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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 15 December 2025 has been entered.
Formal Matters
Claims 6, 17-20, 22, and 25 are cancelled. Claims 1-3, 5, 7-9, 11, 13-15, 21, 23, and 24 are currently amended. New claims 26 and 27 are added. Claims 1-5, 7-16, 21, 23, 24, 26, and 27 are pending and under examination.
Rejections/Objections Withdrawn
The rejection of claim 6 under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, is withdrawn in light of the cancellation of the claim.
The rejection of claims 1-16, 21, 23, and 24 under 35 U.S.C. 102(a)(1) as being anticipated by Shelton et al., US 20190125458 (2 May 2019) is withdrawn in light of Applicant’s amendments. However, a new rejection is set forth below.
Response to Arguments
Regarding the anticipation rejection, Applicant argues that Applicant does not concede that the examiner has established a prima facie case of anticipation regarding the reliance on FIG 204 of Shelton and ¶1681. Applicant argues that no evidence was demonstrated that the shape (icon) displayed on FIG 204 was received from the memory of the end effector. Applicant’s arguments have been fully considered, but it is not persuasive. As an initial matter, Applicant is arguing a now-deleted limitation of the claims. Applicant has deleted shape as a feature characteristic stored by the end effector memory. Additionally, Applicant is making an argument related to a method of use of the end effector and the memory (“demonstrated that the shape (icon) displayed on FIG 204 was received from the memory of the end effector”). There is no requirement for the examiner to show a method of use. Rather, the examiner need only show that the end effector (as presently claimed) is “adapted to be coupled to the robot arm, the end effector retaining a tool, the end effector comprising a memory storing a mechanical parameter of the end effector comprising at least one of a size dimension, a weight, or a center of mass of the end effector …” Shelton expressly teaches that each modular component (e.g., handle 8204, modular adapter 8206, end effector 8208, staple cartridge 8210, etc.) may comprise a processor and a memory unit (not shown) that stores its respective serial number (¶1681). Applicant’s arguments have been fully considered in light of the amendments. Accordingly, the rejection of record is withdrawn in light of Applicant’s amendments and a modified rejection is set forth below.
Objections/Rejections
Claim Rejections - 35 USC § 103
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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-5, 7-16, 21, 23, 24, 26, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Shelton et al., US 20190125458 (2 May 2019) (previously cited of record) in view of Harris et al., US 20190200981 (4 July 2019).
Regarding amended independent claim 1, Shelton teaches a robotic surgical system (FIGs 255, 256, 13800, ¶1954), comprising:
a robot arm (13830/13840/13850; FIGs 255, 256);
an end effector (tool, ¶1954) adapted to be coupled to the robot arm, the end effector retaining a tool (¶1954), and
a processor (13822) configured to send the mechanical parameter (¶1956, “processor 13822 configured to run an algorithm”; ¶1972, the algorithm configured “to send information”, “for example, identification of the tool attachment, force data, and position”) and
a system controller (FIG 261, controller 13862, ¶1968) operably connected to the robot arm (FIG 261, 13861; ¶1968) for positioning the tool with respect to a patient (FIGs 258),
the system controller (FIG 261, 13862) being configured to (FIG 258, algorithm 13500):
determine whether the end effector is coupled to the robot arm (¶1969, tool attachment);
receive data sent by the end effector (¶1972)
identify the end effector using the unique identifier of the end effector (¶1972); and
adjust operation of the surgical system based on the data received from the end effector (¶1973).
Shelton does not expressly teach the end effector comprising a memory storing a mechanical parameter of the end effector comprising at least one of a size dimension, a weight, or a center of mass of the end effector.
However, Shelton expressly teach that “each modular component (e.g., handle 8204, modular adapter 8206, end effector 8208, staple cartridge 8210, etc.) may comprise a processor and a memory unit (not shown) that stores its respective serial number”) (¶1681).
Harris teaches end effector assemblies comprising end effector memory (23136) internal databases where the data may comprise sizes (¶734).
