulness of the hand gestures for the commands could be directly referenced against their acceptance of the gestures. Their perceptions of the potential value of this system for cross-infection control were also evaluated. Results Most participants endorsed these commands as accurate. Our designated hand gestures for these commands were generally accepted. We also found a positive and significant correlation between our participants' level of awareness of cross infection and their endorsement to use this system in clinical practice. Conclusions This study supports the adoption of this promising development for a sterile touch-free patient record-management system

Microscope Embedded Neurosurgical Training and Intraoperative System

In the recent years, neurosurgery has been strongly influenced by new technologies. Computer Aided Surgery (CAS) offers several benefits for patients\u27 safety but fine techniques targeted to obtain minimally invasive and traumatic treatments are required, since intra-operative false movements can be devastating, resulting in patients deaths. The precision of the surgical gesture is related both to accuracy of the available technological instruments and surgeon\u27s experience. In this frame, medical training is particularly important. From a technological point of view, the use of Virtual Reality (VR) for surgeon training and Augmented Reality (AR) for intra-operative treatments offer the best results. In addition, traditional techniques for training in surgery include the use of animals, phantoms and cadavers. The main limitation of these approaches is that live tissue has different properties from dead tissue and that animal anatomy is significantly different from the human. From the medical point of view, Low-Grade Gliomas (LGGs) are intrinsic brain tumours that typically occur in younger adults. The objective of related treatment is to remove as much of the tumour as possible while minimizing damage to the healthy brain. Pathological tissue may closely resemble normal brain parenchyma when looked at through the neurosurgical microscope. The tactile appreciation of the different consistency of the tumour compared to normal brain requires considerable experience on the part of the neurosurgeon and it is a vital point. The first part of this PhD thesis presents a system for realistic simulation (visual and haptic) of the spatula palpation of the LGG. This is the first prototype of a training system using VR, haptics and a real microscope for neurosurgery. This architecture can be also adapted for intra-operative purposes. In this instance, a surgeon needs the basic setup for the Image Guided Therapy (IGT) interventions: microscope, monitors and navigated surgical instruments. The same virtual environment can be AR rendered onto the microscope optics. The objective is to enhance the surgeon\u27s ability for a better intra-operative orientation by giving him a three-dimensional view and other information necessary for a safe navigation inside the patient. The last considerations have served as motivation for the second part of this work which has been devoted to improving a prototype of an AR stereoscopic microscope for neurosurgical interventions, developed in our institute in a previous work. A completely new software has been developed in order to reuse the microscope hardware, enhancing both rendering performances and usability. Since both AR and VR share the same platform, the system can be referred to as Mixed Reality System for neurosurgery. All the components are open source or at least based on a GPL license

Complexity Reduction in Image-Based Breast Cancer Care

The diversity of malignancies of the breast requires personalized diagnostic and therapeutic decision making in a complex situation. This thesis contributes in three clinical areas: (1) For clinical diagnostic image evaluation, computer-aided detection and diagnosis of mass and non-mass lesions in breast MRI is developed. 4D texture features characterize mass lesions. For non-mass lesions, a combined detection/characterisation method utilizes the bilateral symmetry of the breast s contrast agent uptake. (2) To improve clinical workflows, a breast MRI reading paradigm is proposed, exemplified by a breast MRI reading workstation prototype. Instead of mouse and keyboard, it is operated using multi-touch gestures. The concept is extended to mammography screening, introducing efficient navigation aids. (3) Contributions to finite element modeling of breast tissue deformations tackle two clinical problems: surgery planning and the prediction of the breast deformation in a MRI biopsy device

Review of three-dimensional human-computer interaction with focus on the leap motion controller

Modern hardware and software development has led to an evolution of user interfaces from command-line to natural user interfaces for virtual immersive environments. Gestures imitating real-world interaction tasks increasingly replace classical two-dimensional interfaces based on Windows/Icons/Menus/Pointers (WIMP) or touch metaphors. Thus, the purpose of this paper is to survey the state-of-the-art Human-Computer Interaction (HCI) techniques with a focus on the special field of three-dimensional interaction. This includes an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition. Focus is on interfaces based on the Leap Motion Controller (LMC) and corresponding methods of gesture design and recognition. Further, a review of evaluation methods for the proposed natural user interfaces is given

The Use of Predicates in FDA Regulation of Medical Devices: A Case Study of Robotic Surgical Devices

In the last decade, a number of high profile medical device recalls have drawn attention to the regulatory approval process, particularly the streamlined process for devices considered “lower risk” known as the 510(k). Approval of medical devices through the 510(k) Process is not based on clinical data, but rather on “substantial equivalence” to predicate devices approved pre-1976 or legally marketed thereafter. A predicate device is one that shares the same intended use as the new device and technological characteristics which are either the same or different without introducing new safety hazards. Many scholars believe that the premise of approving medical devices based on similarity to existing devices is inherently flawed. In particular, there is worry that presence of technology creep between predicate devices can lead to the approval of medical devices which ultimately do not resemble the original device for which clinical evidence exists, even as that evidence is used to validate device safety. Given these concerns about the safety of the established regulatory process, this thesis explored the impact of predicate creep within the 510(k) Process through a case study of a Robotic Assisted Surgery (RAS) devices, with particular focus on the Intuitive Surgical Da Vinci Surgical System. Through the development of new methodologies using publicly available data to measure predicate creep, this research traces the predicate ancestry of several RAS devices to assess the current impact and implications of predicate creep on the current regulatory process. The study concludes that there is significant evidence of predicate creep within the approval process and recommend new guidelines for classifying device risk and subsequent evidentiary requirements within the 510(k) Process, to reduce the number of devices with high levels of potential risk to public safety released onto the market