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
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. JP2021-018031, filed on 02/08/202.
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Objections
Claim 10 is objected to because of the following informalities: Claim 10 recites "analysis device", but should read as "analysis system" because it is dependent on claim 9. Appropriate correction is required.
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)(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.
Claim(s) 1-5 and 8-15 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kroehl et al. (US20220254353A1).
Regarding Claim 1, Kroehl et al. teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4) comprising:
an operation unit configured to receive a voice input from a microphone or a mobile device (See how the voice signal 206 recorded by the voice input 204 microphone is routed by the portable device 212, i.e. an operation unit, over a network 236, such as the Internet or an Intranet, to the control software 222 installed on a control computer 213 in [0147]-[0159] in Fig. 2; Also, see the system 200 and server 226 in [0137]-[0173] in Fig. 2 and in Claim 1-14); and
a measurement unit configured to analyze a specimen (See how the laboratory facility 244, i.e. a measurement unit, shown in Fig 2 can be a High Throughput Environment (HTE) facility that includes a plurality of laboratory devices 252, 254 and one or more laboratory software modules 250, 248 in [0151]-[0175] and in Claim 1),
wherein the operation unit includes a device state acquisition unit configured to acquire device state data of the measurement unit (See the portable device 212, i.e. an operation unit, with microphone 214, voice input 204, and how the computer 231, i.e. a device state acquisition unit, has the software 222 that can acquire data from the facility 244, i.e. a measurement unit, databases, the internet, and other connect devices in [0141]-[0172] in Fig. 1-4),
a voice detection/recognition unit configured to acquire voice data that is a digital signal converted from a voice input to the microphone or voice data that is a digital signal converted from a voice input to the mobile device and to convert the voice data into a voice instruction text (See the general-language voice-to-text conversion system 226, i.e. a voice recognition unit, which converts the received voice signal 206 into a text 208, the words and phrases of which are taken exclusively from a general-language target vocabulary 234 that does not include the technical-language words such as the name of the varnish or the word “rheological” in [0147]-[0159] in Fig. 1-4; Also, see the portable device with a microphone in Claim(s) 1, 3-7, and 15), and
a device operation permission determination unit configured to determine, when the voice instruction text includes an operation instruction to the measurement unit, whether the operation instruction including the voice instruction text is executable based on the device state data of the measurement unit acquired by the device state acquisition unit and an accuracy of the voice instruction text (See how the system 200 can include the combination of control software 222 and the correction software 225, i.e. a permission determination unit, which can be implemented as a function of the control software or as a stand-alone locally or remotely installed software application. Optionally, the system 200 can also include the NLP processor 258. Optionally, the system 200 can also include the voice-to-text conversion system 226 in [0146]-[0166] in Fig. 1-2; Also, see how the voice-to-text conversion system 226 can be configured as a cloud-based computer system that provides the conversion to multiple clients in the form of a software-based service, referred to herein as a “voice recognition processor” 232; and see how a corrected text 210, which is either transmitted directly by the control software 222 to a specific target system, e.g. the chemical facility 244, or which is first forwarded to an NLP processor 258 in [0146]-[0166] in Fig. 1-2).
Note what is discussed in MPEP § 2114 I-II. "[A]pparatus claims cover what a device is, not what a device does." Hewlett-Packard Co. v. Bausch & Lomb Inc., 909 F.2d 1464, 1469, 15 USPQ2d 1525, 1528 (Fed. Cir. 1990) (emphasis in original). A claim containing a "recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus" if the prior art apparatus teaches all the structural limitations of the claim. Ex parte Masham, 2 USPQ2d 1647 (Bd. Pat. App. & Inter. 1987). The instant application fails to cover the structural components that execute said “analyzing a specimen” or define how that the other apparatus components functionally or structurally relates to a “determining" when or how to analyze a specimen in the device. The structure component(s) such as a software or processors, and voice-to-text devices are common in the art.
Regarding Claim 2, Kroehl et al. teaches the device limitations of claim 1.
