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 .
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 5, 8, and 12-16 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Grantcharov (WO 2016/044920).
Regarding Claim 1, Grantcharov teaches the following:
A computer-implemented method, comprising:
configuring a data pipelines network ([00225] various selection methodologies for optimal parameter adjustment in pipelined recurrent neural networks used for prediction of nonlinear signals; complex-valued pipelined recurrent neural networks) between first and second surgical systems ([0027], [0098] the device middleware and hardware implements data conformity and accurate synchronization for the real-time medical or surgical data streams using network protocols for clock synchronization between the hardware units) such that:
the first and second surgical systems are configured to, during a performance of a surgical procedure on a patient, exchange information over the data pipelines network ([0027], [00142], [00147]: system may include more encoders 22 to collect feeds from local or remote data capture devices (of hardware unit 20) and exchange data. The device middleware and hardware implements data conformity and accurate synchronization for the real-time medical or surgical data streams using network protocols for clock synchronization between the hardware units), and
the first surgical system is configured to, during the performance of the surgical procedure, communicate a first data stream to the second surgical system over the data pipelines network, the first data stream including first data regarding a first measured patient parameter that the second surgical system is configured to use in performing a function during the performance of the surgical procedure ([0072], [00104] Device middleware and hardware may be provided for translating, connecting, formatting and synchronizing of independent digital data streams from source devices. The data platform may be a modular system and not limited in terms of data feeds - any measurable parameter in the OR / patient intervention areas. Also see Fig. 1 and Fig. 8, showing the surgical systems that transfer the data); and
in response to a third surgical system being connected to the data pipelines network ([00183] a synchronized multi-channel video/audio/metadata recording platform may be for use in the intraoperative environment. Development and installation of the black- box platform may be an iterative process that may involve both minor and major changes to the system.), and during the performance of the surgical procedure, reconfiguring the data pipelines network ([00145], [00183], [00247]: The processor may be reconfigurable) such that:
the first, second, and third surgical systems are configured to, during the performance of the surgical procedure on a patient, exchange information over the reconfigured data pipelines network (See Fig. 1 and Fig. 8, [00142]: system may include more encoders 22 to collect feeds from local or remote data capture devices (of hardware unit 20) and exchange data.),
the first surgical system is configured to communicate the first data stream to the second surgical system over the reconfigured data pipelines network ([0072], [00104] Device middleware and hardware may be provided for translating, connecting, formatting and synchronizing of independent digital data streams from source devices. The data platform may be a modular system and not limited in terms of data feeds - any measurable parameter in the OR / patient intervention areas. Also see Fig. 1 and Fig. 8, showing the surgical systems that transfer the data), and
the third surgical system is configured to, during the performance of the surgical procedure, communicate a third data stream to at least one of the first and second surgical systems over the reconfigured data pipelines network, the third data stream including third data regarding a third measured patient parameter that the at least one of the first and second surgical systems is configured to use in performing a function during the performance of the surgical procedure ([0064], [0076]: middleware and hardware for device-to-device translation and connection and synchronization on a private VLAN or other network. The digital data may be ingested into the encoder as streams of metadata and is sourced from an array of potential sensor types and third-party devices (open or proprietary) that are used in surgical, ICU, emergency or other clinical intervention units. These sensors and devices may be connected through middleware and/or hardware devices which may act to translate, format and/or synchronize live streams of data from respected sources.).
Regarding Claim 5, Grantcharov teaches the method of claim 1 and further teaches the following:
The method of claim 1, wherein the third data stream is communicated to the at least one of the first and second surgical systems:
in real-time ([00222] The online approach may provide a real-time tool to assist surgeons and OR teams intraoperatively), or
after a time delay so as to free real-time data capacity of the reconfigured data pipelines network during the time delay ([00225] applications of time delayed A'JNs and feedforward multi-layer perceptron networks to model nonlinear dynamical systems.).
Regarding Claim 8, Grantcharov teaches the method of claim 1 and further teaches the following:
The method of claim 1, wherein the configuring occurs during the performance of the surgical procedure ([0064], [0027]: The customizable control interface 14 and GUI (may include tablet devices, PDA's, hybrid devices, convertibles, etc.) may be used to control configuration for hardware components of unit. The device middleware and hardware implements data conformity and accurate synchronization for the real-time medical or surgical data streams using network protocols for clock synchronization between the hardware units).
