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 .
Response to Arguments
Applicant's arguments filed 7 April 2026 have been fully considered but they are persuasive only in part.
First, regarding the rejections under 35 U.S.C. 112(a), description requirement, applicant’s amendments overcome the previous rejections with the exception of claim 6 (and claim 7 depending therefrom) that still has (have) unaddressed issues in this respect, as indicated previously and below. However, new issues in this respect based on the claim amendment are dealt with below.
Second, regarding the rejections under 35 U.S.C. 112(b), applicant’s claim amendments overcome most of the previous claim rejections, with remaining (e.g., the “care plan” which, while deleted in claim 3, is still present in claim 13) and new issues dealt with below.
Third, regarding the rejection under 35 U.S.C. 101, applicant’s arguments are persuasive at least in part with respect to the second and third independent claims 11 and 20 which as amended require, as a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), the modifying, based on e.g., the reduction in the speed of the gait of the person over the period of time and a speed reduction threshold or based on the gait speed determined based on the location difference, of one or more directional indicators in a space where the person is located, and therefore integrate any abstract into a practical application, but they are NOT persuasive as to method claim 1, since the corresponding limitation is recited in claim 1 contingently/conditionally in the method and therefore “need not be carried out in order for the claimed method to be performed” (Schulhauser[1]), and thus the method does not require the transformation of the article to the different state, with the rejections under 35 U.S.C. 101 of claims 1, 3, 6 to 8, and 10 being reformulated to address the claim amendments..
In this respect, applicant does not seem to argue against the rejection under 35 U.S.C. 101 of claim 1 (or claim 20) in any particular way, and the examiner does not necessarily agree with (all of) applicant’s particular arguments regarding claim 11.
Fourth, applicant’s arguments concerning the rejection of the claims under 35 U.S.C. 103 are convincing e.g., as to independent claims 11 and 20, in that the previously applied art apparently does not reveal or render obvious the modifying, based on the gait speed which is determined based on the claimed location difference and/or based on a reduction in the so-determined gait speed of the person over the period of time and a speed reduction threshold, one or more directional indicators in a space where the person is located. Accordingly the previous rejections are withdrawn.
However, the examiner applies a newly cited modifying reference against claim 1 in the 35 U.S.C 103 rejection, Moon et al. (KR 10-2018-0052513 A), which incorporates lighting units (e.g., 210-1, 210-2, 330) into connectable walking mats 110-1, 110-2 for fall prevention, and controls one or more light-emitting units of the lighting units to emit light when the user’s walking speed continues to decrease (e.g., from 50 cm/sec to 45 cm/sec to 40 cm/sec in paragraph [0091] over a series of steps (FIG. 9(B)), so that the user can visually recognize that they are walking abnormally, with FIGS. 1 and 2 from Moon et al. (KR, ‘513) being reproduced below/on the next page by the examiner:
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Accordingly, applicant’s arguments are only persuasive in part.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the one or more directional indicators that are modified (in claims 1, 11, and 20) must be shown or the feature(s) canceled from the claim(s). No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
INFORMATION ON HOW TO EFFECT DRAWING CHANGES
Replacement Drawing Sheets
Drawing changes must be made by presenting replacement sheets which incorporate the desired changes and which comply with 37 CFR 1.84. An explanation of the changes made must be presented either in the drawing amendments section, or remarks, section of the amendment paper. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). A replacement sheet must include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of the amended drawing(s) must not be labeled as “amended.” If the changes to the drawing figure(s) are not accepted by the examiner, applicant will be notified of any required corrective action in the next Office action. No further drawing submission will be required, unless applicant is notified.
Identifying indicia, if provided, should include the title of the invention, inventor’s name, and application number, or docket number (if any) if an application number has not been assigned to the application. If this information is provided, it must be placed on the front of each sheet and within the top margin.
Annotated Drawing Sheets
A marked-up copy of any amended drawing figure, including annotations indicating the changes made, may be submitted or required by the examiner. The annotated drawing sheet(s) must be clearly labeled as “Annotated Sheet” and must be presented in the amendment or remarks section that explains the change(s) to the drawings.
Timing of Corrections
Applicant is required to submit acceptable corrected drawings within the time period set in the Office action. See 37 CFR 1.85(a). Failure to take corrective action within the set period will result in ABANDONMENT of the application.
If corrected drawings are required in a Notice of Allowability (PTOL-37), the new drawings MUST be filed within the THREE MONTH shortened statutory period set for reply in the “Notice of Allowability.” Extensions of time may NOT be obtained under the provisions of 37 CFR 1.136 for filing the corrected drawings after the mailing of a Notice of Allowability.
Specification
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o)2. Correction of the following is required: antecedent basis should be provided in the specification, without adding new matter, for the new independent claim terminology, “whether the reduction in speed . . . is greater than or equal to a speed reduction threshold”, “modifying one or more directional indicators in a space where the person is located”, “object sensor”, “determine that the location of the person in the object data from the object sensor does not match a location of the person in the floor contact data”, and “input the object data from the object sensor and the floor contact data into one or more machine learning models trained to determine that the location of the person in the object data from the object sensor does not match a location of the person in the floor contact data and to determine a speed of a gait of the person based on the difference between the location of the person in the object data from the object sensor and the location of the person in the floor contact data”, so that the meaning of the terms in the claims may be ascertainable by reference to the description.
Claim (Specification) Objections
Claim 20 is objected to because of the following informalities: in second to last line of claim 20, “modifying” should apparently read, “modify” (cf. claim 11), for grammatical correctness and consistency. Appropriate correction is required.
