Patient-Specific Pose Estimation in Clinical Environments

Patient-Specific Pose Estimation in Clinical Environments

Reliable posture labels in hospital environments can augment research studies on neural correlates to natural behaviors and clinical applications that monitor patient activity. However, many existing pose estimation frameworks are not calibrated for these unpredictable settings. In this paper, we pr...

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Bibliographic Details
Main Authors: Kenny Chen, Paolo Gabriel, Abdulwahab Alasfour, Chenghao Gong, Werner K. Doyle, Orrin Devinsky, Daniel Friedman, Patricia Dugan, Lucia Melloni, Thomas Thesen, David Gonda, Shifteh Sattar, Sonya Wang, Vikash Gilja
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Clinical environments
convolutional neural networks
Kalman filter
patient monitoring
pose estimation
Online Access:https://ieeexplore.ieee.org/document/8490852/

Internet

https://ieeexplore.ieee.org/document/8490852/

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