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 .
Election/Restrictions
Claims 7-13 and 18-20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention and species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 1/5/2026.
Claims 1-6 and 14-17 are hereby under examination.
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 1-6 and 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Step 1 of the subject matter eligibility test (see MPEP 2106.03).
Claims 1-6 and 14-15 are directed to a “method”, which describes one of the four statutory categories of patentable subject matter, i.e., a process.
Step 2A of the subject matter eligibility test (see MPEP 2106.04)
Prong one: Claims 1-6 and 14-15 recite abstract idea, as follows:
“…isolating from each electrical activity measurement a signal comprising a slow wave contractility parameter measurement representative of the target pelvic structure; preparing a data profile comprising the plurality of signals comprising the slow wave contractility parameter measurements ;comparing the data profile with one or more reference data profiles, in which each reference data profile comprises a plurality of slow wave contractility parameter measurements of a reference subject's target pelvic structure taken at a plurality of spaced-apart time points during the reference subject's hormonal cycle; and determining a pelvic condition status of the subject based on the comparison” (claim 1)
Based on the broadest reasonable interpretation, isolating slow wave contractility signal, preparing a data profile, comparing the data profile, and determining a pelvic condition can be done mentally with the aid of a pen and paper. A person can receive measurements of electrical activity of a target pelvic structure in forms of data table or graph. Then from the data table or the graph, the person can isolate electrical activity measurement by selecting relevant parts of the data table or the graph that mathematically indicates a slow wave contractility parameter. The person can prepare a data profile by creating a series of collections of plurality of slow wave contractility parameter on paper either as a data table or a graph. Then the person can compare the data profile with other reference data profiles whose data is created similarly either as a data table or a graph. Lastly, the pelvic condition can be determined mathematically or visually when the comparison is likely an indication of a pelvic condition status.
Prong two: Claims 1-6 and 14-15 do not include additional elements that integrate the abstract into a practical application.
The additional elements are as follows:
Measuring electrical activity (claim 1)
wearable non-invasive sensor (claim 3)
Reciting measuring electrical activity or wearable non-invasive sensor do not integrate the exception into a practical application since it is merely insignificant extra-solution activity to the judicial exception, e.g., mere data gathering at a higher level of generality.
Therefore, claims 1-6 and 14-15 are ineligible at step 2A, prong two.
Step 2B of the subject matter eligibility test (see MPEP 2106.05)
Reciting measuring electrical activity or wearable non-invasive sensor do not integrate the exception into a practical application since it is merely insignificant extra-solution activity to the judicial exception, e.g., mere data gathering at a higher level of generality.
U.S. Patent Application Publication No. US 20170360358 A1 discloses that measuring electrical activity or wearable non-invasive sensor are conventional: [0066], “off-the-shelf consumer electronic devices such as, for example, Fitbit, Jawbone, Apple Watch, or other consumer wearable electronic devices that measure various parameters indicative of different aspects of the wearer's physical or mental wellbeing or other characteristics.”
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above-judicial exception (the abstract idea). Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Therefore, claims 1-6 and 14-15 are ineligible at step 2B.
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.
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 1-3, 5-6 and 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over US20170128722A1 (Perez, Raul E.), hereto referred as Perez, and in view of US20020193670A1 (Garfield et. al), hereto referred as Garfield.
As to claim 1, Perez teaches determining a pelvic condition status in a subject comprising the steps of: measuring electrical activity of a target pelvic structure at a plurality of spaced apart time points during the subject's hormonal cycle (Perez, [0273], "processing and analyzing data generated by a uterine contraction sensor, such as an acoustic sensor, included as one of the sensors 135"; [0181], "one or more sensors 135 to generate data representative of various physiological parameters of an individual, such as …galvanic skin response or GSR, EMG, EEG....”);
preparing a data profile comprising the plurality of signals comprising the slow wave contractility parameter measurements (Perez, [0241], "physiological sensors, configured to be worn on the human body, such as around the wrist, in order to monitor, acquire, record, and/or transmit the physiological data");
one or more reference data profiles, in which each reference data profile comprises a plurality of slow wave contractility parameter measurements of a reference subject's target pelvic structure taken at a plurality of spaced-apart time points during the reference subject's hormonal cycle (Perez, [0442], “It should be appreciated that each of the pre-stimulation and post-stimulation levels, profiles or measurements may be assessed by comparing data from a single individual or by first aggregating pre-stimulation data from multiple individuals and post-stimulation data from multiple individuals and comparing the two aggregated data sets.”).