Regarding Claim 12, Grantcharov teaches the method of claim 1 and further teaches the following:
The method of claim 1, wherein each of the first, second, and third surgical systems is one of a hospital network, a database, a surgical instrument, or a surgical cart (hardware units 20 may have sensors 30 (Fig. 1) installed or utilized in a surgical unit, ICU, emergency unit or clinical intervention units. Example sensors include but are not limited to: environmental sensors: i.e. temperature, moisture, humidity, etc.; acoustic sensors: i.e. ambient noise, decibel, etc.; electrical sensors: i.e. hall, magnetic, current, mems, capacitive, resistance, etc.; flow sensors: i.e. air, fluid, gas, etc.; angle/positional/displacement sensors: i.e., gyroscopes, attitude indicator, piezoelectric, photoelectric, etc.; other sensors: strain, level sensors, load cells, motion, pressure, etc.).
Regarding Claim 13, Grantcharov teaches the following:
A surgical data management system ([0021] a system, method, platform, device, and/or computer readable medium which provides comprehensive data collection of details of patient care in a surgical operating room (OR)), comprising:
a processor ([0058] the system further comprising a processor); and
a memory ([00146] Memory may include a suitable combination of any type of computer memory that is located either internally or externally) storing instructions that, when executed by the processor, cause the processor to perform operations ([00243] The computing devices may have at least one processor configured to execute software instructions stored on a computer readable tangible, non-transitory medium.) comprising:
configuring a data pipelines network ([00225] various selection methodologies for optimal parameter adjustment in pipelined recurrent neural networks used for prediction of nonlinear signals; complex-valued pipelined recurrent neural networks) between first and second surgical systems ([0027], [0098] the device middleware and hardware implements data conformity and accurate synchronization for the real-time medical or surgical data streams using network protocols for clock synchronization between the hardware units) such that:
the first and second surgical systems are configured to, during a performance of a surgical procedure on a patient, exchange information over the data pipelines network ([0027], [00142], [00147]: system may include more encoders 22 to collect feeds from local or remote data capture devices (of hardware unit 20) and exchange data. The device middleware and hardware implements data conformity and accurate synchronization for the real-time medical or surgical data streams using network protocols for clock synchronization between the hardware units), and
the first surgical system is configured to, during the performance of the surgical procedure, communicate a first data stream to the second surgical system over the data pipelines network, the first data stream including first data regarding a first measured patient parameter that the second surgical system is configured to use in performing a function during the performance of the surgical procedure ([0072], [00104] Device middleware and hardware may be provided for translating, connecting, formatting and synchronizing of independent digital data streams from source devices. The data platform may be a modular system and not limited in terms of data feeds - any measurable parameter in the OR / patient intervention areas. Also see Fig. 1 and Fig. 8, showing the surgical systems that transfer the data), and
in response to a third surgical system being connected to the data pipelines network ([00183] a synchronized multi-channel video/audio/metadata recording platform may be for use in the intraoperative environment. Development and installation of the black- box platform may be an iterative process that may involve both minor and major changes to the system.), and during the performance of the surgical procedure, reconfiguring the data pipelines network ([00145], [00183], [00247]: The processor may be reconfigurable) such that:
the first, second, and third surgical systems are configured to, during the performance of the surgical procedure on a patient, exchange information over the reconfigured data pipelines network (See Fig. 1 and Fig. 8, [00142]: system may include more encoders 22 to collect feeds from local or remote data capture devices (of hardware unit 20) and exchange data.), and
the first surgical system is configured to communicate the first data stream to the second surgical system over the reconfigured data pipelines network ([0072], [00104] Device middleware and hardware may be provided for translating, connecting, formatting and synchronizing of independent digital data streams from source devices. The data platform may be a modular system and not limited in terms of data feeds - any measurable parameter in the OR / patient intervention areas. Also see Fig. 1 and Fig. 8, showing the surgical systems that transfer the data); and
wherein the third surgical system is configured to, during the performance of the surgical procedure, communicate a third data stream to at least one of the first and second surgical systems over the reconfigured data pipelines network, the third data stream including third data regarding a third measured patient parameter that the at least one of the first and second surgical systems is configured to use in performing a function during the performance of the surgical procedure ([0064], [0076]: middleware and hardware for device-to-device translation and connection and synchronization on a private VLAN or other network. The digital data may be ingested into the encoder as streams of metadata and is sourced from an array of potential sensor types and third-party devices (open or proprietary) that are used in surgical, ICU, emergency or other clinical intervention units. These sensors and devices may be connected through middleware and/or hardware devices which may act to translate, format and/or synchronize live streams of data from respected sources.).
