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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
No claim limitation has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Specifically, claim 1 recites an abstract idea of “that provides the sensor data as input to the trained model and that generates a signal to activate the noninvasive blood pressure sensor based on an output of the trained model”. Similarly, claim 11 recites an abstract idea of “determining, using a trained model, that the sensor data is associated with a predicted change in blood pressure for the patient; and triggering a noninvasive blood pressure sensor based on the predicted change in blood pressure”. Under the broadest reasonable interpretation, there is nothing in the claims that foreclose them from being performed by a human, mentally or with pen and paper. The “generates a signal to activate the noninvasive blood pressure sensor based on an output of the trained model” and “determining, using a trained model, that the sensor data is associated with a predicted change in blood pressure for the patient; and triggering a noninvasive blood pressure sensor based on the predicted change in blood pressure” steps all represent steps that amount to an observation, evaluation, or judgment that is a mental process performed on a generic computer based on the sensor data received from the one or more patient sensors (step 2A: Prong One).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because:
The claimed “memory” and “processing circuitry” are merely generic computer components performing generic computer functions which are well-understood, routine, and conventional in the art; as such, they do not meaningfully limit the claim to be more than just the abstract idea.
The limitations “a monitoring device that receives the sensor data”, “processing circuitry that provides the sensor data as input to the trained model”, and “receiving sensor data of a patient from one or more patient sensors, the sensor data corresponding to a time window” are merely insignificant extra-solution activity, such as mere data gathering, recited at a high level of generality and/or in a well-understood, routine, and conventional way, of the information needed to carry out the claimed algorithm.
The limitations “a noninvasive blood pressure sensor” and “one or more patient sensors” are well-understood, routine, and conventional in the art, as evidenced by McCombie et al. (US 8,475,370 B2): see col. 1, lines 23-30 and col. 2, lines 7-14, which establish that conventional vital signs monitors include modules to determine ECG and pulse oximetry and Donehoo et al. (US 2010/0249616 A1): see [0002] and [0005], which establish that a noninvasive blood pressure sensor including a blood pressure cuff is conventional in the art. They represent components that would routinely be used in applying the abstract idea and do not meaningfully limit the claim, taken as a whole, to a particular application of the abstract idea (step 2A: Prong Two).
Moreover, the judicial exception is not integrated into a practical application because the claim does not recite any limitations that amount to an improvement in the functioning of a computer, or an improvement to other technology or technical field, apply or use the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement the judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (step 2B).
Regarding dependent claims 2-5, 8-10, and 12-15, the limitations of these dependent claims merely add details to the algorithm which forms the abstract idea but does not contain any further “additional elements”. Thus, the dependent claims are not significantly more than the extended abstract idea.
Dependent claims 6-7 add additional details to the one or more patient sensors and the noninvasive blood pressure sensor, but they are still well-understood, routine, and conventional in the art, as evidenced by the citations to McCombie et al. and Donehoo et al. outlined above.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1-7 and 9-15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Inukai et al. (US Patent No. 7,393,327 B2).
Regarding claim 1, Inukai et al. discloses a noninvasive blood pressure monitoring system, comprising:
a noninvasive blood pressure sensor (12) (see col. 4, lines 1-8 – “Referring to FIG. 1, a cuff 10 has a band-like form, and incorporates a rubber pouch which expands and contracts by pumping of a pump 14. The cuff 10 is normally attached to one of the limbs, typically the upper arm of a patient. A pressure sensor 12 senses a change in pressure applied to the gas filled in the internal rubber pouch of the cuff 10, converts the pressure signal into an electrical signal, and outputs the electrical signal to a controller 100”);
one or more patient sensors (20, 30, 40) that generate sensor data (see col. 4, lines 9-29 – “An electrocardiogram (ECG) electrode 20 comprising a plurality of electrodes is attached to a predetermined position of the chest of a patient, and outputs an induced waveform as an ECG signal to the controller 100. A finger sensor 30 is a so-called pulse oximeter which optically senses and outputs an oxygen saturation degree (SPO2) and plethysmograph to the controller 100. The absorbance of hemoglobin changes in accordance with whether hemoglobin combines with oxygen, and also changes in accordance with the wavelength of light. On the basis of these facts, the finger sensor 30 generally measures the oxygen saturation degree by using two wavelengths, i.e., red light and infrared light. Also, since the AC component of transmitted light or reflected light changes in accordance with the blood flow volume, this AC component is detected as a photoplethysmograph (PTG). Other sensors 40 sense other biological information such as the respiration and body temperature of a patient, and one or more sensors are connected to the controller 100 as needed. The other sensors 40 are not directly related to the blood pressure monitoring operation of this embodiment, so no further explanation thereof will be made”); and