Claim Interpretation
Regarding contingent or conditional clauses, including the contingent/conditional act/step of performing of the intervention as now recited in the last limitation (act/step) of claim 1[3], the examiner applies the guidance of MPEP 2111.04, II. and the PTAB Decision in Ex parte RANDAL C. SCHULHAUSER et al. (Precedential), Appeal 2013-007847, decided 28 April 2016, where the Board decided:
"A proper interpretation of claim language, under the broadest reasonable interpretation of a claim during prosecution, must construe the claim language in a way that at least encompasses the broadest interpretation of the claim language for purposes of infringement. . . . [In a method claim, if] the condition for performing a contingent step is not satisfied, the performance recited by the step need not be carried out in order for the claimed method to be performed. . . . [However, the] broadest reasonable interpretation of a system claim having structure that performs a function, which only needs to occur if a condition precedent is met, still requires structure for performing the function should the condition occur. This interpretation of the system claim differs from the method claim because the structure [] is present in the system regardless of whether the condition is met and the function is actually performed. Unlike [the method claim], which is written in a manner that does not require all of the steps to be performed should the condition precedent not be met, [the system claim] is limited to the structure capable of performing all the recited functions."
If applicant intends this act/step to not be interpreted by the examiner as contingent/conditional, then a change of the claim phrase from, “if the reduction in speed . . .” to, “when the reduction in speed . . .”, would show the examiner that applicant intends for the act/step to not be contingent, and that the act/step must be carried out for the method of claim 1 to be performed.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 3, 6 to 8, 10, 11, 13, 16 to 18, and 20 to 24 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 1, applicant has apparently not previously described, in sufficient detail, by what algorithm(s)4, or by what steps or procedure, he determined whether the reduction in the speed of the gait of the person over the period of time is greater than or equal to a speed reduction threshold, and conditioned the performance of the intervention (i.e., the modification of the one or more directional indicators) on the gate speed reduction being “greater than or equal to the speed reduction threshold”. Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope5 of the claimed invention, but has only described (e.g., in the claims), a desired result.
In this respect, published paragraph [0042] of the specification indicates:
[0042] Based on the one or more parameters, the cloud-based computing system may determine an amount of gait deterioration. For example, the cloud-based computing may determine that the speed of the gait of the person reduced by a certain amount, and the amount of gait deterioration is a certain percentage or value based on the amount of gait speed reduction. The cloud-based computing system may determine whether a propensity for the fall event for the person satisfies a threshold propensity condition based on (i) the amount of gait deterioration satisfying a threshold deterioration condition, or (ii) the amount of gait deterioration satisfying the threshold deterioration condition within a threshold time period. The propensity of the fall event may be scored or categorized into a level of 1 to 5 (any suitable range), where a 1 is the lowest score or category where the propensity for the fall event is the lowest and not likely to occur and a 5 is the highest score or category where the propensity for the fall event is the highest and most likely to occur. The cloud-based computing system may use one or more machine learning models trained to monitor the parameter pertaining to the gait of the person based on the data, determine the amount of gait deterioration based on the parameter, and/or determine whether the propensity for the fall event for the person satisfies the threshold propensity condition.
However, this does not apparently describe a speed reduction threshold, or any algorithm(s) for determining “whether” the gait speed reduction is “greater than or equal to a speed reduction threshold”. Nor does this passage describe that the intervention is conditioned on the reduction in the speed of the gait of the person over the period of time being greater than or equal to the speed reduction threshold, as now claimed in claim 1. Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope of the claimed invention, but has only described (e.g., in the claims), a desired result.
Regarding claim 6, and as previously indicated at paragraphs 7 and 8 of the Office action dated 7 October 2025, applicant has apparently not described, in sufficient detail, by what algorithm(s), or by what steps or procedure, he monitored parameters including, “a distance between a head of the person and feet of the person”, “historical information pertaining to whether the person has previously fallen”, “an age of the person”, “medical history of the person”, “fracture history of the person”, “vision impairment of the person”, “neurological condition of the person” (e.g., epilepsy) based on at least the floor contact data (claim 1), and from those monitored parameters (and the speed of the gait of the person) he determined a reduction in the speed of the gait of the person over the period of time. That is, no algorithm(s) for monitoring the full scope of these parameters (e.g., age of the person, etc.) as encompassed/covered by the claim based on the floor contact data received from a sensing device in the smart floor tile (with or without using computer vision, object recognition, measured pressure, and/or location of the feet of the person as required by claim 7) are apparently described in the specification in sufficient detail, and no algorithm(s) that might use e.g., “a distance between a head of the person and feet of the person”, “historical information pertaining to whether the person has previously fallen”, “an age of the person”, “medical history of the person”, “fracture history of the person”, “vision impairment of the person”, and/or “neurological condition of the person”, as being the one or more parameters that was also based on floor contact data, in order to determine the reduction in gait speed, are apparently described in sufficient detail, in the specification. Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope of the claimed invention, but has only described (e.g., in the claims), a desired result.
For examples only, by what algorithm(s) was the head/feet distance monitored based on floor contact data received from a sensing device in a smart floor tile, by what algorithm(s) was the historical information or the age or the medical or fracture history of the person monitored based on floor contact data received from a sensing device in a smart floor tile, by what algorithm(s) was the vision impairment or neurological condition (e.g., epilepsy) of the person monitored based on floor contact data received from a sensing device in a smart floor tile, from the teachings of the specification? And by what algorithm(s) were the parameters listed in claim 6 (e.g., vision impairment) used in any way to determine the reduction in gait speed, from the teachings of the specification? Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope of the claimed invention, but has only described (e.g., in the claims), a desired result.