Kroehl et al. further teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), wherein the device operation permission determination unit determines whether the operation instruction including the voice instruction text is executable using a determination table (See how the NLP processor 258 can also be provided as a service over a network. The NLP processor analyses the syntactic structure of the corrected text 210 to detect the semantic content of the corrected text and to extract relevant information from it and convert it into a structured text 211.in [0096], [0147]-[0152] in Fig. 1-2; Also, see how the control software 222, i.e. an operation permission determination unit, uses to determine the number and identity of each required target system and how the results 242 of the execution of a particular hardware or software function are returned from the target system to the control software 222 in [0158]-[0159]); and
in the determination table, whether the operation instruction is valid or invalid is registered for a combination of the device state data of the measurement unit and the operation instruction and, when the operation instruction is valid, a threshold of the accuracy of the voice instruction text that makes the operation instruction valid is set (See how the results 242 are—at least also—(or exclusively) returned to the portable device 212 and output via its speaker 218. This is particularly advantageous as it allows the laboratory worker 202 maximum freedom of movement both in terms of inputting control commands, chemical formulations and search queries and in terms of receiving the results of the execution of a corresponding hardware or software function in [0159], [0083]-[0084], [0096] in Fig. 2; See the assignment table 238, i.e. a determination table, in [0148]-[0151]).
Regarding Claim 3, Kroehl et al. teaches the device limitations of claim 1.
Kroehl et al. further teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), wherein the accuracy of the voice instruction text is calculated based on a rate of concordance between the voice instruction text and a character string of the operation instruction (See how the control software 222 transfers the received text 208 to the correction function or correction software 225 and prompts it to correct the text 208 using the assignment table 238. In the course of the correction, words and phrases of the target language that are incorrectly recognised according to the table are replaced in each case by assigned technical-language words and phrases. The result is a corrected text 210, which is either transmitted directly by the control software 222 to a specific target system, for example a chemical facility 244, or which is first forwarded to an NLP processor 258 [0145]-[0167], [0173] in Fig. 1-3).
Regarding Claim(s) 4-5, Kroehl et al. teaches the device limitations of claim 1.
Kroehl et al. further teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), wherein the operation unit includes a screen display/voice output unit (See how the results 424 of the Internet search are returned to the control software or the assistant, which forwards these results to a suitable output device in the vicinity of the user 202, for example the portable device 212 with the microphone and a speaker 214 in [0016], [0173]-[0175] in Fig. 1-4), and
when the device operation permission determination unit determines that the voice input is made from a user in a location distant from the automatic analysis device, the screen display/voice output unit asks the user for confirmation using a screen or a voice whether to execute the operation instruction including the voice instruction text (See how all of the system architectures 200, 300, 400 shown here enable the use of existing voice-to-text APIs of various cloud providers by means of their own cloud-provider-independent hardware to enable subject-specific voice recognition and control, on this basis, of laboratory devices and electronic search services in a laboratory in [0178] in Fig. 1-4; Also, see how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software 222, NLP processor 258, i.e. an operation permission determination unit, and a portable device 212 with microphone in [0146] in Fig. 2);
wherein the device operation permission determination unit determines whether the voice input is made from the user in the location distant from the automatic analysis device based on a volume of the microphone that makes the voice input or position information or a received field intensity of the mobile device to which the voice is input (See how the control software 222, i.e. an operation permission determination unit, can be implemented as a “virtual laboratory assistant” 223. For example, the virtual laboratory assistant can respond to a name such as “CONTROL COMPUTER”, “LUISA” or “EVA”. The control software is configured to search the corrected text 210 for keywords and to invoke specific hardware or software functions of a target system depending on those keywords. Thus, voice input or positing information would be anticipated in [0170]-[0179] in Fig. 1-4). Note MPEP § 2114 I-II.
Regarding Claim 8, Kroehl et al. teaches the device limitations of claim 1.
Kroehl et al. further teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), wherein the mobile device is any one of a pin microphone, a headphone, a smartphone, a tablet, smart glasses, or a smart watch including the microphone (See the portable device 212, i.e. an operation unit, with microphone 214, voice input 204, and how the computer 231, i.e. a device state acquisition unit, has the software 222 that can acquire data from the facility 244, i.e. a measurement unit, databases, the internet, and other connect devices in [0141]-[0172] in Fig. 1-4).