a monitoring device that receives the sensor data and comprising:
a memory (90) storing a trained model (see col. 4, lines 44-51 – “A storage unit 90 is typically a hard disk drive, and records programs for controlling the operation of the biological information monitoring apparatus, various data, measurement results, personal information of patients, and the like. The storage unit 90 may also include at least one other type of storage device, e.g., a device which reads and writes a writable removable medium such as a memory card or an optical disk”); and
processing circuitry (100) that provides the sensor data as input to the trained model (see col. 4, lines 53-64 – “The controller 100 controls the operation of the whole biological information monitoring apparatus. The controller 100 has, e.g., a CPU and RAM, and controls the individual units by loading the control programs stored in the storage unit 90 into the RAM and executing the loaded programs by the CPU, thereby implementing processes including the blood pressure monitoring operation (to be described later) of the biological information monitoring apparatus. Note that not all the processes need be executed using software by the CPU. For example, signal processing such as A/D conversion and filtering of signals input from the various sensors may also be assigned to a DSP or dedicated hardware, thereby appropriately using another arrangement”) and that generates a signal to activate the noninvasive blood pressure sensor based on an output of the trained model (see col. 7, line 59-col 8, line 12 – “In step S130, whether the conditions for executing cuff blood pressure measurement are satisfied is determined. That is, whether one of the following conditions is met is determined. (1) Both the pulse wave parameter and estimated blood pressure are continuously found to be abnormal for a predetermined period. (2) A predetermined time has elapsed since the last cuff blood pressure measurement. If one of these conditions is met, the controller 100 controls the pump 14 to raise the pressure of the cuff 10, monitors the input signal from the pressure sensor 12 while gradually exhausting the air after avascularization, and calculates the highest blood pressure, average blood pressure, and lowest blood pressure on the basis of the well-known oscillometric method. The controller 100 also stores, in the storage unit 90, the waveform parameters and estimated blood pressure obtained immediately before the blood pressure measurement using the cuff 10, and uses them in calibration of the coefficients .alpha. and .beta. contained in the equation for calculating the estimated blood pressure and in processing after that”).
Regarding claim 2, Inukai et al. discloses the trained model is trained on patient data comprising monitored blood pressure and concurrently acquired patient sensor data (see col. 5, lines 58-63 – “First, in step S101, the acquisition of an ECG and pulse wave is started. Also, as initialization, initial blood pressure measurement using a cuff is performed, and the initial values of an accelerated pulse wave parameter and estimated blood pressure are calculated by a method to be explained below, and stored in the storage unit 90” and col. 8, lines 1-12 – “If one of these conditions is met, the controller 100 controls the pump 14 to raise the pressure of the cuff 10, monitors the input signal from the pressure sensor 12 while gradually exhausting the air after avascularization, and calculates the highest blood pressure, average blood pressure, and lowest blood pressure on the basis of the well-known oscillometric method. The controller 100 also stores, in the storage unit 90, the waveform parameters and estimated blood pressure obtained immediately before the blood pressure measurement using the cuff 10, and uses them in calibration of the coefficients .alpha. and .beta. contained in the equation for calculating the estimated blood pressure and in processing after that”).
Regarding claim 3, Inukai et al. discloses the signal is generated based on the model predicting that the sensor data corresponds to a change in blood pressure (see col. 7, lines 39-47 – “In step S125, whether the estimated blood pressure is an abnormal value is determined. This determination can be performed by determining whether the estimated blood pressure is larger than the upper limit or smaller than the lower limit of a predetermined normal range, or determining whether the estimated blood pressure fluctuates more than a predetermined amount (which can be either a fluctuation ratio or difference) from the value of the last cuff blood pressure measurement”).
Regarding claim 4, Inukai et al. discloses the sensor data comprises a segment of a photoplethysmography signal (see col. 4, lines 12-15 – “A finger sensor 30 is a so-called pulse oximeter which optically senses and outputs an oxygen saturation degree (SPO2) and plethysmograph to the controller 100”).
