Deep-Magnetic-Field Generator Using Flexible Laminated Copper for Thermotherapy Applications

Tai, Cheng Chi; Chen, Chien‐Chang; Kuo, Chil-Chyuan; Lin, Fang Wei; Chang, Chau‐Lyan; Chen, Yung‐Hsiang; Wang, Wei Cheng

doi:10.1109/tmag.2014.2331965

Cited by 15 publications

(5 citation statements)

References 9 publications

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“…Compared to conventional heating techniques such as resistive heating, flame heating or arc furnaces, IH is more appropriate for industrial applications since it is more effective and efficient [6][7][8][9]. More importantly, the inherent safe and convection methodologies in IH are very conducive for many medical applications [10][11][12][13][14]. The portability, plug and play aspects of IH-aided gadgets mean it is in high demand regarding household applications [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Induction Heating in Domestic Cooking and Industrial Melting Applications: A Systematic Review on Modelling, Converter Topologies and Control Schemes

et al. 2021

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In the current scenario, power electronic device-based induction heating (IH) technologies are widely employed in domestic cooking, industrial melting and medical applications. These IH applications are designed using different converter topologies, modulation and control techniques. This review article mainly focuses on the modelling of half-bridge series resonant inverter, electrical and thermal model of IH load. This review also analyses the performance of the converter topologies based on the power conversion stages, switching frequency, power rating, power density, control range, modulation techniques, load handling capacity and efficiency. Moreover, this paper provides insight into the future of IH application, with respect to the adaptation of wide band-gap power semiconductor materials, multi-output topologies, variable-frequency control schemes with minimum losses and filters designed to improve source-side power factor. With the identified research gap in the literature, an attempt has also been made to develop a new hybrid modulation technique, to achieve a wide range of power control with high efficiency. A 100 W full-bridge inverter prototype is realised both in simulation and hardware, with various modulation schemes using a PIC16F877A microcontroller. The results are compared with existing techniques and the comparisons reveal that the proposed scheme is highly viable and effective for the rendered applications.

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Section: Introductionmentioning

confidence: 99%

Induction Heating in Domestic Cooking and Industrial Melting Applications: A Systematic Review on Modelling, Converter Topologies and Control Schemes

et al. 2021

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“…From Table II, with the dynamic prediction characteristic of the ENN, the temperature response error in the FEM simulation between Experiments 1 and 2 is close, and fewer data (Experiment 2) could also effectively predict the temperature response. A 3-cm-long SUS420 stainless needle was inserted into the in vitro porcine liver tissue for heating, and a non-ferromagnetic material R-type thermocouple monitored the temperature, as in the case of previous works (Tai et al , 2014; Wang et al , 2016). The results of the temperature prediction at two different coil currents used for the actual conditions of verification are shown in Figure 7.…”

Section: Resultsmentioning

confidence: 99%

A neural network identifier for electromagnetic thermotherapy systems

Tai

Wang

Hsu

2017

COMPEL

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Purpose This study aims to establish a dynamic process model of an electromagnetic thermotherapy system (ETS) to predict the temperature of a thermotherapy needle. Design/methodology/approach The model is used for real-time predicting the static and dynamic responses of temperature and can therefore provide a valuable analysis for system monitoring. Findings The electromagnetic thermotherapy process is a nonlinear problem in which the system identification is implemented by a neural network identifier. It can simulate the input/output relationship of a real system with an excellent approximation ability to uncertain nonlinear system. A system identifier for an ETS is analyzed and selected with recurrent neural networks models to deal with various treatment processes. Originality/value The Elman neural network (ENN) prediction model on ETS proposed in this study is an easy and feasible method. Comparing two situations of inputs with more and fewer data, both are trained to present low mean squared error, and the temperature response error appears within 15 per cent. The ENN, with the advantages of simple design and stable efficacy, is useful for establishing the temperature prediction model to ensure the security in the thermotherapy.

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“…[49] Deep-magnetic-field generation by the new coil design provided 3.527 millitesla at 10 cm deep distance from the coil. [50] In addition, MPI has the ability to guide the movement of magnetic micro/nanoparticles by generating a magnetic gradient field. [51] The feasibility to couple monitoring system with MPI as an MPI-based navigation system to visualize MNPs in a 3D volume further augments its potential for clinical translation.…”

Section: Magnetic Navigation (Mn)mentioning

confidence: 99%

Advances in Magnetic Nanoparticle‐Mediated Cancer Immune‐Theranostics

Cheng

Tsao

Chiang

et al. 2020

Adv Healthcare Materials

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Cancer immunotherapy is a cutting‐edge strategy that eliminates cancer cells by amplifying the host's immune system. However, the low response rate and risks of inducing systemic toxicity have raised uncertainty in the treatment. Magnetic nanoparticles (MNPs) as a versatile theranostic tool can be used to target delivery of multiple immunotherapeutics and monitor cell/tissue responses. These capabilities enable the real‐time characterization of the factors that contribute to immunoactivity so that future treatments can be optimized. The magnetic properties of MNPs further allow the implementation of magnetic navigation and magnetic hyperthermia for boosting the efficacy of immunotherapy. The multimodal approach opens an avenue to induce robust immune responses, minimize safety issues, and monitor immune activities simultaneously. Thus, the object of this review is to provide an overview of the burgeoning fields and to highlight novel technologies for next‐generation immunotherapy. The review further correlates the properties of MNPs with the latest treatment strategies to explore the crosstalk between magnetic nanomaterials and the immune system. This comprehensive review of MNP‐derived immunotherapy covers the obstacles and opportunities for future development and clinical translation.

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Deep-Magnetic-Field Generator Using Flexible Laminated Copper for Thermotherapy Applications

Cited by 15 publications

References 9 publications

Induction Heating in Domestic Cooking and Industrial Melting Applications: A Systematic Review on Modelling, Converter Topologies and Control Schemes

Induction Heating in Domestic Cooking and Industrial Melting Applications: A Systematic Review on Modelling, Converter Topologies and Control Schemes

A neural network identifier for electromagnetic thermotherapy systems

Advances in Magnetic Nanoparticle‐Mediated Cancer Immune‐Theranostics

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