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Torso

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Physics-Guided Deep Scatter Estimation by Weak Supervision for Quantitative SPECT.

IEEE transactions on medical imaging
Accurate scatter estimation is important in quantitative SPECT for improving image contrast and accuracy. With a large number of photon histories, Monte-Carlo (MC) simulation can yield accurate scatter estimation, but is computationally expensive. Re...

Characterizing the Effects of Adding Virtual and Augmented Reality in Robot-Assisted Training.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Extended reality (XR) technology combines physical reality with computer synthetic virtuality to deliver immersive experience to users. Virtual reality (VR) and augmented reality (AR) are two subdomains within XR with different immersion levels. Both...

Patient Re-Identification Based on Deep Metric Learning in Trunk Computed Tomography Images Acquired from Devices from Different Vendors.

Journal of imaging informatics in medicine
During radiologic interpretation, radiologists read patient identifiers from the metadata of medical images to recognize the patient being examined. However, it is challenging for radiologists to identify "incorrect" metadata and patient identificati...

Temporal Variability in Stride Kinematics during the Application of TENS: A Machine Learning Analysis.

Medicine and science in sports and exercise
INTRODUCTION: The purpose of our report was to use a Random Forest classification approach to predict the association between transcutaneous electrical nerve stimulation (TENS) and walking kinematics at the stride level when middle-aged and older adu...

Mitigating Trunk Compensatory Movements in Post-Stroke Survivors through Visual Feedback during Robotic-Assisted Arm Reaching Exercises.

Sensors (Basel, Switzerland)
Trunk compensatory movements frequently manifest during robotic-assisted arm reaching exercises for upper limb rehabilitation following a stroke, potentially impeding functional recovery. These aberrant movements are prevalent among stroke survivors ...

Subject-specific trunk segmental masses prediction for musculoskeletal models using artificial neural networks.

Medical & biological engineering & computing
Accurate determination of body segment parameters is crucial for studying human movement and joint forces using musculoskeletal (MSK) models. However, existing methods for predicting segment mass have limited generalizability and sensitivity to body ...

Improving trunk posture control in children with CP through a cable-driven robotic hippotherapy: A randomized controlled feasibility study.

Gait & posture
BACKGROUND: Many children with cerebral palsy (CP) show impairments in trunk posture control, one crucial factor contributing to impairments in gait and arm manipulation.

Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain.

Scientific reports
This paper presents an analysis of trunk movement in women with postnatal low back pain using machine learning techniques. The study aims to identify the most important features related to low back pain and to develop accurate models for predicting l...

Radiomics and Deep Learning Model for Benign and Malignant Soft Tissue Tumors Differentiation of Extremities and Trunk.

Academic radiology
RATIONALE AND OBJECTIVES: To develop radiomics and deep learning models for differentiating malignant and benign soft tissue tumors (STTs) preoperatively based on fat saturation T2-weighted imaging (FS-T2WI) of patients.

Design and experiments of a humanoid torso based on biological features.

Bioinspiration & biomimetics
Among the components of a humanoid robot, a humanoid torso plays a vital role in supporting a humanoid robot to complete the desired motions. In this paper, a new LARMbot torso is developed to obtain better working performance based on biological fea...