Neurosurgeons are faced with the challenge of learning, planning, and performing increasingly complex surgical procedures in which there is little room for error. With improvements in computational power and advances in visual and haptic display technologies, virtual surgical environments can now offer potential benefits for surgical training, planning, and rehearsal in a safe, simulated setting. This article introduces the various classes of surgical simulators and their respective purposes through a brief survey of representative simulation systems in the context of neurosurgery. Many technical challenges currently limit the application of virtual surgical environments. Although we cannot yet expect a digital patient to be indistinguishable from reality, new developments in computational methods and related technology bring us closer every day. We recognize that the design and implementation of an immersive virtual reality surgical simulator require expert knowledge from many disciplines. This article highlights a selection of recent developments in research areas related to virtual reality simulation, including anatomic modeling, computer graphics and visualization, haptics, and physics simulation, and discusses their implication for the simulation of neurosurgery.
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http://dx.doi.org/10.1227/NEU.0b013e3182750d26 | DOI Listing |
Exp Brain Res
January 2025
Institute for Experimental Psychology, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany.
When we touch ourselves, the pressure appears weaker compared to when someone else touches us, an effect known as sensory attenuation. Sensory attenuation is spatially tuned and does only occur if the positions of the touching and the touched body-party spatially coincide. Here, we ask about the contribution of visual or proprioceptive signals to determine self-touch.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, Medical School, University of Exeter, Exeter EX1 2LU, UK.
: To summarize the impact of various telerehabilitation interventions on motor function, balance, gait, activities of daily living (ADLs), and quality of life (QoL) among patients with stroke and to determine the existing telerehabilitation interventions for delivering physiotherapy sessions in clinical practice. : Six electronic databases were searched to identify relevant quantitative systematic reviews (SRs). Due to substantial heterogeneity, the data were analysed narratively.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Oral Pathobiological Science and Surgery, Tokyo Dental College, 2-9-18 Kandamisaki-cho, Chiyoda-ku, Tokyo 101-0061, Japan.
Mandibular gingival squamous cell carcinoma (SCC) is the second most common oral cancer after tongue cancer. As these carcinomas often invade the mandible early, accurately defining the resection extent is important. This report highlights the use of preoperative virtual surgery data, computer-aided design and manufacturing (CAD/CAM) technology, surgical guidance, and extended reality (XR) support in achieving highly accurate marginal mandibulectomy without recurrence or metastasis.
View Article and Find Full Text PDFSensors (Basel)
January 2025
University-Industrial Cooperation Corps of HiVE Center, Wonkwang Health Science University, 514, Iksan-daero, Iksan-si 54538, Republic of Korea.
Virtual reality (VR) technology has gained popularity across various fields; however, its use often induces cybersickness, characterized by symptoms such as dizziness, nausea, and eye strain. This study investigated the differences in cybersickness levels and head movement patterns under three distinct VR viewing conditions: dynamic VR (DVR), static VR (SVR), and a control condition (CON) using a simulator. Thirty healthy adults participated, and their head movements were recorded using the Meta Quest 2 VR headset and analyzed using Python.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Shanxi Key Laboratory of Machine Vision and Virtual Reality, North University of China, Taiyuan 030051, China.
Automatic crack detection is challenging, owing to the complex and thin topologies, diversity, and background noises of cracks. Inspired by the wavelet theory, we present an instance normalization wavelet (INW) layer and embed the layer into the deep model for segmentation. The proposed layer employs prior knowledge in the wavelets to capture the crack features and filter the high-frequency noises simultaneously, accelerating the convergence of model training.
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