Regarding claims 11 and 20, applicant has apparently not previously described, in sufficient detail, by what algorithm(s), or by what steps or procedure, he determined that the location of the person in the object data from the object sensor does not match a location of the person in the floor contact data, and/or determined a speed of a gait of the person based at least in part on the difference between the location of the person in the object data from the object sensor and the location of the person in the floor contact data. No algorithm(s) for (aligning or) matching of the person’s location in the object data and the floor contact data is apparently described, and no determination that the location of the person in the object data “does not match” the location of the person in the floor contact data is apparently described, in sufficient detail. Additionally, no algorithm(s) for determining the gait speed of the person based on the difference between the location of the person in the object data and the location of the person in the floor contact data is apparently described, in sufficient detail. Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope of the claimed invention, but has only described (e.g., in the claims), a desired result.
In this respect, while the specification apparently refers to no “object sensor” or “object data”, the examiner understands these terms to apparently be intended to refer to the “various sensors” used in the moulding sections “to obtain moulding section sensor data including the locations in a physical space as the objects move around the physical space” (published paragraph [0039] of the specification; see also published paragraph [0065]).
In this context, published paragraph [0067] indicates:
[0067] In some embodiments, the moulding section sensor data can be used to verify the impression tile data and/or image data of the camera 50 is accurate for predicting a fall event for the person 25. Such a technique may improve accuracy of the determination. Further, if the moulding section sensor data, the impression tile data, and/or the image data do not align (e.g., the moulding section sensor data does not indicate a fall event will occur and the impression tile data indicates a fall event will occur), then further analysis may be performed. For example, tests can be performed to determine if there are defective sensors at the corresponding smart floor tile 112 and/or the corresponding moulding section 102 that generated the data. Further, control actions may be performed such as resetting one or more components of the moulding section 102 and/or the smart floor tile 112. In some embodiments, preference to certain data may be made by the cloud-based computing system 116. For example, in one embodiment, preference for the impression tile data may be made over the moulding section sensor data and/or the image data, such that if the impression tile data differs from the moudling section sensor data and/or the image data, the impression tile data is used to predict the propensity for the fall event.
.It appears that the data which is verified or aligned (between the moulding section sensor data and the impression tile data) is the data that is used “for predicting a fall event for the person” or data “which indicates a fall event will occur”. However, the specification apparently does not describe determining that there is a mismatch or a difference in the location of the person in the object data and the floor contact data, or describe the algorithm(s) for determining that there is such a mismatch in sufficient detail, even implicitly, since the specification does apparently clearly describe that the determined location(s) of the person and/or the claimed location difference are used in any algorithm(s) to predict a fall event or to indicate that the fall event will occur.6 Similarly, the specification does not apparently describe algorithm(s) for determining the gait speed of the person based at least in part on the difference between the location of the person in the object data from the object sensor and the location of the person in the floor contact data, e.g., with such a location difference also not apparently being described in the specification.
Regarding claims 18 and 24, applicant apparently has not previously described, in sufficient detail, by what algorithm(s), or by what steps or procedure, he inputted the object data from the object sensor and the floor contact data into one or more machine learning models trained to determine that the location of the person in the object data from the object sensor does not match a location of the person in the floor contact data and to determine a speed of a gait of the person based on the difference between the location of the person in the object data from the object sensor and the location of the person in the floor contact data. Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope of the claimed invention, but has only described (e.g., in the claims), a desired result.
In this respect, published paragraph [0135] indicates:
[0135] The cloud-based computing system 116 may receive data 754 from the smart floor tiles 112, the moulding sections 102, and/or the camera 50. The data may be input into one or more machine learning models 154 that are each trained to monitor a particular parameter using the data and determine an amount of gait deterioration based on the monitored parameter. For example, the machine learning models 154 include a stride variability machine learning model 154.1, a walking speed machine learning model 154.2, a balance machine learning model 154.3, and a normalized activity (physical) machine learning mode 154.4. The machine learning models 154.1-154.4 may be trained to determine an amount of gait deterioration for a particular parameter. The amount of gait deterioration may include a category, a score, a rate, a percentage, or any suitable indicator the provides a measurement of the amount of gait deterioration.
In the specification, the amount of gait deterioration is apparently determined based on the speed of the gait of the person being reduced by a certain amount, and/or based on the other parameters now recited in claims 6, 16, and 22. However, the specification does not apparently describe (nor do those claims apparently indicate) that the parameter is/was/would have been the location or location difference of the person, or that the gait deterioration is/was/would have been determined based on the location or location difference of the person. Accordingly, the examiner believes applicant has not evidenced, to those skilled in the art, possession of the full scope of the claimed invention, but has only described (e.g., in the claims), a desired result.
Claims 1, 3, 6 to 8, 10, 11, 13, 16 to 18, and 20 to 24 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In claim 1, lines 9ff, “determining whether the reduction in the speed of the gait of the person over the period of time is greater than or equal to a speed reduction threshold” is indefinite from the teachings of the specification that apparently uses or clarifies no explicit “threshold” used in conjunction with any gait speed reduction determination, and apparently does not explicitly determine “whether” the gait speed is “greater than or equal to” any threshold, value, amount, etc. (e.g., the “certain amount” in published paragraph [0042]).
In claim 8, lines 5ff, “the period of time the speed reduction threshold” is unclear.
Similarly, in claim 8, lines 10ff, “the period of time the speed reduction threshold” is unclear.
In claim 11, lines 6ff, and in claim 20, line 13, “[determine that the location. . .] does not match” is indefinite as being facially subjective (e.g., what degree of location difference between the object data and the floor contact data should be determined as a mismatch, i.e., ”does not match”?), with no objective standard provided in the specification to allow the public to determine the scope of the claim phrase. See MPEP 2173.05(b), IV.
In claim 13, line 8, "care plan" is indefinite and not reasonably certain from the teachings of the specification, with indeterminate metes and bounds (e.g., a care plan defined particularly how? For example, is warning a care giver a care plan? Why or why not?)