Regarding Claim 9, Kroehl et al. teaches an automatic analysis system (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4) comprising:
a plurality of automatic analysis devices each of which includes a measurement unit configured to analyze a specimen (See how the laboratory facility 244, i.e. a measurement unit, shown in Fig 2 can be a High Throughput Environment (HTE) facility that includes a plurality of laboratory devices 252, 254 and one or more laboratory software modules 250, 248 in [0151]-[0175] and in Claim 1); and
a management server configured to connect the plurality of automatic analysis devices via a network and to manage the plurality of automatic analysis devices (See the system 200 can also include the voice-to-text conversion system 226 in [0146]-[0166] in Fig. 1-4; Also, see the cloud computer software 302 that can hold protocols and procedures of action and the in [0035], [0057]-[0116]; See how the voice-to-text conversion system 226 can be configured as a cloud-based computer system that provides the conversion to multiple clients in the form of a software-based service, referred to herein as a “voice recognition processor” 232. The voice-to-text conversion system 226 can be, for example, Google's cloud computer system providing Google's speech-to-text cloud service over the Internet. Thus, the interface 224 in this case is a cloud-based API from Google. The voice-to-text conversion system returns the recognised text 208 to the control software 222 in [0147] in Fig. 1-4),
wherein one or more automatic analysis devices among the plurality of automatic analysis devices are operated through a voice input from a mobile device (See the general-language voice-to-text conversion system 226, i.e. a voice recognition unit, which converts the received voice signal 206 into a text 208, the words and phrases of which are taken exclusively from a general-language target vocabulary 234 that does not include the technical-language words such as the name of the varnish or the word “rheological” in [0147]-[0159] in Fig. 1-4; Also, see the portable device with a microphone in Claim(s) 1, 3-7, and 15), and
the management server includes a device state acquisition unit configured to acquire device state/operation information data including device state data of the measurement unit and operation information for the automatic analysis device relating to the device state data from the plurality of automatic analysis devices (See how the system 200 can include the combination of control software 222 and the correction software 225, i.e. a permission determination unit, which can be implemented as a function of the control software or as a stand-alone locally or remotely installed software application. Optionally, the system 200 can also include the NLP processor 258. Optionally, the system 200 can also include the voice-to-text conversion system 226 in [0146]-[0166] in Fig. 1-2; Also, see how the voice-to-text conversion system 226 can be configured as a cloud-based computer system that provides the conversion to multiple clients in the form of a software-based service, referred to herein as a “voice recognition processor” 232; and see how a corrected text 210, which is either transmitted directly by the control software 222 to a specific target system, e.g. the chemical facility 244, or which is first forwarded to an NLP processor 258 in [0146]-[0166] in Fig. 1-2),
a voice detection/recognition unit configured to acquire voice data that is a digital signal converted from a voice input to the mobile device and to convert the voice data into a voice instruction text, a system management unit configured to identify, when the voice instruction text includes an operation instruction to the automatic analysis device, an automatic analysis device to be operated by the operation instruction including the voice instruction text (See how the NLP processor 258 can also be provided as a service over a network. The NLP processor analyses the syntactic structure of the corrected text 210 to detect the semantic content of the corrected text and to extract relevant information from it and convert it into a structured text 211.in [0096], [0147]-[0152] in Fig. 1-2; Also, see how the control software 222, i.e. an operation permission determination unit, uses to determine the number and identity of each required target system and how the results 242 of the execution of a particular hardware or software function are returned from the target system to the control software 222 in [0158]-[0159]), and a device communication unit configured to transmit voice data acquired from the mobile device or a voice instruction text corresponding to the voice data to the automatic analysis device identified by the system management unit (See in Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4).
Note what is discussed in MPEP § 2114 I-II. "[A]pparatus claims cover what a device is, not what a device does." Hewlett-Packard Co. v. Bausch & Lomb Inc., 909 F.2d 1464, 1469, 15 USPQ2d 1525, 1528 (Fed. Cir. 1990) (emphasis in original). A claim containing a "recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus" if the prior art apparatus teaches all the structural limitations of the claim. Ex parte Masham, 2 USPQ2d 1647 (Bd. Pat. App. & Inter. 1987). The instant application fails to cover the structural components that execute said “analyzing a specimen” or define how that the other apparatus components functionally or structurally relates to a “determining" when or how to analyze a specimen in the device. The structure component(s) such as a software or processors, and voice-to-text devices are common in the art.
Regarding Claim 10, Kroehl et al. teaches the device limitations of claim 9.
Kroehl et al. further teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), wherein the system management unit identifies the automatic analysis device to be operated by the operation instruction including the voice instruction text using a management table, in the management table, for each of the plurality of automatic analysis devices, an identifier of the mobile device capable of operating the automatic analysis device, device state data of the measurement unit of the automatic analysis device, an identifier of a subject that operates the automatic analysis device to enter a device state of the device state data, a date and time at which the subject operated the automatic analysis device to enter the device state of the device state data, and a lock status of the automatic analysis device are registered, and the management table is updated based on the device state/operation information data acquired by the device state acquisition unit (See how all of the system architectures 200, 300, 400 shown here enable the use of existing voice-to-text APIs of various cloud providers by means of their own cloud-provider-independent hardware to enable subject-specific voice recognition and control, on this basis, of laboratory devices and electronic search services in a laboratory in [0178] in Fig. 1-4; Also, see how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software 222, NLP processor 258, i.e. an operation permission determination unit or management units, and a portable device 212 with microphone in [0146] in Fig. 2).