Regarding claim 5, Inukai et al. discloses the sensor data comprises a physiological parameter (see col. 4, lines 9-29 – “An electrocardiogram (ECG) electrode 20 comprising a plurality of electrodes is attached to a predetermined position of the chest of a patient, and outputs an induced waveform as an ECG signal to the controller 100. A finger sensor 30 is a so-called pulse oximeter which optically senses and outputs an oxygen saturation degree (SPO2) and plethysmograph to the controller 100. The absorbance of hemoglobin changes in accordance with whether hemoglobin combines with oxygen, and also changes in accordance with the wavelength of light. On the basis of these facts, the finger sensor 30 generally measures the oxygen saturation degree by using two wavelengths, i.e., red light and infrared light. Also, since the AC component of transmitted light or reflected light changes in accordance with the blood flow volume, this AC component is detected as a photoplethysmograph (PTG). Other sensors 40 sense other biological information such as the respiration and body temperature of a patient, and one or more sensors are connected to the controller 100 as needed. The other sensors 40 are not directly related to the blood pressure monitoring operation of this embodiment, so no further explanation thereof will be made”).
Regarding claim 6, Inukai et al. discloses the sensor data comprises one or more of pulse oximetry monitoring data, carbon dioxide monitoring data, temperature data, or EEG data (see col. 4, lines 9-29 – “An electrocardiogram (ECG) electrode 20 comprising a plurality of electrodes is attached to a predetermined position of the chest of a patient, and outputs an induced waveform as an ECG signal to the controller 100. A finger sensor 30 is a so-called pulse oximeter which optically senses and outputs an oxygen saturation degree (SPO2) and plethysmograph to the controller 100. The absorbance of hemoglobin changes in accordance with whether hemoglobin combines with oxygen, and also changes in accordance with the wavelength of light. On the basis of these facts, the finger sensor 30 generally measures the oxygen saturation degree by using two wavelengths, i.e., red light and infrared light. Also, since the AC component of transmitted light or reflected light changes in accordance with the blood flow volume, this AC component is detected as a photoplethysmograph (PTG). Other sensors 40 sense other biological information such as the respiration and body temperature of a patient, and one or more sensors are connected to the controller 100 as needed. The other sensors 40 are not directly related to the blood pressure monitoring operation of this embodiment, so no further explanation thereof will be made”).
Regarding claim 7, Inukai et al. discloses the signal to activate the noninvasive blood pressure sensor causes a cuff of the noninvasive blood pressure sensor to inflate and to subsequently deflate as a part of blood pressure monitoring (see col. 8, lines 1-7 – “If one of these conditions is met, the controller 100 controls the pump 14 to raise the pressure of the cuff 10, monitors the input signal from the pressure sensor 12 while gradually exhausting the air after avascularization, and calculates the highest blood pressure, average blood pressure, and lowest blood pressure on the basis of the well-known oscillometric method”).
Regarding claim 9, Inukai et al. discloses the monitoring device operates to receive blood pressure data as a result of activating the noninvasive blood pressure sensor (see col. 8, lines 1-7 – “If one of these conditions is met, the controller 100 controls the pump 14 to raise the pressure of the cuff 10, monitors the input signal from the pressure sensor 12 while gradually exhausting the air after avascularization, and calculates the highest blood pressure, average blood pressure, and lowest blood pressure on the basis of the well-known oscillometric method”).
Regarding claim 10, Inukai et al. discloses the processing circuitry of the monitoring device operates to update the trained model using the blood pressure data and the sensor data (see col. 7, lines 28-38 – “Note that the coefficients .alpha. and .beta. need only be determined in advance. That is, this equation is a linear equation with two unknowns, so the values of the coefficients .alpha. and .beta. can be determined by using at least two actually measured blood pressures and the corresponding pulse wave propagation times. Each coefficient need not be fixed but may also be updated to an optimum value by using an actually measured value obtained by another method (cuff measurement or direct measurement) and the pulse wave propagation time at the corresponding timing”; see also Figure 5).
