DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Examiner’s Note
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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, 14-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bourlion et al. (US 2020/0324408), herein referred to as Bourlion, and in view of Hokstad (US 11,789,177).
Regarding claim 1, Bourlion discloses a method implemented by a system (¶82 and figure 1) comprising one or more processors (37, 50) for penetrating an anatomic structure (1) (figures 5-12), the method comprising causing a drilling portion (26) (¶128) to penetrate the anatomic structure (1) (figures 5-12), receiving data indicative of electrical conductivity (¶134) sensed by the drilling portion (26) as the drilling portion (26) penetrates the anatomic structure (1), and causing, if the breach condition is detected (¶157), the drilling portion (26) to stop or modify penetration of the anatomic structure (1) (¶185, ¶186, ¶268).
Yet, Bourlion lacks a detailed description on using a probabilistic perforation detection algorithm to probabilistically detect a breach condition based on the data.
However, Hokstad teaches using a probabilistic perforation detection algorithm (e.g. Bayesian-based perforation detection algorithm) (claim 1) to probabilistically detect a breach condition based on the data (claim 1).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide Bourlion’s method with using a probabilistic perforation detection algorithm to probabilistically detect a breach condition based on the data as taught by Hokstad, since such a modification would provide a specific type of statistical computation in updating the probability based on data.
Regarding claim 2, the modified Bourlion’s method has wherein using the probabilistic perforation detection algorithm to probabilistically detect the breach condition based on the data comprises using the Bayesian-based perforation detection algorithm (claim 1 of Hokstad) to probabilistically detect a time instant when a probability distribution of a time series changes (claim 1 of Hokstad).
Regarding claim 3, the modified Bourlion’s method has wherein using the Bayesian-based perforation detection algorithm to probabilistically detect the time instant when the probability distribution of the time series changes comprising using the Bayesian-based perforation detection algorithm (claim 1 of Hokstad) to probabilistically detect the time instant when a run length associated with the data drops to zero (claim 1 of Hokstad).
Regarding claim 14, the modified Bourlion’s method has wherein the probabilistic perforation detection algorithm comprises a Bayesian-based perforation detection algorithm (claim 1 of Hokstad), and wherein using the Bayesian based perforation detection algorithm (claim 1 of Hokstad) to probabilistically detect the breach condition based on the data does not require filtering of the data or prior calibration (claim 1 of Hokstad).
Regarding claim 15, the modified Bourlion’s method has further comprising: determining at least one of an entry point into the anatomic portion or a trajectory along which the drilling portion (26 of Bourlion) penetrates the anatomic structure (1 of Bourlion) (figures 5-12 of Bourlion), and causing a robot arm (11 of Bourlion) coupled to the drilling portion (26 of Bourlion) to position the drilling portion (26 of Bourlion) in alignment with the at least one of the entry point or the trajectory (figures 5-12 of Bourlion).
Regarding claim 16, the modified Bourlion’s method has wherein the robot arm (11 of Bourlion) is coupled to the drilling portion (26 of Bourlion) via a power drill unit (¶128 and ¶134 of Bourlion) mounted on a distal end of the robot arm (11 of Bourlion) (figure 1 of Bourlion), the power drill unit (¶128 and ¶134 of Bourlion) configured to (i.e. capable of) transmit rotary motion to the drilling portion (figure 5-12 of Bourlion).
Regarding claim 17, the modified Bourlion’s method has wherein causing the drilling portion to penetrate the anatomic structure comprises causing a power drill unit (¶128 and ¶134 of Bourlion) coupled to the drilling portion (26 of Bourlion) to transmit rotary motion to the drilling portion (26 of Bourlion).
Regarding claim 18, Bourlion discloses a system (10) (figure 1) for penetrating an anatomic structure (1) (figures 5-12), the system (10) comprising a drilling portion (26) configured to (i.e. capable of) sense electrical conductivity (¶127) as the drilling portion penetrates the anatomic structure (1) (figures 5-12), and a controller (37, 50) operatively coupled to the drilling portion (26) (figure 1), the controller (37, 50) programmed to: cause the drilling portion (26) to penetrate the anatomic structure (1) (figures 5-12), receive data indicative of electrical conductivity sensed by the drilling portion (26) (¶157) as the drilling portion (26) penetrates the anatomic structure (1), and cause, if the breach condition is detected (¶157), the drilling portion (26) to stop or modify penetration of the anatomic structure (1) (¶185, ¶186, ¶268).
Yet, Bourlion lacks a detailed description on using a probabilistic perforation detection algorithm to probabilistically detect a breach condition based on the data.
However, Hokstad teaches using a probabilistic perforation detection algorithm (e.g. Bayesian-based perforation detection algorithm) (claim 1) to probabilistically detect a breach condition based on the data (claim 1).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide Bourlion’s system with using a probabilistic perforation detection algorithm to probabilistically detect a breach condition based on the data as taught by Hokstad, since such a modification would provide a specific type of statistical computation in updating the probability based on data.
Regarding claim 20, the modified Bourlion’s system has further comprising: a robot arm (11) (figure 1), and a power drill unit (¶128 and ¶134 of Bourlion) mounted on the robot arm (11) (figure 1), the power drill unit (¶128 and ¶134 of Bourlion) operatively coupled to the controller (37, 50) and configured to (i.e. capable of) transmit rotary motion to the drilling portion (26) to penetrate the anatomic structure (1).
Allowable Subject Matter
Claims 4-13 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/SI MING KU/Primary Examiner, Art Unit 3775
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