The SMOOTH-robot is a mobile robot that-due to its modularity-combines a relatively low price with the possibility to be used for a large variety of tasks in a wide range of domains. In this article, we demonstrate the potential of the SMOOTH-robot through three use cases, two of which were performed in elderly care homes. The robot is designed so that it can either make itself ready or be quickly changed by staff to perform different tasks. We carefully considered important design parameters such as the appearance, intended and unintended interactions with users, and the technical complexity, in order to achieve high acceptability and a sufficient degree of utilization of the robot. Three demonstrated use cases indicate that such a robot could contribute to an improved work environment, having the potential to free resources of care staff which could be allocated to actual care-giving tasks. Moreover, the SMOOTH-robot can be used in many other domains, as we will also exemplify in this article.
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http://dx.doi.org/10.3389/frobt.2021.645639 | DOI Listing |
Ann 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 PDFProstate Int
September 2024
Department of Urology, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu, Japan.
Background: Despite providing valuable staging and prognostic information, the therapeutic benefit of pelvic lymph node dissection (PLND) remains uncertain. We sought to assess the effect of extended PLND (ePLND) on the biochemical recurrence (BCR) of patients with National Comprehensive Cancer Net (NCCN) high- or very high-risk prostate cancer treated via robot-assisted radical prostatectomy (RARP).
Methods: We used a multi-institutional database (six centers) to assess 989 patients who underwent RARP from 2014 to 2022 with or without ePLND, among which 699 patients underwent BCR analysis.
J Spine Surg
December 2024
Department of Orthopaedic Surgery, Changi General Hospital, Singapore, Singapore.
Background: Robotic-assisted spinal surgery has reportedly improved the accuracy of instrumentation with smaller incisions, improving surgical outcomes and reducing hospital stay. However, robot-assisted spine surgery has thus far been confined to placement of pedicle screw instrumentation only. This pilot study aims to explore the feasibility of utilizing the Mazor™ X Stealth Edition (Medtronic, Sofamor Danek USA), robotic-arm platform in the minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) procedure inclusive of interbody cage placement, in our institution.
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.
View Article and Find Full Text PDFOver the past decade, there has been a global increase in the incidence of skin cancers. Skin cancer has serious consequences if left untreated, potentially leading to more advanced cancer stages. In recent years, deep learning based convolutional neural network have emerged as powerful tools for skin cancer detection.
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