Claim(s) depending from claims expressly noted above are also rejected under 35 U.S.C. 112 by/for reason of their dependency from a noted claim that is rejected under 35 U.S.C. 112, for the reasons given.
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, 3, 6 to 8 and 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1 and Step 2A, Prong I:
Claim(s) 1, 3, 6 to 8, and 10, while (each) reciting a statutory category of invention defined in 35 U.S.C. 101 (a useful process, machine, manufacture, or composition of matter), is/are directed to an abstract idea, which is a judicial exception, the recited abstract idea being that of monitoring one or more parameters pertaining to a gait of a person based on the floor contact data, the one or more parameters comprising at least a speed of a gait of a person; determining a reduction in the speed of the gait of the person over a period of time an amount of gait deterioration based on the one or more parameters; determining whether the reduction in the speed of the gait of the person over the period of time is greater than or equal to a speed reduction threshold; and performing an intervention if the reduction in the speed of the gait of the person over the period of time is greater than or equal to the speed reduction threshold, e.g., by receiving floor contact data from a sensing device in a smart floor tile; monitoring one or more parameters pertaining to a gait of a person based on the floor contact data, the one or more parameters comprising at least a speed of a gait of a person; determining a reduction in the speed of the gait of the person over a period of time an amount of gait deterioration based on the one or more parameters; determining whether the reduction in the speed of the gait of the person over the period of time is greater than or equal to a speed reduction threshold; and performing an intervention if the reduction in the speed of the gait of the person over the period of time is greater than or equal to the speed reduction threshold, the intervention comprising modifying one or more directional indicators in a space where the person is located; wherein the intervention further comprises: transmitting a first message to a computing device of the person, transmitting a second message to a computing device of a medical personnel, causing an alarm to be triggered in a facility in which the person is located, changing a property of an electronic device located in a physical space with the person, or some combination thereof; wherein the one or more parameters further comprise at least one of: a distance between a head of the person and feet of the person, a distance between the feet during the gait of the person, historical information pertaining to whether the person has previously fallen, a weight of the person, an age of the person, medical history of the person, fracture history of the person, vision impairment of the person,
activity level of the person, balance distribution of weight while stationary, during gait, or both, neurological condition of the person, change in stride of the person, results of a calibration test, or some combination thereof; wherein at least one of the one or more parameters is monitored using computer vision, object recognition, measured pressure, location of feet of the person, or some combination thereof; wherein the monitoring the one or more parameters, the determining the reduction in the speed of the gait of the person over the period of time based on the one or more parameters, and the determining whether the reduction in the speed of the gait of the person over the period of time the speed reduction threshold propensity condition further comprises: inputting the floor contact data into one or more machine learning models trained to determine the reduction in the speed of the gait of the person over the period of time based on the one or more parameters and to determine whether the reduction in the speed of the gait of the person over the period of time the speed reduction threshold; and further comprising: calibrating one or more gait baseline parameters for the person; and determining the reduction in the speed of the gait of the person over the period of time based on comparing the one or more parameters to at least one of the one or more gait baseline parameters.
This abstract idea falls within the grouping(s) of mathematical concepts, mental processes, and/or certain methods of organizing human activity, distilled from case law, because the monitoring of the parameters, the determining regarding the reduction in speed of the gait and whether the is greater than or equal to a speed reduction threshold, the performing of the intervention (e.g., by speaking, etc.) are mental processes that could be practically performed in the human mind, with the comparison (whether the speed reduction is greater than or equal to the speed reduction threshold) also being a mathematical concept.
Step 2A, Prong II and Step 2B:
Additionally, applying a preponderance of the evidence standard, the abstract idea is not integrated (e.g., at Step 2A, Prong II) by the recitation of additional elements/limitations into a practical application (using the considerations set forth in MPEP §§ 2106.04(a)-(h)) because merely using a computer (e.g., including one or more machine learning models) as a tool to perform an abstract idea or adding the words "apply it" is not integrating the idea into a practical application of the idea, and e.g., looking at the claim as a whole and considering any additional elements/limitations individually and in combination, no (additional) particular machine, transformation, improvement to the functioning of a computer or an existing technological process or technical field, or meaningful application of the idea, beyond generally linking the idea to a technological environment (e.g., "implementation via computers", Alice) or adding insignificant extra-solution activity (e.g., receiving data from a sensing device in a smart floor tile as mere data gathering, performing an intervention that is not recited as a particular treatment or prophylaxis for a disease or medical condition, modifying a directional indicator which is recited contingently in the method and therefore need not be carried out for the method to be performed, etc.; see e.g., MPEP 2111.04, II.), is recited in or encompassed by the claims. Therefore, the claim is not integrated into a practical application and is thus "directed to" the exception.
Moreover, applying a preponderance of the evidence standard, the claim(s) does/do not include additional elements/limitations/steps (e.g., at Step 2B) that are, individually or in ordered combination, sufficient to amount to significantly more than the judicial exception because the elements/limitations/steps are recited at a high level of generality (e.g., a smart floor tile, performing the intervention with the contingently claimed modification of the directional indicator, etc.) so as to not favor eligibility (MPEP § 2106.05(d); see also MPEP 2111.04, II.) and/or are used e.g., for data/information gathering only or for other activities that were well-understood, routine, and conventional activity in the industry (see the literature cited with the Office action of 7 October 2025 regarding using smart floor tiles for data gathering), for example as indicated in applicant's specification at published paragraph [0003], and moreover, the generically recited computer elements (e.g., computing device, electronic device, computer vision, object recognition, machine learning models, etc.; see e.g., Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 110 USPQ2d 1984 (2014); buySAFE, Inc. v. Google, Inc., 765 F.3d. 1350, 112 USPQ2d 1093 (Fed. Cir. 2014); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 115 USPQ2d 1090 (Fed. Cir. 2015); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1321, 120 USPQ2d 1353, 1362; Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-1355, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 1096 (Fed. Cir. 2016) (“[T]he use of generic computer elements like a microprocessor or user interface do not alone transform an otherwise abstract idea into patent-eligible subject matter.”); Mobile Acuity, Ltd. v. Blippar Ltd., Case No. 22-2216 (Fed. Cir. Aug. 6, 2024); see also the 2019 PEG Advanced Module at pages 89, 145, etc.) do not add a meaningful limitation to the abstract idea because their use would be routine (and conventional) in any computer implementation of the idea.
