Multistep prediction of physiological tremor based on machine learning for robotics assisted microsurgery

S Tatinati, KC Veluvolu, WT Ang - IEEE transactions on …, 2014 - ieeexplore.ieee.org
For effective tremor compensation in robotics assisted hand-held device, accurate filtering of
tremulous motion is necessary. The time-varying unknown phase delay that arises due to …

Broad learning extreme learning machine for forecasting and eliminating tremors in teleoperation

Q Yang, K Liang, T Su, K Geng, M Pan - Applied Soft Computing, 2021 - Elsevier
Unwanted errors caused by hand tremors are a bottleneck for the application of
teleoperation robots in space explorations, underwater explorations, and minimally invasive …

A real-time model based on least squares support vector machines and output bias update for the prediction of NO x emission from coal-fired power …

F Ahmed, HJ Cho, JK Kim, NU Seong… - Korean Journal of …, 2015 - Springer
The accurate and reliable real-time estimation of NOx emission is indispensable for the
implementation of successful control and optimization of NOx emission from a coal-fired …

[HTML][HTML] Kee** surgeons in the loop: Are handheld robotics the best path towards more autonomous actions?(A comparison of complete vs. handheld robotic …

AA Gumbs, M Abu-Hilal, TJ Tsai, L Starker… - Artificial Intelligence …, 2021 - oaepublish.com
Aim: Some surgeons have been using some form of handheld robotics (HR) since liver
resections began being done minimally invasively (MI); however, with the development of …

A wavelet broad learning adaptive filter for forecasting and cancelling the physiological tremor in teleoperation

J Lin, Z Liu, CLP Chen, Y Zhang - Neurocomputing, 2019 - Elsevier
Physiological tremor forecasting is one of the most important issues in tele-operation that
can improve the operational precision greatly. In the tele-operation, signals are three …

A convolutional neural network-based broad incremental learning filter for attenuating physiological tremors in telerobot systems

G Lai, W Liu, W Yang, Y Zhang - Applied Sciences, 2023 - mdpi.com
While master-slave teleoperated robotic systems have extensive applications in practice, the
physiological tremors can easily affect the control accuracy and even destroy the stability of …

Multivariable LS-SVM with moving window over time slices for the prediction of bearing performance degradation

G Tang, Y Zhang, H Wang - Journal of Intelligent & Fuzzy …, 2018 - content.iospress.com
The prediction of performance degradation is significant for the health monitoring of rolling
bearing, which helps to greatly reduce the loss caused by potential faults in the entire life …

Adaptive soft sensor based on a moving window just-in-time learning LS-SVM for distillation processes

Q Li, L **ng, W Liu, W Ba - IFAC-PapersOnLine, 2015 - Elsevier
In order to measure the distillation processes compositions under the time-varying
conditions, an adaptive soft sensor model is proposed in this paper for composition quality …

Multivariable least squares support vector machine with time integral operator for the prediction of bearing performance degradation

Y Zhang, Y Zhou, G Tang… - Proceedings of the …, 2019 - journals.sagepub.com
The prediction of performance degradation is significant for the health monitoring of rolling
bearing, which helps to greatly reduce the loss caused by potential faults in the entire life …

Adaptive nonlinear vessel steering modelling using time-sequence incremental and decremental LS-SVM

HT Xu, CG Soares - Trends in Maritime Technology and …, 2022 - taylorfrancis.com
In this paper, an adaptive nonlinear vessel steering model is proposed. A time-sequence
Least square support vector machine (LS-SVM) based on incremental and decremental …