Regarding Claim(s) 11-15, Kroehl et al. teaches the device limitations of claim 10.
Kroehl et al. further teaches an automatic analysis system (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), wherein when the voice instruction text includes designation of an automatic analysis device to be operated by the voice instruction text, the system management unit selects the automatic analysis device designated by the voice instruction text as an automatic analysis device candidate to be operated, and when the voice instruction text does not include designation of the automatic analysis device to be operated by the voice instruction text, the system management unit refers to the management table to select, as the automatic analysis device candidate to be operated, an automatic analysis device where the mobile device transmitting the voice data is registered as the subject that operated the automatic analysis device most recently (See the various systems and units embodiments in Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4);
wherein the system management unit refers to the management table and selects, as the automatic analysis device candidate to be operated, an automatic analysis device where the mobile device transmitting the voice data is registered as the subject that operated the automatic analysis device most recently and a predetermined period of time did not elapse from a latest operation date and time (See the various systems and units’ embodiments in Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4);
wherein the system management unit refers to the management table and, when the automatic analysis device selected as the candidate to be operated cannot respond to the operation instruction including the voice instruction text, recommends an automatic analysis device that can respond to the operation instruction including the voice instruction text to the mobile device transmitting the voice data (See the various systems and units’ embodiments in Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4);
wherein the system management unit refers to the management table and, when the automatic analysis device selected as the candidate to be operated can respond to the operation instruction including the voice instruction text, if the mobile device transmitting the voice data has operation authority for the automatic analysis device and another mobile device did not lock the automatic analysis device, identifies the automatic analysis device as the automatic analysis device to be operated (See the various systems and units embodiments in Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4); and
wherein when the voice instruction text is a specific operation instruction that is an operation instruction to all of the plurality of automatic analysis devices, the system management unit does not identify the automatic analysis device to be operated and causes the device communication unit to transmit voice data acquired from the mobile device or a voice instruction text corresponding to the voice data to all of the plurality of automatic analysis devices (See the various systems and units embodiments in Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4).
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.
Claim(s) 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Kroehl et al. (US20220254353A1) as applied to claim 1 above, and further in view of Seki et al. (US20230094420A1).
Regarding Claim 6, Kroehl et al. teaches the device limitations of claim 1.
Kroehl et al. further teaches an automatic analysis device (See the Abstract, how the system 200 comprises laboratory devices 252, 254 and laboratory software modules 248, 250, a control computer 213 with control software, and a portable device 212 with microphone, and the Claim(s) 1-16 in [0137]-[0173] in Fig. 1-4), an external server; and when the voice instruction text includes an operation instruction to the measurement unit, the device operation permission determination unit determines whether the operation instruction including the voice instruction text is executable based on the inspection schedule of the automatic analysis device acquired by the inspection plan acquisition unit and the operation instruction including the voice instruction text (See the system 200 can also include the voice-to-text conversion system 226 in [0146]-[0166] in Fig. 1-4; Also, see the cloud computer software 302 that can hold protocols and procedures of action and the in [0035], [0057]-[0116]; See how the voice-to-text conversion system 226 can be configured as a cloud-based computer system that provides the conversion to multiple clients in the form of a software-based service, referred to herein as a “voice recognition processor” 232. The voice-to-text conversion system 226 can be, for example, Google's cloud computer system providing Google's speech-to-text cloud service over the Internet. Thus, the interface 224 in this case is a cloud-based API from Google. The voice-to-text conversion system returns the recognised text 208 to the control software 222 in [0147] in Fig. 1-4).
Kroehl et al. fails to explicitly teach an automatic analysis device, wherein the operation unit includes an inspection plan acquisition unit connected to an external server and configured to acquire an inspection schedule of the automatic analysis device from the external server, and when the voice instruction text includes an operation instruction to the measurement unit, the device operation permission determination unit determines whether the operation instruction including the voice instruction text is executable based on the inspection schedule of the automatic analysis device acquired by the inspection plan acquisition unit and the operation instruction including the voice instruction text.