Harris also teaches that the computed response of the physical system takes into account properties like mass, inertial, viscous friction, inductance resistance, etc., to predict what the states and outputs of the physical system will be by knowing the input (¶452).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine the teachings of Shelton and Harris given that the prior art included each element claimed, although not necessarily in a single reference. Shelton and Harris teach in the same field of endeavor, robotic surgical systems comprising processors, controllers, and end-effectors. Although, Shelton the claimed base robotic surgical system (robotic arm, end effectors, end effectors comprising memory and data including serial numbers, processors, and system controllers), Shelton does not expressly disclose the end effector comprising a memory storing a mechanical parameter of the end effector comprising at least one of a size dimension, a weight, or a center of mass of the end effector.
Harris specifically addresses end effector assemblies comprising end effector memory (23136) internal databases where the data may comprise size dimensions (¶734). Harris teaches “end effector assembly 23130 may transmit the detected parameter to a control circuit (e.g., 23112 and/or 23122) associated with another surgical instrument 23102 component, for example, the handle assembly 23110 and/or the shaft assembly 23120. In such an aspect, that other surgical instrument component control circuit (e.g., 23112 and/or 23122). Furthermore, according to various aspects, the shaft assembly 23120 of the surgical instrument 23102 may include a sensor 23124 configured to detect a parameter associated with a function (e.g., rotation, articulation, etc.) of the shaft assembly 23120 and to transmit the detected parameter to a control circuit (e.g., 23112) similarly configured to perform the various aspects of the end effector control circuit 23132 as described above. In end, the situationally aware surgical instrument 23102 may be configured to, for example, alert its user of a discrepancy (e.g., via a user interface 23138 of the end effector assembly 23130, via a user interface (e.g., 23128 and/or 23118) of another surgical instrument 23102 component, for example, the shaft assembly 23120 and/or the handle assembly 23110, and/or via a user interface 23148 and/or 23158 associated with a surgical hub 23140 coupled to the surgical instrument 23102). For example, the discrepancy may include that a detected parameter exceeds a preferred/ideal parameter and/or a preferred/ideal parameter range associated with those sizes and/or types of staples or those expected tissues and/or tissue types. As a further example, the situationally aware surgical instrument 23102 may be configured to control a surgical instrument 23102 function based on the discrepancy. In accordance with at least one aspect, the situationally aware surgical instrument 23102 may prevent a surgical function based on a discrepancy.” (¶734).
Because Shelton includes an end-to-end connected surgical robotic system with end effectors comprising memory (¶¶1972, 1975) that store at least serial numbers of the end effectors, a person of ordinary skill in the art, seeking to provide more detailed data in a real-time setting would reasonably consult Harris’s more detailed end effector memory storage solution. Harris’s more detailed end effector memory storage solution can be incorporated alongside Shelton’s robotic surgical system (same general robotic surgical system, robotic arm, end effector retaining a tool, the end effector comprising a memory storing data, and an algorithmically configurable system controller) using known assembly methods without redesigning Shelton’s ‘458’s core device components.
Because the references address the same engineering problem (robotically integrated hardware and software within the boundaries of a given operating suite) and the proposed modifications are mechanically compatible and implemented by routine engineering practices (adding more data to an on-device memory in an end effector), a person of ordinary skill in the art before the effective filing date of the claimed invention would have had a reasonable expectation of success in combining these teachings.
Regarding currently amended claim 2, Shelton modified by Harris teaches the system of claim 1, as set forth above.
Shelton teaches wherein the data received from the end effector further comprises at least one of a unique identifier, a version identifier, a class identifier, manufacturing information, duration of use, lifetime information, service history, or sterilization history (¶¶1972, 1975).
Regarding currently amended claim 3, Shelton modified by Harris teaches the system of claim 1, as set forth above.
Shelton teaches wherein the system controller is further configured to determine a parameter regarding the end effector, provided that the determined parameter is not received from the end effector (¶1966). See also, Harris (¶734).
Regarding claim 4, Shelton modified by Harris teaches the system of claim 3, as set forth above.
Harris wherein the determined parameter is retrieved from a database (¶734).
Regarding currently amended claim 5, Shelton modified by Harris teaches the system of claim 3, as set forth above.
Harris teaches wherein the determined parameter is detected by the system controller (¶734).
Regarding currently amended claim 7, Shelton modified by Harris teaches the system of claim 3, as set forth above.
Shelton teaches wherein the system controller is further configured to determine the determined parameter regarding the end effector before the end effector is coupled to the robot arm (¶¶1972, 1975).