Regarding Claim 14, Grantcharov teaches the system of claim 13 and further teaches the following:
The surgical data management system of claim 13, wherein a surgical hub includes the processor and the memory ([0077] and Claim 22: a Central control station (non-limiting examples being one or more computers, tablets, PDA's, hybrids, and/or convertibles, etc.) which may be located in the clinical unit or another customer designated location. A media management hub server with middleware and hardware for translating, connecting, formatting, and recording the real-time medical or surgical data streams to generate session container files on network accessible storage devices).
Regarding Claim 15, Grantcharov teaches the system of claim 14 and further teaches the following:
The surgical data management system of claim 14, further comprising the first, second, and third surgical systems (See Fig. 1 and Fig. 8, [00142]: system may include more encoders 22 to collect feeds from local or remote data capture devices (of hardware unit 20) and exchange data.).
Regarding Claim 16, Grantcharov teaches the system of claim 13 and further teaches the following:
The surgical data management system of claim 13, wherein each of the first, second, and third surgical systems is one of a hospital network, a database, a surgical instrument, or a surgical cart (hardware units 20 may have sensors 30 (Fig. 1) installed or utilized in a surgical unit, ICU, emergency unit or clinical intervention units. Example sensors include but are not limited to: environmental sensors: i.e. temperature, moisture, humidity, etc.; acoustic sensors: i.e. ambient noise, decibel, etc.; electrical sensors: i.e. hall, magnetic, current, mems, capacitive, resistance, etc.; flow sensors: i.e. air, fluid, gas, etc.; angle/positional/displacement sensors: i.e., gyroscopes, attitude indicator, piezoelectric, photoelectric, etc.; other sensors: strain, level sensors, load cells, motion, pressure, etc.).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 2-4, 6-7, and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Grantcharov (WO 2016/044920) in view of Giataganas et al. (US 2020/0118677) (Hereinafter Giataganas).
Regarding Claim 2, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 1, wherein the information exchanged over the reconfigured data pipelines network allows at least two of the first, second, and third surgical systems to close a control loop controlling a sub-system of the at least two of the first, second, and third surgical systems, the patient being part of the closed control loop (See Fig. 6, [0085]: Illustration of an embodiment of a surgical map including interconnected surgical data structures).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the closed loop structure between the surgical systems, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure (See Giataganas [0021]).
Regarding Claim 3, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 1, wherein the third data steam is a dedicated data stream to only one of the first and second surgical systems ([0086] and Fig. 6: the surgical map 600 may transition from a first data structure 604 to another surgical data structure (e.g., the second data structure 606 or the third data structure 608) in the global surgical graph).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the dedicated data stream between the surgical systems, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure (See Giataganas [0021]).
Regarding Claim 4, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 1, wherein the third data steam is communicated to each of the first and second surgical systems (See Frig. 3 and Fig. 6: The streams can go between each of the systems, (e.g., between 604, 606, and 608).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the data streams going between each of the surgical systems, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure (See Giataganas [0021]).
Regarding Claim 6, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 1, wherein the second surgical system is configured to, during the performance of the surgical procedure, communicate a second data stream to the first surgical system over the data pipelines network, the first surgical system being configured to use the second data received over the data pipelines network in performing a function during the performance of the surgical procedure ([0085], Fig. 6: the second data structure 606 may include node 664 that is connected by edge 690 to one or more node 672 of the third data structure 608. It is also contemplated that any of the nodes 610,612,614 for the first data structure 604 can be connected by edge 690 to any of the nodes 670, 672, 674 of the third data structure 608); and
the second surgical system is configured to communicate the second data stream to the first surgical system over the reconfigured data pipelines network ([0085] Each of the surgical data structures 604, 606, 608 can be connected in multiple ways as long as there are interconnections (e.g., edges) between the surgical data structures).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the data streams going between the first and second surgical systems, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure. The metadata can be used to generate and/or update an electronic output during a surgical procedure or afterwards. (See Giataganas [0021]).