However, in the analogous art of management devices and request methods, Seki et al. teaches an automatic analysis device (See the Abstract, the management device 102 and analysis devices 103, and the Claim(s) 1-15 in [0035]-[0103] in Fig. 1-4), wherein the operation unit includes an inspection plan acquisition unit connected to an external server and configured to acquire an inspection schedule of the automatic analysis device from the external server (See how the storage device 213 is mounted on the analysis devices 103 to 107, i.e. acquisition units, and includes a reagent information management table 214-16, the person-in-charge schedule management table 218-219, the position information management table 219, reagent storage information management table 220-221 in [0040]-[0068], [0100]-[0103] in Fig. 7 and in Claim(s) 2, 3, 6, 8, and 11-12; Also, see how the communication device 204 is a communication device for the management device 102 to communicate with the position information acquisition device 224, the analysis devices/pre-processing device 103 to 108, and the terminal 225 via the networks, and a wired/wireless local area network, a wired/wireless global area network, a mobile phone line network, or a combination thereof can be used in [0037]-[0043] in Fig. 1-2), and
when the input instruction text includes an operation instruction to the measurement unit, the device operation permission determination unit determines whether the operation instruction including the input instruction text is executable based on the inspection schedule of the automatic analysis device acquired by the inspection plan acquisition unit and the operation instruction including the voice instruction text (See how the information processing device 205 is a computer for executing various applications of the management device 102 in [0034]-[0043] in Fig. 1-2 and in Claim(s) 1-15).
Thus, it would be obvious to one with ordinary skills in the art to modify the device of Kroehl et al. by incorporating an operation unit that includes an inspection plan acquisition unit connected to an external server and configured to acquire an inspection schedule of the automatic analysis device from the external server, and instruction text that includes an operation instruction to the measurement unit (as taught by Seki et al.) for the benefit of determining whether the operation instruction including the instruction text is executable based on the inspection schedule of the automatic analysis device acquired by the inspection plan acquisition unit and the operation instruction including the voice instruction text.
Note what is discussed in MPEP § 2114 I-II. "[A]pparatus claims cover what a device is, not what a device does." Hewlett-Packard Co. v. Bausch & Lomb Inc., 909 F.2d 1464, 1469, 15 USPQ2d 1525, 1528 (Fed. Cir. 1990) (emphasis in original). A claim containing a "recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus" if the prior art apparatus teaches all the structural limitations of the claim. Ex parte Masham, 2 USPQ2d 1647 (Bd. Pat. App. & Inter. 1987). The instant application fails to cover the structural components that execute said “analyzing a specimen” or define how that the other apparatus components functionally or structurally relates to a “determining" when or how to analyze a specimen in the device. The structure component(s) such as a software or processors, and voice-to-text devices are common in the art.
Regarding Claim 7, The combination of Kroehl et al. and Seki et al. teaches the device limitations of claim 6.
Seki et al. further teaches an automatic analysis device (See the Abstract, the management device 102 and analysis devices 103, and the Claim(s) 1-15 in [0035]-[0103] in Fig. 1-4), wherein when the operation instruction including the instruction text is start of a predetermined specific operation and the specific operation is scheduled within a predetermined time in the inspection schedule of the automatic analysis device acquired by the inspection plan acquisition unit (See how the information processing device 205 is a computer for executing various applications of the management device 102 in [0034]-[0043] in Fig. 1-2 and in Claim(s) 1-15),
the device operation permission determination unit determines that the operation instruction representing the start of the specific operation is not executable (See how the storage device 213 is mounted on the analysis devices 103 to 107, i.e. acquisition units, and includes a reagent information management table 214-16, the person-in-charge schedule management table 218-219, the position information management table 219, reagent storage information management table 220-221 in [0040]-[0068], [0100]-[0103] in Fig. 7 and in Claim(s) 2, 3, 6, 8, and 11-12; Also, see how the communication device 204 is a communication device for the management device 102 to communicate with the position information acquisition device 224, the analysis devices/pre-processing device 103 to 108, and the terminal 225 via the networks, and a wired/wireless local area network, a wired/wireless global area network, a mobile phone line network, or a combination thereof can be used in [0037]-[0043] in Fig. 1-2).
Thus, it would be obvious to one with ordinary skills in the art to modify the device of Kroehl et al. by incorporating an operation instruction including an instruction text that starts of a predetermined specific operation and a specific operation is scheduled within a predetermined time in an inspection schedule of the automatic analysis device acquired by the inspection plan acquisition unit (as taught by Seki et al.) for the benefit of configuring the device operation permission determination unit to determine that the operation instruction representing the start of the specific operation is not executable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The following prior art teaches similar devices and methods Sugimoto (US20210116468A1) and Christopher et al. (US11302316B2).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRITNEY N WASHINGTON whose telephone number is (703)756-5959. The examiner can normally be reached Monday-Friday 7:00am - 3:30pm CT.
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/BRITNEY N. WASHINGTON/Examiner, Art Unit 1797
/JENNIFER WECKER/Primary Examiner, Art Unit 1797