Regarding currently amended claim 8, Shelton modified by Harris teaches the system of claim 3, as set forth above.
Shelton teaches wherein the system controller is further configured to determine the determined parameter regarding the end effector after the end effector is coupled to the robot arm (¶¶1972, 1975).
Regarding currently amended claim 9, Shelton modified by Harris teaches the system of claim 1, as set forth above.
Shelton teaches wherein the operation adjustment by the system controller is at least one of an adjustment to the robot arm based on an estimated load and/or force exerted by the end effector weight or center of mass, an adjustment to the robot arm to allow for optimal joint configuration of the robot arm based on tool trajectory, or an adjustment to calibration data (¶1973).
Regarding claim 10, Shelton modified by Harris teaches the system of claim 9, as set forth above.
Harris wherein the adjustment to calibration data (¶655) reflects a size dimension of the end effector (¶734).
Regarding currently amended claim 11, Shelton modified by Harris teaches the system of claim 1, as set forth above.
Shelton teaches a related embodiment (FIG 204) wherein the system controller (¶1684) is further configured to determine manufacturing information of the end effector (¶1685), obtain one or more of end effector or tool geometry (¶1681), and adjust the robot arm using the one or more of end effector or tool geometry to improve accuracy of the surgical system (FIG 204; ¶1687).
Shelton teaches multiple embodiments of connected robotic surgical systems (¶5). One of ordinary skill in the art would be able to utilize various aspects of the different embodiments and incorporate them into the base system components, particularly when the components are software-based, as they are in configured system controllers. Additionally, Harris supports these additional embodiments by teaching that the end effector assembly may be further configured to receive data from an internal database and/or an external database, such as a cloud or surgical hub database, throughout the course of the surgical procedure (¶734).
Regarding claim 12, Shelton modified by Harris teaches the system of claim 11, as set forth above.
Shelton teaches wherein the tool geometry is at least one of a distance of a tool from a distal end of the robot arm, an angle of a tool axis relative to the distal end of the robot arm, or a depth a tool tip will protrude from the end effector (¶1155 “surgical hub could be configured to automatically calculate sizes or dimensions of structures (or distances between structures) during a surgical procedure by comparing the structures to markings affixed to devices that are intended to be placed within the field of view (FOV) of the medical imaging device during a surgical procedure. The markings can represent a known scale, which can then be utilized to make measurements by comparing the unknown measured length to the known scale”).
Regarding currently amended claim 13, Shelton modified by Harris teaches the system of claim 1, as set forth above.
Shelton teaches wherein the system controller is further configured to, based on the data received from the end effector, determine at least one of use, service, or replacement data for the end effector (¶¶1972, 1975).
Regarding currently amended claim 14, Shelton modified by Harris teaches the system of claim 13, as set forth above.
Shelton teaches wherein the system controller is further configured to determine if a lifetime maximum duration of use will be exceeded during a procedure (¶¶1678-1679).
Shelton teaches multiple embodiments of connected robotic surgical systems (¶5). One of ordinary skill in the art would be able to utilize various aspects of the different embodiments and incorporate them into the base system components, particularly when the components are software-based, as they are in configured system controllers. Additionally, Harris supports these additional embodiments by teaching that the end effector assembly may be further configured to receive data from an internal database and/or an external database, such as a cloud or surgical hub database, throughout the course of the surgical procedure (¶734).
Regarding currently amended claim 15, Shelton modified by Harris teaches the system of claim 1, as set forth above.
Shelton teaches wherein the system controller is further configured to write updated data to the memory of the end effector (¶1585).
Shelton teaches multiple embodiments of connected robotic surgical systems (¶5). One of ordinary skill in the art would be able to utilize various aspects of the different embodiments and incorporate them into the base system components, particularly when the components are software-based, as they are in configured system controllers. Additionally, Harris supports these additional embodiments by teaching that the end effector assembly may be further configured to receive data from an internal database and/or an external database, such as a cloud or surgical hub database, throughout the course of the surgical procedure (¶734).
Regarding claim 16, Shelton modified by Harris teaches the system of claim 15, as set forth above.
Shelton teaches wherein the updated data is based on at least one of use of the end effector, a unique identifier of the robot arm to which the end effector was coupled, a most recently performed procedure, sterilization history, or service update (¶1592).
