PO-1739 Optimal threshold of model parameters for the respiratory tracking system with helical tomotherapy

Received signal strength (RSS) changes of static wireless nodes can be used for device-free localization and tracking (DFLT). Most RSS-based DFLT systems require access to calibration data, either RSS measurements from a time period when the area was not occupied by people, or measurements while a person stands in known locations. Such calibration periods can be very expensive in terms of time and effort, making system deployment and maintenance challenging. This paper develops an Expectation-Maximization (EM) algorithm based on Gaussian smoothing for estimating the unknown RSS model parameters, liberating the system from supervised training and calibration periods. To fully use the EM algorithm’s potential, a novel localization-and-tracking system is presented to estimate a target’s arbitrary trajectory. To demonstrate the effectiveness of the proposed approach, it is shown that: (i) the system requires no calibration period; (ii) the EM algorithm improves the accuracy of existing DFLT methods; (iii) it is computationally very efficient; and (iv) the system outperforms a state-of-the-art adaptive DFLT system in terms of tracking accuracy.

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Development of a tracking error prediction system for the CyberKnife Synchrony Respiratory Tracking System with use of support vector regression

Medical & Biological Engineering & Computing ◽

10.1007/s11517-021-02445-4 ◽

2021 ◽

Author(s):

Kohei Okawa ◽

Mitsuhiro Inoue ◽

Takeji Sakae

Keyword(s):

Support Vector Regression ◽

Tracking System ◽

Tracking Error ◽

Support Vector ◽

Error Prediction ◽

Prediction System ◽

Respiratory Tracking

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TH-D-AUD-05: Assessment of CyberKnife's Heterogeneity Dose Calculation Algorithm and Respiratory Tracking System Using An Anthropomorphic Thorax Phantom

Medical Physics ◽

10.1118/1.2761724 ◽

2007 ◽

Vol 34 (6Part23) ◽

pp. 2641-2642

Author(s):

P Nitsch ◽

G Ibbott ◽

S Dieterich ◽

D Followill

Keyword(s):

Tracking System ◽

Dose Calculation ◽

Calculation Algorithm ◽

Dose Calculation Algorithm ◽

Respiratory Tracking

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A Spring–Dashpot System for Modelling Lung Tumour Motion in Radiotherapy

Computational and Mathematical Methods in Medicine ◽

10.1080/17486700802616534 ◽

2010 ◽

Vol 11 (1) ◽

pp. 13-26 ◽

Cited By ~ 6

Author(s):

P. L. Wilson ◽

J. Meyer

Keyword(s):

Numerical Scheme ◽

3D Model ◽

Tracking System ◽

Spatial Relationship ◽

Single Equation ◽

Lung Tumour ◽

Model Parameters ◽

Optimization Routine ◽

Parameter Ranges ◽

Differential Equations Models

A 3D system of springs and dashpots is presented to model the motion of a lung tumour during respiration. The main guiding factor in configuring the system is the spatial relationship between abdominal and lung tumour motion. A coupled, non-dimensional triple of ordinary differential equations models the tumour motion when driven by a 3D breathing signal. Asymptotic analysis is used to reduce the system to a single equation driven by a 3D signal, in the limit of small lateral and transverse tumour motions. A numerical scheme is introduced to solve this equation, and tested over wide parameter ranges. Real clinical data is used as input to the model, and the tumour motion output is in excellent agreement with that obtained by a prototype tumour tracking system, with model parameters obtained by optimization. The fully 3D model has the potential to accurately model the motion of any lung tumour given an abdominal signal as input, with model parameters obtained from an internal optimization routine.

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DYPIC - Dynamic Positioning in Ice: First Phase of Model Testing

Volume 6: Materials Technology; Polar and Arctic Sciences and Technology; Petroleum Technology Symposium ◽

10.1115/omae2012-83455 ◽

2012 ◽

Cited By ~ 2

Author(s):

Andrea Haase ◽

Solange van der Werff ◽

Peter Jochmann

Keyword(s):

Tracking System ◽

Development Project ◽

Model Testing ◽

Fine Tuning ◽

Model Parameters ◽

Second Phase ◽

Dynamic Positioning ◽

The European Union ◽

Testing Procedures ◽

Ice Conditions

DYPIC (Dynamic Positioning in Ice) is a research and development project within the MARTEC ERA-NET project of the European Union. Its objective is to contribute to the closure of the gap between DP in open water being an industry standard, and DP in ice which has some extra challenges to tackle. Two phases of model testing in ice form the back bone of the project and are facilitated by HSVA (Hamburg Ship Model Basin, Germany). The first test phase, which was executed from May to July 2011, involved two different model ships. Both were tested in free floating mode (where the model sailed solely by its own propulsion system) and fixed mode (where the model was connected to a carriage). In the free floating mode the controlling was performed by a prototype DP system scaled to model parameters. Four different managed ice fields with systematically varied ice concentration and ice floe size were prepared in the ice tank in order to investigate the influence of the relevant parameters. Tests were executed for several velocities and headings with respect to the approaching ice floes. In the free floating case ice loads on the hull were derived from the measured loads on the thrusters. The behavior of the model ship was captured by the position and heading tracking system Qualisys and several installed video cameras. The fixed mode tests serve well as a reference measurement. The results will be used to develop a model scale DP system for ice that is adjustable to different kinds of vessels and ice conditions and eventually to develop testing procedures for the assessment of the DP performance of a vessel in managed ice. A second phase of model testing for fine tuning and benchmarking the developed system will be carried out in August 2012. Within the scope of the paper is the description of the performed tests speaking of test setup and ice conditions. Analyses of results are not covered.

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