Moreover, limiting or linking the use of the idea to a particular technological environment (e.g., a method using a smart floor tile and one or more directional indicators for insignificant extra-solution activity) is not enough to transform the abstract idea into a patent-eligible invention (Flook[7]) e.g., because the preemptive effect of the claims on the idea within the field of use would be broad.
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.
Claims 1, 6 to 8, and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Cole et al.8 (2015/0282766) in view of MacKinnon et al. (2014/0307118) and Moon et al.9 (Korea, 10-2018-0052513; EPO machine translation attached).
Cole et al. (‘766), assigned to Tactonic Technologies, LLC, reveals:
per claim 1, a method for determining a propensity for a fall event to occur [e.g., paragraph [0003], “predict the propensity to fall”], the method comprising:
receiving floor contact data [e.g., from the sensor 21 in FIG. 2, at 42 in FIG. 5, at 51 in FIG. 6, etc.] from a sensing device in a [e.g., the plurality of sensor tiles forming a walkway (FIG. 2), such as Tactonic Technology LLC's pressure sensing floor tiles (paragraph [0053])10; see also paragraphs [0087], [0090], [0106], etc.];
monitoring one or more parameters pertaining to a gait of a person based on the floor contact data [e.g., paragraph [0003], “changes in gait parameters can monitor the progression of certain diseases. The measurements of gait, balance, and activity can be used to monitor the person's ergonomic performance and provide a means to give feedback information to the worker or to a system in order to reduce risk or increase the overall performance and efficiency of the work and the system”; and e.g., in the data processing & analytics unit (as described at paragraphs [0083], [0103], etc., for using/monitoring gait velocity and balance measurements)], the one or more parameters comprising at least a speed of a gait of a person [e.g., paragraph [0083], “There may be the step of calculating gait velocity and balance using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times to calculate the future risk of falling using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times and correlating them with changes in a reference collection of expert judgments about the future risk of falling based on sequences of gait velocity and balance measurements recorded at disparate times.”];
determining [e.g., paragraph [0083], “There may be the step of calculating gait velocity and balance using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times to calculate the future risk of falling using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times and correlating them with changes in a reference collection of expert judgments about the future risk of falling based on sequences of gait velocity and balance measurements recorded at disparate times.”];
. . .
It may be alleged that the floor tiles in Cole et al. (‘766) are not explicitly described as being “smart”, although the examiner understands that these tiles must have aspects that are intelligent or smart, since their outputs are sent to a signal processing unit, and e.g., dumb floor tiles would apparently not have any outputs that might be signal processed/processable.
Cole et al. (‘766) also may not/does not apparently reveal detail related to the “reduction” in speed of the gait of the person and the conditional intervention as claimed including the modifying of the directional indicator(s), although Cole et al. (‘766) teaches e.g., at paragraph [0083] that changes in gait velocity may be used to calculate the future risk of falling, and the act/step of performing the intervention is recited contingently/conditionally in the claim and therefore need not be carried out for the method to be performed (see MPEP 2111.04, II.)
However, in the context/field of improved sensor tiles used for gait analysis and, for example, detecting whether someone has fallen, MacKinnon et al. (‘118) teaches the use of smart tiles having both sensors and microprocessors, for allowing the sensors to communicate with a host computer.
Moreover, in the context/field of improved connectable walking mats (110-1, 110-2 in FIG. 2) for fall prevention, Moon et al. (KR, ‘513) teaches e.g., at paragraph [0091] that the mat(s) may be provided with multiple lighting units (e.g., 210-1, 210-2 in FIG. 2, 330 in FIG. 3, etc.) each having e.g., multiple light-emitting units, and when it is determined (using mat pressure information; paragraph [0086]) that the user’s walking speed continues to decrease more than a preset number of times (e.g. from 50 cm/sec to 45 cm/sec to 40 cm/sec over the course of plural steps), the processing unit 320 controls the one or more light-emitting units of the lighting unit (330) to emit light when the user is walking abnormally, so the user can visually recognize they are walk abnormally.
It would have been obvious before the effective filing date of the claimed invention to implement or modify the Cole et al. (‘766) method and apparatus to infer object and agent properties, including the risk of falling, so that the sensor floor tiles used for gait analysis and, for example, detecting whether someone has fallen, would have been smart tiles as taught by MacKinnon et al. (‘118) having both sensors and microprocessors, in order to allow the sensors to communicate with the computer (19), as taught by MacKinnon et al. (‘118), with a reasonable expectation of success, and e.g., as a use of a known technique to improve similar devices (methods, or products) in the same way.
Moreover, it would have been obvious before the effective filing date of the claimed invention to implement or further modify the Cole et al. (‘766) method and apparatus to infer object and agent properties, including the risk of falling, so that the plurality of sensor tiles forming the walkway in Cole et al. (‘766) would have been provided with multiple lighting units (210-1, 210-2, 330), as taught by Moon et al. (KR, ‘513), and when it was determined (using pressure information) that the user’s walking speed continued to decrease, one or more light-emitting units of the lighting unit (330) would have been controlled to emit light when the user is walking abnormally, as taught by Moon et al. (KR, ‘513), in order for the user to be able to visually recognize they are walk abnormally, with a reasonable expectation of success, and e.g., as a use of a known technique to improve similar devices (methods, or products) in the same way.