Regarding claim 11, Inukai et al. discloses a method of noninvasive blood pressure monitoring, the method comprising:
receiving sensor data of a patient from one or more patient sensors, the sensor data corresponding to a time window (see col. 5, lines 58-63 – “First, in step S101, the acquisition of an ECG and pulse wave is started. Also, as initialization, initial blood pressure measurement using a cuff is performed, and the initial values of an accelerated pulse wave parameter and estimated blood pressure are calculated by a method to be explained below, and stored in the storage unit 90” and col. 8, lines 1-12 – “If one of these conditions is met, the controller 100 controls the pump 14 to raise the pressure of the cuff 10, monitors the input signal from the pressure sensor 12 while gradually exhausting the air after avascularization, and calculates the highest blood pressure, average blood pressure, and lowest blood pressure on the basis of the well-known oscillometric method. The controller 100 also stores, in the storage unit 90, the waveform parameters and estimated blood pressure obtained immediately before the blood pressure measurement using the cuff 10, and uses them in calibration of the coefficients .alpha. and .beta. contained in the equation for calculating the estimated blood pressure and in processing after that”);
determining, using a trained model, that the sensor data is associated with a predicted change in blood pressure for the patient (see col. 7, lines 39-47 – “In step S125, whether the estimated blood pressure is an abnormal value is determined. This determination can be performed by determining whether the estimated blood pressure is larger than the upper limit or smaller than the lower limit of a predetermined normal range, or determining whether the estimated blood pressure fluctuates more than a predetermined amount (which can be either a fluctuation ratio or difference) from the value of the last cuff blood pressure measurement”); and
triggering a noninvasive blood pressure sensor based on the predicted change in blood pressure (see col. 7, line 59-col 8, line 12 – “In step S130, whether the conditions for executing cuff blood pressure measurement are satisfied is determined. That is, whether one of the following conditions is met is determined. (1) Both the pulse wave parameter and estimated blood pressure are continuously found to be abnormal for a predetermined period. (2) A predetermined time has elapsed since the last cuff blood pressure measurement. If one of these conditions is met, the controller 100 controls the pump 14 to raise the pressure of the cuff 10, monitors the input signal from the pressure sensor 12 while gradually exhausting the air after avascularization, and calculates the highest blood pressure, average blood pressure, and lowest blood pressure on the basis of the well-known oscillometric method. The controller 100 also stores, in the storage unit 90, the waveform parameters and estimated blood pressure obtained immediately before the blood pressure measurement using the cuff 10, and uses them in calibration of the coefficients .alpha. and .beta. contained in the equation for calculating the estimated blood pressure and in processing after that”).
Regarding claim 12, Inukai et al. discloses receiving new sensor data from the one or more patient sensors, the new sensor data corresponding to a subsequent time window after the time window (see col. 5, lines 1-15 – “The biological information monitoring apparatus of this embodiment is similar to the prior art in that the pulse wave propagation velocity is continuously calculated by using an ECG and plethysmograph, and an estimated blood pressure is continuously calculated by using an expression having a precalibrated coefficient, and that the necessity of blood pressure measurement using a cuff is determined by using the estimated blood pressure. In this embodiment, however, it is determined that blood pressure measurement using a cuff is necessary only when another condition is met in addition to the estimated blood pressure, thereby increasing the abnormality detection accuracy in continuous blood pressure monitoring. This embodiment is characterized in that the value of a parameter obtained from an accelerated pulse wave is used as the other condition” and col. 7, lines 34-47 – “Each coefficient need not be fixed but may also be updated to an optimum value by using an actually measured value obtained by another method (cuff measurement or direct measurement) and the pulse wave propagation time at the corresponding timing. In step S125, whether the estimated blood pressure is an abnormal value is determined. This determination can be performed by determining whether the estimated blood pressure is larger than the upper limit or smaller than the lower limit of a predetermined normal range, or determining whether the estimated blood pressure fluctuates more than a predetermined amount (which can be either a fluctuation ratio or difference) from the value of the last cuff blood pressure measurement”);
determining, using the trained model, that the new sensor data is associated with a predicted stable blood pressure for the patient (see col. 7, lines 54-58 – “If the estimated blood pressure is found to be abnormal in step S125, the flow advances to step S130. If the estimated blood pressure is found to be normal in step S125, the flow returns to step S121 to continue the processing for the next heart beat”); and
not triggering the noninvasive blood pressure sensor based on the predicted stable blood pressure (see col. 7, lines 54-58 – “If the estimated blood pressure is found to be abnormal in step S125, the flow advances to step S130. If the estimated blood pressure is found to be normal in step S125, the flow returns to step S121 to continue the processing for the next heart beat”).
