Neurally adjusted ventilator assist (NAVA) is a ventilator mode based on providing assistance to the patient in proportion to the electrical activity of the diaphragm. NAVA may improve patient-ventilator interactions. We describe a very complex case of a child with a permanent ventricular assist device where we attempted to use NAVA during the weaning process and then realised that it was impossible to use.
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http://dx.doi.org/10.1136/bcr-10-2011-5029 | DOI Listing |
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January 2025
Key Laboratory for Micro/Nano Technology and System of Liaoning Province, Dalian University of Technology, Dalian, 116024, China.
To achieve efficient size tuning of printed microstructures on insulating substrates, an integrated process parameter intelligent optimization design framework for alternating current pulse modulation electrohydrodynamic (AC-EHD) printing is proposed for the first time. The framework is comprised of two stages: the construction of a prediction model and the acquisition of process parameters. The first stage employs the elk herd optimizer(EHO)-artificial neural network(ANN) to establish a mapping relationship between printing process parameters and the size of deposited droplets.
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January 2025
School of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China.
Breast cancer (BC) is one of the most lethal cancers worldwide, and its early diagnosis is critical for improving patient survival rates. However, the extraction of key information from complex medical images and the attainment of high-precision classification present a significant challenge. In the field of signal processing, texture-rich images typically exhibit periodic patterns and structures, which are manifested as significant energy concentrations at specific frequencies in the frequency domain.
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December 2024
College of Intelligent Manufacturing and Industrial Modernization, Xinjiang University, Urumqi 830017, China.
This paper addresses the challenges of low accuracy and long transfer learning time in small-sample bearing fault diagnosis, which are often caused by limited samples, high noise levels, and poor feature extraction. We propose a method that combines an improved capsule network with a Siamese neural network. Multi-view data partitioning is used to enrich data diversity, and Markov transformation converts one-dimensional vibration signals into two-dimensional images, enhancing the visualization of signal features.
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December 2024
Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100032, China.
Investigating the physiological mechanisms in the motor cortex during rehabilitation exercises is crucial for assessing stroke patients' progress. This study developed a single-channel Jansen neural mass model to explore the relationship between model parameters and motor cortex mechanisms. Firstly, EEG signals were recorded from 11 healthy participants under 20%, 40%, and 60% maximum voluntary contraction, and alpha rhythm power spectral density characteristics were extracted using the Welch power spectrum method.
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December 2024
Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an 710119, China.
During the interaction process of a manipulator executing a grasping task, to ensure no damage to the object, accurate force and position control of the manipulator's end-effector must be concurrently implemented. To address the computationally intensive nature of current hybrid force/position control methods, a variable-parameter impedance control method for manipulators, utilizing a gradient descent method and Radial Basis Function Neural Network (RBFNN), is proposed. This method employs a position-based impedance control structure that integrates iterative learning control principles with a gradient descent method to dynamically adjust impedance parameters.
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