As such, the implemented or modified Cole et al. (‘766) method and apparatus to infer object and agent properties, including the risk of falling, would have rendered obvious:
per claim 1, a method for determining a propensity for a fall event to occur [e.g., in Cole et al. (‘766), paragraph [0003], “predict the propensity to fall”], the method comprising:
receiving floor contact data [e.g., in Cole et al. (‘766), from the sensor 21 in FIG. 2, at 42 in FIG. 5, at 51 in FIG. 6, etc.] from a sensing device in a smart floor tile [e.g., the smart tiles in MacKinnon et al. (‘118), implementing in Cole et al. (‘766) the plurality of sensor tiles forming a walkway (FIG. 2), such as Tactonic Technology LLC's pressure sensing floor tiles (paragraph [0053])11; see also paragraphs [0087], [0090], [0106], etc. in Cole et al. (‘766)];
monitoring one or more parameters pertaining to a gait of a person based on the floor contact data [e.g., in Cole et al. (‘766), paragraph [0003], “changes in gait parameters can monitor the progression of certain diseases. The measurements of gait, balance, and activity can be used to monitor the person's ergonomic performance and provide a means to give feedback information to the worker or to a system in order to reduce risk or increase the overall performance and efficiency of the work and the system”; and e.g., in the data processing & analytics unit (as described at paragraphs [0083], [0103], etc., for using/monitoring gait velocity and balance measurements)], the one or more parameters comprising at least a speed of a gait of a person [e.g., the walking speed determined in the manner described in conjunction with FIG. 10 (see also FIG. 9(B)) in Moon et al. (KR, ‘613); and in Cole et al. (‘766), paragraph [0083], “There may be the step of calculating gait velocity and balance using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times to calculate the future risk of falling using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times and correlating them with changes in a reference collection of expert judgments about the future risk of falling based on sequences of gait velocity and balance measurements recorded at disparate times.”];
determining a reduction in the speed of the gait of the person over a period of time an amount of gait deterioration based on the one or more parameters [e.g., the “decrease” in walking speed at paragraphs [0091], claim 6, etc. in Moon et al. (KR, ‘613) which occurs e.g., over the period of two or more steps in FIG. 9(B); and in Cole et al. (‘766), paragraph [0083], “There may be the step of calculating gait velocity and balance using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times to calculate the future risk of falling using learned models from the configured machine learning engine. There may be the step of using changes in patterns of gait velocity and balance measurements recorded at disparate times and correlating them with changes in a reference collection of expert judgments about the future risk of falling based on sequences of gait velocity and balance measurements recorded at disparate times.”];
determining whether the reduction in the speed of the gait of the person over the period of time is greater than or equal to a speed reduction threshold [e.g., with the determined “decrease” in speed in Moon et al. (KR, ‘513) (which “decrease” in speed is not a “constant” speed or an “increase” in speed) obviously representing at least (“greater than or equal to”) a small/threshold reduction in speed, such as obviously 5 cm/sec in paragraph [0091] as one example of a “certain amount”, or smaller, to one having ordinary skill in the art; and when the walking speed was obviously determined to be decreasing by some small/threshold amount, in order to distinguish the determined decrease from other determinations of the walking speed remaining constant or increasing, this distinguishing would obviously constitute the “determining whether” aspect of the claim language]; and
performing an intervention [e.g., causing the light-emitting units (e.g., 330) in Moon (KR, ‘513) when the walking speed continues to decrease (by an obvious threshold reduction) for more than a preset number of steps] if the reduction in the speed of the gait of the person over the period of time is greater than or equal to the speed reduction threshold [e.g., meaning if the walking speed continues to be determined as “decreas[ing]” in Moon et al. (KR, ‘513), obviously decreasing by at least a small/threshold amount such as 5 cm/sec in paragraph [0091]], the intervention comprising modifying one or more directional indicators in a space where the person is located [e.g., in Moon et al. (KR, ‘513), the light-emitting units that show the direction(s) to the (lateral) sides of the walkway/mats];
per claim 6, depending from claim 1.wherein the one or more parameters further comprise at least one of:
a distance between a head of the person and feet of the person,
a distance between the feet during the gait of the person,
historical information pertaining to whether the person has previously fallen,
a weight of the person,
an age of the person,
medical history of the person [e.g., paragraph [0103] in Cole et al. (‘766), “Changes in such pattern properties over time can be used as inputs to calculate historical trends and make predictions about the future value of properties and features of an object. One example is prediction of the expected gait velocity and balance of a person. A specific utility of such predictive capacity of the invention is the calculation of the future probability of falling, which has been correlated with declines in observed gait velocity and deteriorating balance.”],
fracture history of the person,
vision impairment of the person,
activity level of the person,
balance distribution of weight while stationary, during gait, or both e.g., the balance in Cole et al. (‘766) at paragraphs [0033], [0083], etc.],
neurological condition of the person,
change in stride of the person [e.g., paragraphs [0101] in Cole et al. (‘766)],
results of a calibration test, or
some combination thereof;
per claim 7, depending from claim 6, wherein at least one of the one or more parameters is monitored using computer vision, object recognition, measured pressure [e.g., as taught in conjunction with FIGS. 1 to 5 of Cole et al. (‘766)], location of feet of the person [e.g., as taught in conjunction with FIGS. 7 to 11 of Cole et al. (‘766)], or some combination thereof;
per claim 8, depending from claim 1, wherein the monitoring the one or more parameters, the determining the reduction in the speed of the gait of the person over the period of time based on the one or more parameters, and the determining whether the reduction in the speed of the gait of the person over the period of time the speed reduction threshold propensity condition further comprises:
