DETAILED ACTION
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on April 24, 2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to the rejection(s) of the amended claim(s) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is set forth below.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3, and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (US 2006/0047240) in view of Wikipedia (NPL “Wikipedia: Kalman Filter”) as evidenced by Olde et al. (US 2014/0231319).
Regarding claims 1 and 3, Kumar et al. (henceforth Kumar) discloses a method for determining and controlling the internal body pressure in medical methods comprising the steps of: pumping a fluid by a pumping device via a supply line (4) into a body cavity (11), wherein the fluid is able to flow through a second line (12) out of the body cavity or wherein the fluid is able to flow through a separate skin incision of the body cavity (paragraph [0022]), controlling a pump (inflow pump 3) in the pumping device, the pump having an input speed of rotation controlling pressure; measuring the pressure in the supply line using a pressure sensor (5; paragraph [0087]), wherein the pressure measured by the pressure sensor is a measurable state variable for calculating an observer error for a the state observer and controls the input speed of the pump by means of this estimated value (the system utilizes pressure feedback to maintain the pressure within the cavity via controlling of the inflow pump based upon pressure readings in the fluid line, paragraph [0027]; also see paragraphs [0097] and [0100] which set forth the use of a feedback control system to maintain cavity pressure by altering the input speed of the input pump). Kumar does not explicitly state wherein the feedback mechanism is a state-space model or that an estimate of the pressure controls the pump speed via a recursive algorithm based on a Kalman Filter.
Wikipedia teaches (verified page history via Wayback machine that the equations and explanation were present as of September 30, 2011) a known recursive algorithm as the definition of a Kalman filter, for a control system comprising the steps of:
Calculating a Kalman gain based on the predicted state covariance – the gain is described by Kk which uses the predicted estimated covariance Pk|k-1.
Updating the state covariance using the Kalman gain - the update is a new estimate using the Kalman gain, “the current a priori prediction is combined with current observation information to refine the state estimate”. See “Update” portion of Kalman filter article which includes the gain value.
Calculating an updated state estimate based on the Kalman gain and an observer error said updated state being used as a control output for a system (e.g., the pump system of Kumar) – the state estimate is updated, as above, using the optimal Kalman gain and the observer error, which is defined as the state estimate Xk|k.
Therefore, Wikipedia explicitly teaches that the Kalman filter algorithm is known to be a recursive algorithm which updates a Kalman gain based on predicted covariance, updates the state covariance using that gain, and calculates an updated state estimate based on the gain and the observer error as claimed. It is noted that this control algorithm is standard in systems control textbooks and Wikipedia is being relied on to provide an easily citable example of such a known control system algorithm.
Wikipedia teaches the general knowledge of the recursive algorithm but fails to explicit state that it is used in medical devices. However, Olde teaches the use of this algorithm to use data from the pressure sensor of a medical fluid system to control (paragraphs [0025] and [0151]-[0153]).
Therefore, it would have been obvious to one of ordinary skill in the art to modify the feedback control system of Kuman to utilize the Kalman filter algorithm of Wikipedia so as to provide a means for providing a clean pressure signal from noisy measurements, e.g., biological signals present in the cavity which might be present in the sensor data. The Kalman filter and algorithm track the desired pressure signal more closely while reducing noise which provides better feedback signals for pump control. Therefore, it provides for a smoother, more reliable estimate of the actual cavity pressure than raw sensor output can provide. This features prevents the pump controller from over-compensating for transient spikes or dips. Finally, for these reasons, the Kalman algorithm provides for the best linear unbiased estimate of the state given past data which is what one of ordinary skill would desire when providing a signal to control a fluid pump. Olde teaches that such an algorithm is known for use in medical fluid control systems using pressure sensor (4a-4d) data (see also paragraphs [0065] and [0138]), and it would therefore be obvious to apply this control algorithm to the pump of Kumar for the reasons set forth above, since it is known for use in medical systems for smoothing sensor data to use to control the system during a procedure.
Regarding claim 5, Kumar further discloses wherein the fluid is a liquid (paragraph [0087], saline is utilized).
Claim 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kumar in view of Wikipedia as evidenced by Olde, and further in view of Kadan (US 2004/0082915).
Regarding claim 4, Kumar/Wikipedia/Olde teach the claimed invention substantially as set forth above for claims 1 and 7, but do not explicitly disclose wherein the fluid is a gas used by an insufflator.
Kadan teaches an arthroscopy and lavage system wherein a body cavity (abdomen) is distended via the introduction of a gas (CO2; paragraph [0021]) via an insufflator.
It would have been obvious to one of ordinary skill in the art at the time of filing to modify the distension system of Kumar/Wikipedia/Olde to utilize CO2 gas rather than saline as gas is well-known in the art as a reliable means of distending a body cavity and wherein pressure monitoring is a common concern during such a procedure. In this manner it would be obvious to utilize any fluid in the method of Kumar/Wikipedia/Olde.
Claim 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kumar in view of Wikipedia as evidenced by Olde, and further in view of Kumar et al. (US 2006/0122557).
Regarding claim 13, Kumar/Wikipedia/Olde teach the claimed method as set forth above for claim 1, but fail to explicitly disclose the step of reaching the selected pressure in less than 20 seconds and maintaining the selected setpoint pressure in a range of +/- 10 mmHg during use.
Kumar et al. (henceforth Kumar ‘557) teaches a medical fluid flow system which aims to utilize a pressure control system to achieve a desired set-point to maintain a pressure over time (paragraph [0090]) and which teaches reaching a target cavity pressure within 10 seconds (see e.g., paragraph [0110] which teaches reaching and maintaining a pressure value within 10 seconds) and maintaining a cavity pressure in a range between 10 mmHg during a procedure (paragraph [0101] discloses maintaining the pressure difference in a range of between 0 and 2 mmHg)
It would have been obvious to one of ordinary skill in the art at the time of filing to utilize a state-space Kalman filter model for the pump controller as it represents a well-understood feedback control mechanism which may be utilized in fluid flow systems to achieve a specific pump control function such as that disclosed by Wikipedia/Olde. In such a combination the continuous time monitoring of the pressure in the cavity may be controlled by changing pump rotation speed which is determined by the state-space model output, as set forth above for claim 1. The cavity pressure control of Kumar which is achieved via the real-time alteration of the input pump rotation speed, based on the smoothed data from the pressure sensor data from supply line, would be maintained with the use of a state-space Kalman filter model which would correct for sensed error of a cavity pressure versus a target pressure and manipulate the input pump speed to achieve and/or maintain the desired cavity pressure as set forth above. Finally, it would have been obvious to one of ordinary skill in the art at the time of filing to maintain the target pressure within a very narrow pressure range as taught by Kumar ‘557 so as to ensure the procedure proceeds as desired with the target pressure value so as to avoid unwanted complications during the procedure.
Conclusion
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/JUSTIN L ZAMORY/Examiner, Art Unit 3783
/MICHAEL J TSAI/Supervisory Patent Examiner, Art Unit 3783
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