Regarding claim 13, Inukai et al. discloses receiving blood pressure data from the triggered noninvasive blood pressure sensor (see col. 6, lines 32-59 – “Note that in the above equations, (current) indicates a present calculated value, and (ref) indicates a reference calculated value obtained in the last cuff blood pressure measurement. Note also that the threshold values Thb and Thd indicating normal ranges can be either equal or individually set. In addition, the fluctuation need not be absolute values, and it is also possible to individually set the threshold value (upper limit) on the increasing side and the threshold value (lower limit) on the decreasing side. Practical values of the threshold values can be appropriately determined. For example, Thb=Thd=20(%) can be set in inequalities (1a) and (1b). It is also possible to dynamically change the threshold values in accordance with the results of periodical blood pressure measurements using a cuff. For example, if the result of cuff blood pressure measurement is smaller than a predetermined value, it is possible to make the threshold value on the decreasing side stricter (make the threshold value easier to exceed) than when the measurement result is not smaller than the predetermined value, thereby monitoring the decrease in blood pressure more strictly. More specifically, when the normal range is defined by the upper and lower limits, the lower limit is set to be high. In this case, the lower limit becomes easier to exceed, so the decrease in blood pressure can be strictly monitored. On the contrary, if the cuff measurement result is large, it is possible to make the threshold value on the increasing side stricter (make the upper limit of the normal range smaller)”); and
determining that the predicted change in blood pressure is not present in the blood pressure data (see col. 6, lines 32-59 – “Note that in the above equations, (current) indicates a present calculated value, and (ref) indicates a reference calculated value obtained in the last cuff blood pressure measurement. Note also that the threshold values Thb and Thd indicating normal ranges can be either equal or individually set. In addition, the fluctuation need not be absolute values, and it is also possible to individually set the threshold value (upper limit) on the increasing side and the threshold value (lower limit) on the decreasing side. Practical values of the threshold values can be appropriately determined. For example, Thb=Thd=20(%) can be set in inequalities (1a) and (1b). It is also possible to dynamically change the threshold values in accordance with the results of periodical blood pressure measurements using a cuff. For example, if the result of cuff blood pressure measurement is smaller than a predetermined value, it is possible to make the threshold value on the decreasing side stricter (make the threshold value easier to exceed) than when the measurement result is not smaller than the predetermined value, thereby monitoring the decrease in blood pressure more strictly. More specifically, when the normal range is defined by the upper and lower limits, the lower limit is set to be high. In this case, the lower limit becomes easier to exceed, so the decrease in blood pressure can be strictly monitored. On the contrary, if the cuff measurement result is large, it is possible to make the threshold value on the increasing side stricter (make the upper limit of the normal range smaller)”).
Regarding claim 14, Inukai et al. discloses increasing a confidence threshold of the trained model associated with predicting subsequent changes in blood pressure based on the predicted change in blood pressure not being present in the blood pressure data (see col. 6, lines 44-59 – “It is also possible to dynamically change the threshold values in accordance with the results of periodical blood pressure measurements using a cuff. For example, if the result of cuff blood pressure measurement is smaller than a predetermined value, it is possible to make the threshold value on the decreasing side stricter (make the threshold value easier to exceed) than when the measurement result is not smaller than the predetermined value, thereby monitoring the decrease in blood pressure more strictly. More specifically, when the normal range is defined by the upper and lower limits, the lower limit is set to be high. In this case, the lower limit becomes easier to exceed, so the decrease in blood pressure can be strictly monitored. On the contrary, if the cuff measurement result is large, it is possible to make the threshold value on the increasing side stricter (make the upper limit of the normal range smaller)”).
Regarding claim 15, Inukai et al. discloses switching activation of the noninvasive blood pressure sensor to timed intervals based on the predicted change in blood pressure not being present in the blood pressure data (see col. 7, lines 59-67 – “In step S130, whether the conditions for executing cuff blood pressure measurement are satisfied is determined. That is, whether one of the following conditions is met is determined. (1) Both the pulse wave parameter and estimated blood pressure are continuously found to be abnormal for a predetermined period. (2) A predetermined time has elapsed since the last cuff blood pressure measurement”).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
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.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Inukai et al., further in view of Sethi et al. (US Publication No. 2010/0081892 A1).
Regarding claim 8, it is noted Inukai et al. does not specifically teach the processing circuitry of the monitoring device operates to identify a type of the one or more patient sensors and to select the trained model from a plurality of trained models based on the identified type. However, Sethi et al. teaches the processing circuitry of the monitoring device operates to identify a type of the one or more patient sensors and to select the trained model from a plurality of trained models based on the identified type (see [0029] – “In an embodiment, encoder 42 may contain information about sensor 12, such as what type of sensor it is (e.g., whether the sensor is intended for placement on a forehead or digit) and the wavelengths of light emitted by emitter 16. This information may be used by monitor 14 to select appropriate algorithms, lookup tables and/or calibration coefficients stored in monitor 14 for calculating the patient's physiological parameters”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Inukai et al. to include the processing circuitry of the monitoring device operates to identify a type of the one or more patient sensors and to select the trained model from a plurality of trained models based on the identified type, as disclosed in Sethi et al., so as to select appropriate algorithms, lookup tables, and/or calibration coefficients for calculating the patient’s physiological parameters (see Sethi et al.: [0029]).
Conclusion
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/DEVIN B HENSON/ Primary Examiner, Art Unit 3791
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