Although Perez teaches onset of uterine contraction can trigger treatment (Perez, [0273], “Data obtained by the uterine contraction sensor can be used to trigger stimulation.”), Perez does not explicitly teach the detailed steps of detecting the pelvic condition status. Garfield teaches a relevant art of detecting the pelvic condition status (Garfield, abstract). Garfield teaches:
isolating from each electrical activity measurement a signal comprising a slow wave contractility parameter measurement representative of the target pelvic structure (Garfield, claim 1, b, "isolating a system from the patient for analog filtering and amplifying an electrical signal as appropriate to isolate desired frequency components of said signal from background noise in said signal");
comparing the data profile with one or more reference data profiles (Garfield, [0093], "When such classification/clinical data are entered into the program, and after the results of uterine signal analysis, using any one or more of the mathematical parameters described in block 65 above, data are compared with normal values"),
determining a pelvic condition status of the subject based on the comparison (Perez, “an input of a degree of the patient's dysmenorrhea”; Garfield, claim 1, f, “using detection algorithms to detect one or more attributes of said uterine, maternal or fetal cardiac activity”)).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Perez in view of Garfield to include data processing details of isolating a signal comprising a slow wave contractility parameter measurement, comparing data profile with one or more reference data profiles, and determining pelvic condition status of the subject because Perez already recognizes the necessities of determination of pelvic status, and Garfield supplies the detailed procedures that Perez does not necessarily teach.
As to claim 2, Perez does not teach the frequency of the contraction. However, Garfield teaches the contractility parameter is a slow wave electrical contractility frequency (Garfield, [0014], "about 0.001 Hz to about 3.000 Hz for uterine EMG"). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Perez in view of Garfield to include the contractility parameter is a slow wave electrical contractility frequency because Perez teaches placing the device on pelvic area (Perez, [0217], “dermatomes T9 to T12, L1, L2, L5 and/or S1 to S4 dermatomes”), and Garfield explicitly supplies the details of relevant electrical contractility for the pelvic area.
As to claim 3, Perez-Garfield teaches the measuring step employs a wearable non-invasive sensor (Perez, [0333], "dermal patch device 110 of FIG. 1A) provides for a non-invasive treatment of pain management").
As to claim 5, Perez-Garfield teaches the target pelvic structure is selected from the uterus, the pelvic floor, and the prostate (Perez, [0273], "uterine contraction sensor").
As to claim 6, Perez-Garfield teaches the subject is a non-pregnant female (Garfield, [0003], "in non-pregnant patients where hypercontractility is associated with dysmenorrhea ");
the target pelvic structure is a uterus or pelvic floor (Perez, [0273], “uterine contraction senso”); the pelvic condition is an endocrine condition characterised by abnormal contractility activity of the target pelvic structure (Garfield, [0166], “One of these is dysmenorrhea. It is caused by cramping during parts of the menstrual cycle”); and (Perez, [0032], “Dysmenorrhea is the medical term used to describe pain experienced immediately before or during menstruation”)
the measuring step comprises measuring electrical activity of the subjects uterus or pelvic floor at a plurality of spaced apart time points during the subject's menstrual cycle (Perez, [0273], "processing and analyzing data generated by a uterine contraction sensor, such as an acoustic sensor, included as one of the sensors 135"; [0181], "one or more sensors 135 to generate data representative of various physiological parameters of an individual, such as …galvanic skin response or GSR, EMG, EEG....”).
As to claim 14, Perez-Garfield teaches the method includes a step of measuring at least one non-electrical hormonal cycle parameter at a plurality of time points during the subject's hormonal cycle (Perez, [0397], "menstrual cycle"), wherein the data profile comprises the slow wave contractility parameter measurements representative of the target pelvic structure and the non-electrical hormonal cycle parameter measurements, and in which the non-electrical hormonal cycle parameters are selected from bleeding, fatigue, pain intensity, and pain occurrence (Perez, [0397], "pain profile").
