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The smooth movement of hand/surgical instruments is considered an indicator of skilled, coordinated surgical performance. Jerky surgical instrument movements or hand tremors can cause unwanted damages to the surgical site. Different methods have been used in previous studies for assessing motion smoothness, causing conflicting results regarding the comparison among surgical skill levels. We recruited four attending surgeons, five surgical residents, and nine novices. The participants conducted three simulated laparoscopic tasks, including peg transfer, bimanual peg transfer, and rubber band translocation. Tooltip motion smoothness was computed using the mean tooltip motion jerk, logarithmic dimensionless tooltip motion jerk, and 95% tooltip motion frequency (originally proposed in this study) to evaluate their capability of surgical skill level differentiation. The results revealed that logarithmic dimensionless motion jerk and 95% motion frequency were capable of distinguishing skill levels, indicated by smoother tooltip movements observed in high compared to low skill levels. Contrarily, mean motion jerk was not able to distinguish the skill levels. Additionally, 95% motion frequency was less affected by the measurement noise since it did not require the calculation of motion jerk, and 95% motion frequency and logarithmic dimensionless motion jerk yielded a better motion smoothness assessment outcome in distinguishing skill levels than mean motion jerk.
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http://dx.doi.org/10.3390/s23063146 | DOI Listing |
Knee Surg Sports Traumatol Arthrosc
September 2025
Acıbadem University School of Medicine, Istanbul, Turkey.
Purpose: Scapular dyskinesis (SD) is present in as many as 67%-100% of athletes with shoulder injuries but it is also highly present in many asymptomatic individuals. The aim of the present study was to identify and analyse SD among asymptomatic professional basketball players.
Methods: A total of 54 European professional basketball players of various professional levels and ages were included in this prospectively recruited cross-sectional study.
Front Robot AI
August 2025
Rehab Technologies Lab, Italian Institute of Technology, Genoa, Italy.
This study's primary objective was to develop an Active Ankle-Foot Orthosis (AAFO) specifically designed for integration into lower-limb exoskeletons. An analysis of human ankle motion is conducted to inform the development process, guiding the creation of an AAFO that aligns with specifics extrapolated by real data. The AAFO incorporates an electric motor with a non-backdrivable transmission system, engineered to reduce distal mass, minimize power consumption, and enable high-precision position control.
View Article and Find Full Text PDFAccid Anal Prev
October 2025
School of Transportation, Southeast University, Nanjing 211189, China; Jiangsu Key Laboratory of Urban ITS, School of Transportation, Southeast University, Nanjing 211189, China.
Increasingly, the collection of multi-source sensing data from heavy vehicles through intelligent networked platforms has become prevalent for safety management and supervision. However, practical approaches for crash risk management and safety evaluation have not been fully developed to capitalize on this high-value driving data. This study proposed a safety evaluation framework for heavy vehicles using the extreme value modeling approach.
View Article and Find Full Text PDFSci Rep
August 2025
Department of Electrical Engineering, Dr. Shakuntala Misra National Rehabilitation University, Lucknow, India.
This study presents breakthrough mathematical formulations for UAV tracking that achieve 56.1% HOTA accuracy for targets with start-stop and irregular motion-a 65% improvement over traditional Kalman Filter approaches. Unmanned aerial vehicles face significant challenges when tracking targets exhibiting abrupt velocity changes, intermittent stops, and nonlinear trajectories due to motion discontinuities, occlusions, and environmental noise.
View Article and Find Full Text PDFEur J Sport Sci
August 2025
Centre for Neuroscience Studies, Queen's University, Kingston, Canada.
Frequent head impacts are common in Canadian football, yet the biomechanical determinants underlying repeated subconcussive exposure and their potential implications remain poorly characterized. To address this, we investigated the biomechanical impact characteristics of college-level Canadian varsity football players, aiming to elucidate the underlying factors that drive subconcussive impacts. Sixty-four athletes were outfitted with head impact sensors during games, practices, and training camps.
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