Systems and methods for phase predictive impedance loss model calibration and compensation

US9480523B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9480523-B2
Application numberUS-201213360306-A
CountryUS
Kind codeB2
Filing dateJan 27, 2012
Priority dateJan 27, 2012
Publication dateNov 1, 2016
Grant dateNov 1, 2016

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Abstract

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The systems and methods of the present disclosure calibrate impedance loss model parameters associated with an electrosurgical system and compensate for impedance losses in an electrosurgical system using the calibrated impedance loss model parameters. A computer system stores voltage and current sensor data for different test loads and calculates impedance values for each test load. The computer system predicts a phase value for each test load using a respective load impedance value. The computer system back calculates impedance loss model parameters based upon the voltage and current sensor data, the predicted phase values, and the impedance values of the test loads. During operation, the electrosurgical device senses a voltage and a current, predicts a phase value based upon the sensed voltage and current, and calculates metrics at the tissue site based upon the sensed voltage and current, the predicted phase value, and the impedance loss model parameters.

First claim

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What is claimed is: 1. A method of compensating for losses in an electrosurgical device, comprising: sensing a voltage and a current of an electrosurgical signal generated and applied to a tissue site by the electrosurgical device to obtain a sensed voltage and a sensed current; calculating an impedance value based upon the sensed voltage and the sensed current; evaluating a third-order polynomial function of the impedance value to estimate a phase value; calculating at least one metric at the tissue site based upon the sensed voltage, the sensed current, the estimated phase value, and at least one impedance loss model parameter associated with the electrosurgical device; and controlling a power level of the electrosurgical signal based on the at least one metric. 2. The method of claim 1 , wherein calculating the at least one metric at the tissue site includes: converting the sensed voltage to a complex voltage value based upon the estimated phase value; converting the sensed current to a complex current value based upon the estimated phase value; and calculating at least one metric at the tissue based upon the complex voltage value, the complex current value, and the at least one impedance loss model parameter. 3. The method of claim 1 , wherein the at least one impedance loss model parameter includes a source impedance parameter and a leakage impedance parameter. 4. The method of claim 3 , wherein calculating the at least one metric at the tissue site includes: multiplying the sensed current by the source impedance parameter to obtain a source impedance voltage value; subtracting the source impedance voltage value from the sensed voltage to obtain a load voltage value; dividing the load voltage value by the leakage impedance parameter to obtain a leakage current value; and subtracting the leakage current value from the sensed current to obtain a load current value. 5. The method of claim 1 , wherein the at least one metric includes a load voltage and a load current. 6. The method of claim 1 , wherein the at least one metric includes power. 7. The method of claim 1 , wherein the at least one metric includes a load impedance. 8. An electrosurgical device, comprising: at least one electrode that applies electrosurgical energy to tissue; an electrosurgical energy output stage electrically coupled to the at least one electrode through a transmission line, the electrosurgical energy output stage configured to generate electrosurgical energy; a voltage sensor and a current sensor coupled to the electrosurgical energy output stage, the voltage sensor configured to sense a voltage of the electrosurgical energy to obtain a sensed voltage and the current sensor configured to sense a current of the electrosurgical energy to obtain a sensed current; a memory that stores at least one impedance loss model parameter associated with the transmission line; and a processor coupled to the voltage sensor, the current sensor, and the memory, the processor configured to: calculate an impedance value based upon the sensed voltage and the sensed current; evaluating a third-order polynomial function of the impedance value to estimate a phase value; retrieve the at least one impedance loss model parameter; calculate at least one metric at the tissue based upon the sensed voltage value, the sensed current value, the estimated phase value, and the at least one impedance loss model parameter; and control a power level of the electrosurgical energy based on the at least one metric. 9. The electrosurgical device of claim 8 , wherein the at least one metric includes a load voltage and a load current. 10. The electrosurgical device of claim 8 , wherein the at least one metric includes power. 11. The electrosurgical device of claim 8 , wherein the at least one metric includes a load impedance. 12. The electrosurgical device of claim 8 , wherein the at least one impedance loss model parameter includes a source impedance parameter and a leakage impedance parameter.

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What does patent US9480523B2 cover?
The systems and methods of the present disclosure calibrate impedance loss model parameters associated with an electrosurgical system and compensate for impedance losses in an electrosurgical system using the calibrated impedance loss model parameters. A computer system stores voltage and current sensor data for different test loads and calculates impedance values for each test load. The comput…
Who is the assignee on this patent?
Heckel Donald W, Covidien Lp
What technology area does this patent fall under?
Primary CPC classification A61B18/1206. Mapped technology areas include Human Necessities.
When was this patent published?
Publication date Tue Nov 01 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).