inputting the floor contact data into one or more machine learning models [e.g., the trained classifier(s) as taught by Cole et al. (‘766) e.g., in conjunction with FIGS. 2, 4, 5, paragraphs [0083], [0103], claim 12, etc.] trained to determine the reduction in the speed of the gait of the person over the period of time [e.g., the decrease in walking speed as taught by Moon et al. (‘513), e.g., at paragraph [0091]] based on the one or more parameters and to determine whether the reduction in the speed of the gait of the person over the period of time the speed reduction threshold [e.g., to determine the continued walking speed decrease (where the speed obviously goes down by some perceptible amount) in Moon et al. (KR, ‘513)];
per claim 10, depending from claim 1, further comprising:
calibrating one or more gait baseline parameters for the person [e.g., paragraph [0103] in Cole et al. (‘766), “For all object properties and features, patterns of statistical properties and sequences of the pressure observations can be recorded and stored. Changes in such pattern properties over time can be used as inputs to calculate historical trends and make predictions about the future value of properties and features of an object. One example is prediction of the expected gait velocity and balance of a person. A specific utility of such predictive capacity of the invention is the calculation of the future probability of falling, which has been correlated with declines in observed gait velocity and deteriorating balance.”, where recorded and stored initial (pressure) parameters related to gait are obviously baselines from which changes are determined; see also paragraphs [0083], etc.]; and
determining the reduction in the speed of the gait of the person over the period of time based on comparing the one or more parameters to at least one of the one or more gait baseline parameters [e.g., paragraph [0101] in Cole et al. (‘766), “The invention records, classifies, and compares patterns of gait parameters over time periods. Changes in these patterns are classified using a trained classifier to measure current values of properties of a person and predict future values, such as the likelihood of falling”, with the gait parameter changes obviously having been determined relative to an initial gait parameter functioning as a baseline parameter];
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Cole et al.12 (2015/0282766) in view of MacKinnon et al. (2014/0307118) and Moon et al.13 (Korea, 10-2018-0052513; EPO machine translation attached) as applied to claim 1 above, and further in view of Zheng et al. (2020/0205697).
Cole et al. (‘766) as implemented or modified in view of MacKinnon et al. (‘118) and Moon et al. (KR, ‘513) has been described above.
The implemented or modified Cole et al. (‘766) method and apparatus to infer object and agent properties, including the risk of falling, may not reveal the message(s), alarm, or property change as recited in claim 3, although the examiner understands that if only one (1) of the light-emitting units was used in Moon et al. (KR, ‘513) to read on the “one or more directional indicators” of claim 1, then others of the light-emitting units could fairly read on the “electronic device” of claim 3, with Moon et al. (KR, ‘513) also transmitting pressure information to external/portable device 120-1 so that the device can analyze the pressure information and determine whether the user is able to walk normally and transmit the determined result to the walking mat 110.
However, in the context/field of an improved fall risk assessment system, Zheng et al. (‘697) teaches in conjunction with FIG. 13 and at paragraphs [0170] to [0175], etc. that gait features extracted (e.g., from video) over a predetermined time period (e.g., hourly, weekly, etc.) with the assessment system 1300 may be used by a gait analysis module 1312 to estimate a fall risk. For example, determined temporal variations over time in the gait features may be compared to predefined threshold values to identify abnormal behavior or mobility behavior (e.g., the number of steps during a day) or balance ability linked to a high fall risk. When the assessment system determines the high fall risk, a high-fall-risk warning 1340 may be output to a mobile app installed on one or more mobile devices (e.g., of a caregiver).
It would have been obvious before the effective filing date of the claimed invention to implement or further modify the Cole et al. (‘766) method and apparatus to infer object and agent properties, including the risk of falling, so that when a high fall risk was determined, a high-fall-risk warning 1340 would have been output, as taught by Zheng et al. (‘697), e.g., to a mobile app installed on one or more mobile devices (e.g., of a caregiver), as taught by Zheng et al. (‘697), in order to additionally output warnings, as taught by Zheng et al. (‘697), with a reasonable expectation of success, and e.g., as a use of a known technique to improve similar devices (methods, or products) in the same way.
As such, the implemented or modified Cole et al. (‘766) method and apparatus to infer object and agent properties, including the risk of falling, would have rendered obvious:
per claim 3, depending from claim 1, wherein the intervention further comprises:
transmitting a first message to a computing device of the person,
transmitting a second message to a computing device of a medical personnel [e.g., the mobile devices 206 – 208 in Zheng et al. (‘697), monitored by medical personnel, etc. (paragraphs [0047], [0170], etc.)],
causing an alarm to be triggered in a facility in which the person is located [e.g., at the mobile devices 206 – 208 in Zheng et al. (‘697), obviously monitored by medical personnel, etc. (paragraphs [0047], [0170], etc.) in the facility],
changing a property of an electronic device located in a physical space with the person [e.g., of the mobile devices 206 – 208 in Zheng et al. (‘697), monitored by medical personnel, etc. (paragraphs [0047], [0170], etc.); and the external/portable device 120 (120-1) at paragraph [0101] in Moon et al. (KR, ‘513)], or
some combination thereof;
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
For example only, Srinivasan et al. (9,972,187) teaches at column 17, lines 43ff identifying time segments of “large reduction in [walking] speed” as a predictor of fall risk, and teaches at column 20, lines 1ff that the biomechanical parameter determination system (BPDS) “generates alerts that indicate an occurrence of the fall, and/or a health status, and/or a fall risk using the determined biomechanical parameters and transmits the generated alerts to one or more respondents, for example, a caretaker, 911 type emergency service facilities, a health assistant, a senior home, a nursing facility, devices, etc., about the fall via the network for timely intervention.”