Regarding currently amended independent claim 21, Shelton teaches a robotic surgical system (FIGs 255, 256, 13800, ¶1954), comprising:
a robot arm (13830/13840/13850; FIGs 255, 256);
an end effector (tool, ¶1954) configured to be coupled to the robot arm at a first end and to retain a tool at a second end (¶1954),
the end effector (tool, ¶1954).
a processor (13822) configured to send data (¶1956),
a system controller (FIG 261, controller 13862, ¶1968) operably connected to the robot arm (FIG 261, 13861; ¶1968) for positioning the tool with respect to a patient (FIGs 258),
the system controller (FIG 261, 13862) being configured to (FIG 258, algorithm 13500):
determine whether the end effector is coupled to the robot arm (¶1969, tool attachment);
receive the data including the mechanical parameter from the end effector (¶1972, for example, identification of the tool attachment)
identify the end effector (¶1972); and
adjust operation of the surgical system based on the data received from the end effector (¶1973).
Shelton at embodiment 13800 does not expressly teach the end effector comprising a memory storing data about the end effector a mechanical parameter of the end effector.
However, embodiment FIG 204 of Shelton teaches the memory unit of each modular component stores its usage parameter and/or usable life metric (¶1684).
Shelton at embodiment 13800 does not expressly teach that the end effector is coupled to the robot arm via completion of an electrical circuit between mating contacts of the end effector and the robot arm.
However, Shelton teaches embodiment FIGs 213 and 214 where “tool mounting portion 12250 also includes electrical contacts 12262, and the robotic tool 12226 includes electrical contacts 12264 positioned and structured to mate with the electrical contacts 12262 on the tool mounting portion 12250. Electrical signals can be communicated between the robotic tool 12226 and the robot 12222 (FIG 213) via the mating electrical contacts 12262, 12264. Mechanical control parameters from the robotic tool 12262 can be communicated to the robot 12222 via the electrical contacts 12262, 12264” (¶1765).
Shelton at embodiment 13800 does not expressly teach that data including the mechanical parameter from the end effector is received via wired communication between the contacts.
However, Shelton teaches embodiment FIG 215 where electrical contacts 12262 of the tool mounting portion 12250 facilitate data transmission (¶1766).
Shelton teaches multiple embodiments of connected robotic surgical systems (¶5). One of ordinary skill in the art would be able to utilize various aspects of the different embodiments and incorporate them into the base system components, particularly when the components are software-based, as they are in configured system controllers. Additionally, Harris supports these additional embodiments by teaching that the end effector assembly may be further configured to receive data from an internal database and/or an external database, such as a cloud or surgical hub database, throughout the course of the surgical procedure (¶734).
Shelton does not teach wherein the data about the end effector stored in the memory of the end effector includes at least one of a mechanical parameter comprising a size dimension, a weight, or a center of mass.
However, Shelton expressly teach that “each modular component (e.g., handle 8204, modular adapter 8206, end effector 8208, staple cartridge 8210, etc.) may comprise a processor and a memory unit (not shown) that stores its respective serial number”) (¶1681).
Harris teaches end effector assemblies comprising end effector memory (23136) internal databases where the data may comprise sizes (¶734).
Harris also teaches that the computed response of the physical system takes into account properties like mass, inertial, viscous friction, inductance resistance, etc., to predict what the states and outputs of the physical system will be by knowing the input (¶452).
It would have been obvious to one having ordinary skill in the art as of the effective filing date of the invention to combine the teachings of Shelton and Harris given that the prior art included each element claimed, although not necessarily in a single reference. Shelton and Harris teach in the same field of endeavor, robotic surgical systems comprising processors, controllers, and end-effectors. Although, Shelton the claimed base robotic surgical system (robotic arm, end effectors, end effectors comprising memory and data including serial numbers, processors, and system controllers), Shelton does not expressly disclose the end effector comprising a memory storing a mechanical parameter of the end effector comprising at least one of a size dimension, a weight, or a center of mass of the end effector.
