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Extremities

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Comparing end-effector position and joint angle feedback for online robotic limb tracking.

PloS one
Somatosensation greatly increases the ability to control our natural body. This suggests that supplementing vision with haptic sensory feedback would also be helpful when a user aims at controlling a robotic arm proficiently. However, whether the pos...

Design of Low-Complexity Convolutional Neural Network Accelerator for Finger Vein Identification System.

Sensors (Basel, Switzerland)
In the biometric field, vein identification is a vital process that is constrained by the invisibility of veins as well as other unique features. Moreover, users generally do not wish to have their personal information uploaded to the cloud, so edge ...

A virtual reality platform to evaluate the effects of supernumerary limbs' appearance.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Supernumerary robot limbs (SL) can expand the ability of users by increasing the number of degrees of freedom that they control. While several SLs have been designed and tested on human participants, the effect of the limb's appearance on the user's ...

A deep learning model for accurately predicting cancer-specific survival in patients with primary bone sarcoma of the extremity: a population-based study.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Primary bone and joint sarcomas of the long bone are relatively rare neoplasms with poor prognosis. An efficient clinical tool that can accurately predict patient prognosis is not available. The current study aimed to use deep learning algor...

Mangled extremity: limb salvage for reconstruction versus primary amputation.

Current opinion in critical care
PURPOSE OF REVIEW: While MESS has historically influenced limb salvage versus amputation decisions, its universal applicability remains uncertain. With trauma systems expanding and advancements in trauma care, the need for a nuanced understanding of ...

Assessing the Potential of a Deep Learning Tool to Improve Fracture Detection by Radiologists and Emergency Physicians on Extremity Radiographs.

Academic radiology
RATIONALE AND OBJECTIVES: To evaluate the standalone performance of a deep learning (DL) based fracture detection tool on extremity radiographs and assess the performance of radiologists and emergency physicians in identifying fractures of the extrem...

Development and external validation of a machine learning model for prediction of survival in extremity leiomyosarcoma.

Surgical oncology
PURPOSE: Machine learning (ML) models have been used to predict cancer survival in several sarcoma subtypes. However, none have investigated extremity leiomyosarcoma (LMS). ML is a powerful tool that has the potential to better prognosticate extremit...

Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND: Volume of interest (VOI) segmentation is a crucial step for Radiomics analyses and radiotherapy (RT) treatment planning. Because it can be time-consuming and subject to inter-observer variability, we developed and tested a Deep Learning-b...

Universal optimal design in the vertebrate limb pattern and lessons for bioinspired design.

Bioinspiration & biomimetics
This paper broadly summarizes the variation of design features found in vertebrate limbs and analyses the resultant versatility and multifunctionality in order to make recommendations for bioinspired robotics. The vertebrate limb pattern (e.g. should...