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to David A Testardi whose telephone number is (571)270-3528. The examiner can normally be reached Monday, Tuesday, Thursday, 8:30am - 5:30pm E.T., and Friday, 8:30 am - 12:30 pm E.T.
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/DAVID A TESTARDI/Primary Examiner, Art Unit 3664
1 See the Claim Interpretation section below and MPEP 2111.04, II.
2 Quoting the MPEP, “New claims, including claims first presented after the application filing date where no claims were submitted on filing, and amendments to the claims already in the application should be scrutinized not only for new matter but also for new terminology. While an applicant is not limited to the nomenclature used in the application as filed, he or she should make appropriate amendment of the specification whenever this nomenclature is departed from by amendment of the claims so as to have clear support or antecedent basis in the specification for the new terms appearing in the claims. This is necessary in order to insure certainty in construing the claims in the light of the specification. See 37 CFR 1.75, MPEP § 608.01(i) and § 1302.01 and § 2103. Note that examiners should ensure that the terms and phrases used in claims presented late in prosecution of the application (including claims amended via an examiner’s amendment) find clear support or antecedent basis in the description so that the meaning of the terms in the claims may be ascertainable by reference to the description, see 37 CFR 1.75(d)(1). If the examiner determines that the claims presented late in prosecution do not comply with 37 CFR 1.75(d)(1), applicant will be required to make appropriate amendment to the description to provide clear support or antecedent basis for the terms appearing in the claims provided no new matter is introduced.”
3 Quoting claim 1, “performing an intervention if the reduction in the speed of the gait of the person over the period of time is greater than or equal to the speed reduction threshold, the intervention comprising modifying one or more directional indicators in a space where the person is located.”
4 See the 2019 35 U.S.C. 112 Compliance Federal Register Notice (Federal Register, Vol. 84, No. 4, Monday, January 7, 2019, pages 57 to 63). See also http://ptoweb.uspto.gov/patents/exTrain/documents/2019-112-guidance-initiative.pptx . Quoting the FR Notice at pages 61 and 62, "The Federal Circuit emphasized that ‘‘[t]he written description requirement is not met if the specification merely describes a ‘desired result.’ ’’ Vasudevan, 782 F.3d at 682 (quoting Ariad, 598 F.3d at 1349). . . . When examining computer-implemented, software-related claims, examiners should determine whether the specification discloses the computer and the algorithm(s) that achieve the claimed function in sufficient detail that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as 'a finite sequence of steps for solving a logical or mathematical problem or performing a task.' Microsoft Computer Dictionary (5th ed., 2002). Applicant may 'express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure.' Finisar, 523 F.3d at 1340 (internal citation omitted). It is not enough that one skilled in the art could theoretically write a program to achieve the claimed function, rather the specification itself must explain how the claimed function is achieved to demonstrate that the applicant had possession of it. See, e.g., Vasudevan, 782 F.3d at 682–83. If the specification does not provide a disclosure of the computer and algorithm(s) in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention that achieves the claimed result, a rejection under 35 U.S.C. 112(a) for lack of written description must be made. See MPEP § 2161.01, subsection I."
5 See MPEP 2161.01, I. and LizardTech Inc. v. Earth Resource Mapping Inc., 424 F.3d 1336, 1345 (Fed. Cir. 2005) cited therein ("Whether the flaw in the specification is regarded as a failure to demonstrate that the applicant possessed the full scope of the invention recited in [the claim] or a failure to enable the full breadth of that claim, the specification provides inadequate support for the claim under [§ 112(a)]").
6 For examples only, published paragraphs [0035] and [0077] of the specification indicate this:
[0035] Embodiments as disclosed herein relate to prevention of fall events using interventions based on data analytics. People typically experience fall events as they move from a first location to a second location by performing a physical activity, such as walking, jumping, jogging, and/or running. Research shows that the propensity for a fall event to occur increases as people age. This is due to aging being generally associated with decrease in muscle strength and muscle mass that may result in reduced functional capacity physical frailty, impaired mobility, and/or accidental falls. There are numerous risks that may increase the propensity for the fall event to occur. For example, the risks may include characteristics of a gait and/or balance of the person, physical measurements of the person, medical history, fracture history, fall history, urinary incontinence, neurological conditions, medication, and the like. As the number of risks that a person is exposed to increases, the propensity for the fall event may increase.
[0077] In the non-limiting example shown in FIG. 2, the moulding section 102 includes a memory 204. According to certain embodiments, memory 204 is a non-transitory memory containing program code to implement, for example, generation and transmission of control instructions, networking functionality, the algorithms for generating and analyzing locations, presence, and/or tracks, and the algorithms for determining gait deterioration and/or propensity for a fall event as described herein.
7 See e.g., Bilski v. Kappos, 561 U.S. 593 ("Flook established that limiting an abstract idea to one field of use . . . did not make the concept patentable.")
8 Now U.S. Patent 10,335,091 B2.
9 Examiner’s note: the USPTO and EPO document number designation for this document is
KR 20180052513 A.
10 For example only, see U.S. Patent Application Publication 2012/0089348, assigned to Tactonic Technologies LLC, and numerous other related patents/publications, where (e.g., in FIG. 35) a microcontroller 5 on a circuit board 4 of the tile performs both sensor scanning and host computer communication.
11 For example only, see U.S. Patent Application Publication 2012/0089348, assigned to Tactonic Technologies LLC, and numerous other related patents/publications, where (e.g., in FIG. 35) a microcontroller 5 on a circuit board 4 of the tile performs both sensor scanning and host computer communication.
12 Now U.S. Patent 10,335,091 B2.
13 Examiner’s note: the USPTO and EPO number designation for this document is KR 20180052513 A.
Prosecution Insights