As to claim 15, Perez-Garfield teaches the method includes a step of determining at least one non-electrical non-hormonal cycle parameter, wherein the data profile comprises the slow wave contractility parameter measurements representative of the target pelvic structure, and the non-electrical non-hormonal cycle parameter measurements, and in which the non-electrical non-hormonal cycle parameter is selected from sex, age, reproductive status, hormonal cycle status, previous diagnoses or conditions, family history, medical records, medical imaging, BMI, and medication (Perez, [0404], "The separate monitoring device is configured to measure a plurality of physiological parameters, including, but not limited to, patient weight, body fat, lean mass, and BMI"; [0295], "interface 1300 may also provide to the user an ability to track intake of birth control pills and correlate this information with dysmenorrhea and related symptoms")
As to claim 16, Perez-Garfield teaches the subject is determined to be positive for a pelvic condition characterised by abnormal target pelvic structure contractility (Perez, [0060], "based upon an input of a degree of the patient's dysmenorrhea symptoms"), the method includes a step of treating the pelvic condition by administering electrostimulation to the target pelvic structure configured to normalise abnormal target pelvic structure contractility (Perez, [0397], "During the treatment cycle, if the patient experiences decrease in pain or other symptoms of dysmenorrhea, the companion device slowly lowers stimulation to a minimum threshold or leaves stimulation unchanged at step 2214").
As to claim 17, Perez-Garfield teaches the electrostimulation comprises electrostimulation of the target pelvic structure with electrical pulses of 0.1 to 20 mA, a pulse width of 500 μs to 20 ms, and a frequency of 0.1 to 50 Hz (Perez, [0078], "Optionally, the pulse width is equal to 200 μsec, the pulse amplitude is equal to 5 mA, the pulse frequency is equal to 20 Hz"; [0059], “Optionally, said stimulation pulse width is in a range of 10 μsec to 100 msec”).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Perez-Garfield as applied to claim 1 above, and further in view of WO2008144613A1 (Quinones et. al), hereto referred as Quinones.
Claim 1 is taught as above.
As to claim 4, Perez teaches the subject's data profile is compared to reference data profiles (Perez, [0244], “For example, in an aggregate patient data network, multiple different patients have an EDP communicating with a personal companion device.”), and teaches a model generated using reference data profiles from a population of reference subjects with a known pelvic condition status (Perez, [0442], “It should be appreciated that each of the pre-stimulation and post-stimulation levels, profiles or measurements may be assessed by comparing data from a single individual or by first aggregating pre-stimulation data from multiple individuals and post-stimulation data from multiple individuals and comparing the two aggregated data sets.” ).
However, Perez does not teach that the subject's data profile is correlated with pelvic condition status by employing a classification model, which Garfield teaches (Garfield, [0093], "Once patient classification/clinical data for a patient are entered into the computer, and after the results of cardiac signal analysis, using any one or more of the mathematical parameters described in block 65 above, data are compared with normal values. Then an assessment is made as to the normality/abnormality of the maternal and fetal cardiac activity."). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Perez in view of Garfield to include that the subject's data profile is correlated with pelvic condition status by employing a classification model generated using reference data profiles from a population of reference subjects with a known pelvic condition status because Perez already has the means to correlated data with reference data profile, and Garfield teaches the detailed steps of doing so.
However, Perez-Garfield does not teach that the known pelvic condition status are selected from positive for the condition, negative for the condition, risk of developing the condition, and severity of the condition. Quinones teaches a solution to a relevant art of determining a disorder status (Quinones, abstract, “capable of classifying subjects according to bipolar disorder status”). Quinones teaches known condition status are selected from positive for the condition, negative for the condition, risk of developing the condition, and severity of the condition (Quinones, pg. 30, lines 16-17, “A neural network is trained by introducing a population of subjects in which the bipolar disorder status is known”; Pg. 4, lines 28-30, “the presence or absence of the disorder, the risk of developing the disorder, the stage of the disorder”). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Perez-Garfield in view of Quinones to include that known condition status are selected from positive for the condition, negative for the condition, risk of developing the condition, and severity of the condition as Perez-Garfield teaches determining endocrine disorder status, and Quinones supplies a method of delivering the status with more useful details.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ELINA S JANG whose telephone number is (571)272-7019. The examiner can normally be reached M-F 9:00 am - 6:00 pm.
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/ELINA SOHYUN JANG/Examiner, Art Unit 3791
/JENNIFER ROBERTSON/Supervisory Patent Examiner, Art Unit 3791