To investigate the flexible adaptation of human visual system, we developed a system to provide different view fields to both eyes of a user respectively. The system named "Virtual Chameleon" consists of two CCD cameras independently controlled and a head-mounted display was used by twelve healthy volunteers. Eleven of them became able to independently control visual axes and understood two different views. The successful users of the system were able to actively control visual axes by manipulating 3D sensors held by their both hands, to watch independent view fields presented to the left and right eyes, and to look around as chameleons do. The results raise interesting question on adaption to provided two independent view fields.
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http://dx.doi.org/10.1109/IEMBS.2010.5627404 | DOI Listing |
CNS Neurosci Ther
January 2025
Department of Neurosurgery, Affiliated Qingyuan Hospital, Guangzhou Medical University, Qingyuan People's Hospital, Qiangyuan, China.
Background: During the course of the past two decades, head-mounted augmented reality surgical navigation (HMARSN) systems have been increasingly employed in a variety of surgical specialties as a result of both advancements in augmented reality-related technologies and surgeons' desires to overcome some drawbacks inherent to conventional surgical navigation systems. In the present time, most experimental HMARSN systems adopt overlain display (OD) that overlay virtual models and planned routes of surgical tools on corresponding physical tissues, organs, lesions, and so forth, in a surgical field so as to provide surgeons with an intuitive and direct view to gain better hand-eye coordination as well as avoid attention shift and loss of sight (LOS), among other benefits during procedures. Yet, its system accuracy, which is the most crucial performance indicator of any surgical navigation system, is difficult to ascertain because it is highly subjective and user-dependent.
View Article and Find Full Text PDFDevelopment
January 2025
Department of Organismic and Evolutionary Biology, Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA.
Developmental biologists can perform studies that describe a phenomenon (descriptive work) and/or explain how the phenomenon works (mechanistic work). There is a prevalent perception that molecular/genetic explanations achieved via perturbations of gene function are the primary means of advancing mechanistic knowledge. We believe this to be a limited perspective, one that does not effectively represent the breadth of work in our field.
View Article and Find Full Text PDFAnn Transl Med
December 2024
Department of Neurosurgery, Providence Neuroscience Center Everett, Everett, WA, USA.
Background: Robotic assistance has become increasingly prevalent in spinal surgery in recent years, emerging as a tool to increase accuracy and precision and lower complication rates and radiation exposure. The 7 and 8 Annual Seattle Science Foundation (SSF) Robotics Courses showcased presentations and demonstrations from some of the field's most experiences leaders on latest topics in robotics and spinal surgery, including cutting-edge preoperative planning technologies, augmented reality (AR) in the operating room, cervical fusion with transpedicular screws, and neuro-oncologic management. We provide a scoping review of the use of robotics technology in spinal surgery featuring highlights from the 7 and 8 Annual SSF Robotics Courses.
View Article and Find Full Text PDFAnn Transl Med
December 2024
Division of Cardiothoracic Surgery, Department of Surgery, The Chinese University of Hong Kong, Hong Kong, China.
Background And Objective: Patients with thoracic aortic aneurysm and dissection (TAAD) are often asymptomatic but present acutely with life threatening complications that necessitate emergency intervention. Aortic diameter measurement using computed tomography (CT) is considered the gold standard for diagnosis, surgical planning, and monitoring. However, manual measurement can create challenges in clinical workflows due to its time-consuming, labour-intensive nature and susceptibility to human error.
View Article and Find Full Text PDFHealthc Technol Lett
December 2024
Robotics and Control Laboratory, Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada.
The Segment Anything model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each frame and large computational cost limit its usage in robotically assisted surgery. Applications, such as augmented reality guidance, require little user intervention along with efficient inference to be usable clinically.
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