Harris specifically addresses end effector assemblies comprising end effector memory (23136) internal databases where the data may comprise size dimensions (¶734). Harris teaches “end effector assembly 23130 may transmit the detected parameter to a control circuit (e.g., 23112 and/or 23122) associated with another surgical instrument 23102 component, for example, the handle assembly 23110 and/or the shaft assembly 23120. In such an aspect, that other surgical instrument component control circuit (e.g., 23112 and/or 23122). Furthermore, according to various aspects, the shaft assembly 23120 of the surgical instrument 23102 may include a sensor 23124 configured to detect a parameter associated with a function (e.g., rotation, articulation, etc.) of the shaft assembly 23120 and to transmit the detected parameter to a control circuit (e.g., 23112) similarly configured to perform the various aspects of the end effector control circuit 23132 as described above. In end, the situationally aware surgical instrument 23102 may be configured to, for example, alert its user of a discrepancy (e.g., via a user interface 23138 of the end effector assembly 23130, via a user interface (e.g., 23128 and/or 23118) of another surgical instrument 23102 component, for example, the shaft assembly 23120 and/or the handle assembly 23110, and/or via a user interface 23148 and/or 23158 associated with a surgical hub 23140 coupled to the surgical instrument 23102). For example, the discrepancy may include that a detected parameter exceeds a preferred/ideal parameter and/or a preferred/ideal parameter range associated with those sizes and/or types of staples or those expected tissues and/or tissue types. As a further example, the situationally aware surgical instrument 23102 may be configured to control a surgical instrument 23102 function based on the discrepancy. In accordance with at least one aspect, the situationally aware surgical instrument 23102 may prevent a surgical function based on a discrepancy.” (¶734).
Because Shelton includes an end-to-end connected surgical robotic system with end effectors comprising memory (¶¶1972, 1975) that store at least serial numbers of the end effectors, a person of ordinary skill in the art, seeking to provide more detailed data in a real-time setting would reasonably consult Harris’s more detailed end effector memory storage solution. Harris’s more detailed end effector memory storage solution can be incorporated alongside Shelton’s robotic surgical system (same general robotic surgical system, robotic arm, end effector retaining a tool, the end effector comprising a memory storing data, and an algorithmically configurable system controller) using known assembly methods without redesigning Shelton’s ‘458’s core device components.
Because the references address the same engineering problem (robotically integrated hardware and software within the boundaries of a given operating suite) and the proposed modifications are mechanically compatible and implemented by routine engineering practices (adding more data to an on-device memory in an end effector), a person of ordinary skill in the art before the effective filing date of the claimed invention would have had a reasonable expectation of success in combining these teachings.
Regarding claim 23, Shelton modified by Harris teaches the system of claim 21, as set forth above.
Shelton teaches wherein the controller is further configured to send updated data (¶1585) comprising duration of use, lifetime information, service history, or sterilization history to the end effector (¶1592).
Harris teaches data to be stored in internal databases in end effector memory (¶734).
Regarding claim 24, Shelton modified by Harris teaches the system of claim 21, as set forth above.
Shelton teaches wherein the system controller is further configured to send updated data comprising at least one of use of the end effector, a unique identifier of a robot arm to which the end effector was coupled, a most recently performed procedure, sterilization history, or service update(¶¶1972, 1975).
Harris teaches data to be stored in internal databases in end effector memory (¶734).
Regarding new claim 26, Shelton modified by Harris teaches the system of claim 21, as set forth above.
Shelton teaches wherein the operation adjustment by the system controller is at least one of an adjustment to the robot arm based on:
an estimated load and/or force exerted by the end effector weight;
an estimated load and/or force exerted by the end effector center of mass; or
a tool trajectory related to the end effector size dimension (¶1973).
Regarding new claim 27, Shelton modified by Harris teaches the system of claim 21, as set forth above.
Shelton teaches (FIG 204) wherein the system controller (¶1684) is further configured to determine manufacturing information of the end effector (¶1685), obtain one or more of end effector or tool geometry (¶1681), and adjust the robot arm using the one or more of end effector or tool geometry to improve accuracy of the surgical system (FIG 204; ¶1687).
Conclusion
No claim is allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHERIE M POLAND whose telephone number is (703)756-1341. The examiner can normally be reached M-W (9am-9pm CST) and R-F (9am-3pm CST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jackie Ho can be reached at 571-272-4696. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHERIE M POLAND/Examiner, Art Unit 3771
/SHAUN L DAVID/Primary Examiner, Art Unit 3771