Regarding Claim 7, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 6, further comprising, during the performance of the surgical procedure, adjusting the reconfigured data pipelines network such that a priority level of the first, second, and third data streams is adjusted ([0091] the surgical data structures can identify a surgical action based on weights assigned to one or more edges between the node-to-node transitions. The weights may be manually assigned and updated when constructing the surgical data structure).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the surgical systems having priority levels, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure. The different functions can be assigned weights that can be associated with different factors such as risk, surgical outcomes, prevalence of use, current procedural states, etc., which allows for a larger variety of data being collected and streamed (See Giataganas [0021] and [0091]).
Regarding Claim 9, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 1, wherein the function performed by the second surgical system using the first data is one of: same as the function performed by the second surgical system using the third data, and different from the function performed by the second surgical system using the third data ([0047] Each information unit of the set of information units may correspond to a different temporal association relative to other information units of the set of information units.).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the surgical systems having different functions, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure. The different functions can be assigned weights that can be associated with different factors such as risk, surgical outcomes, prevalence of use, current procedural states, etc., which allows for a larger variety of data being collected and streamed (See Giataganas [0021] and [0091]).
Regarding Claim 10, Grantcharov teaches the method of claim 1 but fails to teach the following that is met by Giataganas:
The method of claim 1, wherein the first measured patient parameter is different from third measured patient parameter (Fig. 6, [0087], [0089]: the first surgical data structure 604 may start at node 610 and represent procedural states of a surgical procedure. The third surgical data structure 608 may start at node 670 and represent one or more anatomical features (e.g., heart, spleen, kidney, etc.) in the surgical procedure.).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the surgical systems having different parameters, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure. The different parameters can be assigned weights that can be associated with different factors such as risk, surgical outcomes, prevalence of use, current procedural states, etc., which allows for a larger variety of data being collected and streamed (See Giataganas [0021] and [0091]).
Regarding Claim 11, Grantcharov teaches the method of claim 1 and further teaches:
The method of claim 1, wherein the first measured patient parameter is same as the third measured patient parameter (See Fig. 1, where each system (20) can contain the same instruments and data collection devices to collect the same parameters);
However, Grantcharov does not teach the following that is met by Giataganas:
at least the second surgical system receives the third data stream ([0086] and Fig. 6: The first, second, and third surgical data structure 604, 606, 608 may include multiple interconnected nodes that provide inter-relational information between each of the surgical data structures. Thus, the second and third systems are interconnected and receive streams from the other); and
the second surgical system is configured to select one of the first data and the third data to use ([0005] An edge of the one or more edges (of the first, second, and third systems) is selected based on the additional metadata associated with the one or more edges. Electronic data associated with the portion of the surgical dataset is generated based on the selected edge.).
It would have been obvious to one of ordinary skill in the art before the effective filing date to have combined the data pipeline network including three surgical systems, as taught by Grantcharov, with the data streams going between the second and third surgical systems, as well as the selection of data to use, as taught by Giataganas, because the interconnected surgical data structures can include relational metadata (e.g., metadata associated with corresponding data structures), which is not available in a single data structure. The metadata can be used to generate and/or update an electronic output during a surgical procedure or afterwards. (See Giataganas [0021]).
Relevant Prior Art of Record Not Currently Being Applied
The relevant art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Grantcharov et al (US 11,322,248) discloses a similar system of exchanging data through data streams in an operating room environment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXIS K VAN DUZER whose telephone number is (571)270-5832. The examiner can normally be reached Monday thru Thursday 8-5 CT.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marc Jimenez can be reached at (571) 272-4530. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A.K.V./Examiner, Art Unit 3681
/MARC Q JIMENEZ/Supervisory Patent Examiner, Art Unit 3681