Learning Skill Characteristics From Manipulations

Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary artery disease. The procedure requires high experienced skills and dexterous manipulations. However, there are few techniques to model PCI skill so far. In this study, a learning framework with local and...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 34; H. 12; S. 9727 - 9741
Hauptverfasser:	Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Ni, Zhen-Liang, Zhou, Yan-Jie, Li, Rui-Qi, Gui, Mei-Jiang, Fan, Chen-Chen, Feng, Zhen-Qiu, Bian, Gui-Bin, Hou, Zeng-Guang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.12.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Animal models Animals Arteries Cardiovascular disease Coronary arteriosclerosis Coronary artery disease Ensemble learning Feature extraction Fiber optics Heart diseases Humans In vivo In vivo methods and tests in vivo porcine studies Learning Machine learning Measurement Neural Networks, Computer Percutaneous Coronary Intervention Robotics Sensor phenomena and characterization Sensors skill characteristics Surgery Swine Task analysis wavelet packet decomposition (WPD) Wavelet transforms Wrist
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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