CAM-FoC: A High Accuracy Lightweight Deep Neural Network for Grip Force Measurement of Elongated Surgical Instrument

Grip force measurement enables better control performance for robot-assisted minimally invasive surgery (RMIS). A deep-learning-based method is proposed to measure the instrument grip force without mounting additional sensors in this article. First, the training trajectory and input data frame are s...

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Vydané v:	IEEE transactions on instrumentation and measurement Ročník 70; s. 1 - 12
Hlavní autori:	Guo, Yongchen, Pan, Bo, Fu, Yili, Meng, Max Q.-H.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Ablation Accuracy Algorithms Artificial neural networks Attention mechanism Control equipment convolutional neural network (CNN) Error reduction Force Force measurement Force sensors Grip force grip force measurement Instruments Machine learning Optimization Robot control robot-assisted minimally invasive surgery (RMIS) Robotic surgery Root-mean-square errors Sensors Surgery Surgical instruments Trajectory
ISSN:	0018-9456, 1557-9662
On-line prístup:	Získať plný text
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