DETAILED ACTION
Applicant’s response, filed 22 Sept. 2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Status of Claims
Claims 1-20 are pending.
Claims 1-20 are rejected.
Priority
Applicant’s claim for the benefit of a prior-filed application, U.S. Provisional App. No. 63/433,721 filed 19 Dec. 2022, under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged.
Accordingly, the effective filing date of the claimed invention is 19 Dec. 2022.
Drawings
The objection to the drawings filed 24 March 2023 has been withdrawn in view of the replacement drawing sheets filed 22 Sept. 2026.
The drawings filed 22 Sept. 2026 are accepted.
Claim Objection- Warning
Applicant is advised that should claims 15-17 be found allowable, claims 18-20 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
Independent claim 15 recites “One or more non-transitory computer readable storage media embodying instructions and coupled to one or more processors that are operable to execute the instructions to:…”, and independent claim 18 recite “A system comprising: one or more non-transitory computer readable media embodying instructions; and one or more processors coupled to the non-transitory computer readable storage media, the one or more processors being operable to execute the instructions to…”. Therefore, both claims 15 and 18 are a system with one or more non-transitory computer readable storage media embodying instructions and coupled to one or more processors that carry out the instructions to perform the same steps. Claims 16-17 are identical to claims 19-20 respectively.
Response to Arguments
Applicant's arguments filed 22 Sept. 2026 regarding the claim objection warning have been fully considered but they are not persuasive.
Applicant remarks that claim 15 only comprises a non-transitory computer readable medium, but does not comprise the coupled one or more processors (Applicant’s remarks at pg. 8, para. 3-4).
This argument is not persuasive. Claim 15 recites “One or more non-transitory computer readable storage media…coupled to one or more processors that are operable to execute the instructions to:…”, and therefore requires one or more non-transitory computer readable storage media coupled to one or more processors. Given the term “coupled” means physically connected to, a claim to a non-transitory computer readable medium coupled to a processor requires both the non-transitory computer readable medium and the processor. If Applicant intends for claim 15 to only require the computer readable medium, the claim can be amended to recite “One or more non-transitory computer readable storage media embodying instructions, that when executed by one or more processors coupled to the one or more non-transitory computer readable storage medium, cause the one or more processors to: access…”
Claim Interpretation
Claims 2, 16, and 19 recite “wherein the first portion of a user's body comprises a limb and the second portion of the user's body comprises a trunk or a head”. Claims 1, 15, and 18 recite “accessing/access first sensor data from a first sensor worn on a first portion of a user’s body; accessing/access second sensor data from a second sensor worn on a second portion of the user’s body”. Therefore, claims 1, 15, and 18 involve accessing/receiving already generated first and second sensor data. As a result, the wherein clause of claims 2, 16, and 19 are interpreted to define the process in which the first and second sensor data was previously generated (i.e. from a sensor on a limb and from a sensor on a trunk or head). See MPEP 2113.
Claims 3-5, 8, 13, 17, and 20 also further limit what the first and second sensor are (e.g. calibrated sensors in claim 13). Therefore, these limitations are similarity interpreted to be part of the product by process limitation identified above.
Claim Rejections - 35 USC § 112(b)
The rejection of claim 12 under 35 U.S.C. 112(b) in the Office action mailed 22 June 2026 has been withdrawn in view of claim amendments received 22 Sept. 2026.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Any newly recited portion is necessitated by claim amendment.
The Supreme Court has established a two-step framework for this analysis, wherein a claim does not satisfy § 101 if (1) it is “directed to” a patent-ineligible concept, i.e., a law of nature, natural phenomenon, or abstract idea, and (2), if so, the particular elements of the claim, considered “both individually and as an ordered combination,” do not add enough to “transform the nature of the claim into a patent-eligible application.” Elec. Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353 (Fed. Cir. 2016) (quoting Alice, 134 S. Ct. at 2355). Applicant is also directed to MPEP 2106.
Step 1: The instantly claimed invention (claims 1, 15, and 18 being representative) is directed a method and system. Therefore, the instantly claimed invention falls into one of the four statutory categories. [Step 1: YES]
Step 2A: First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in in Prong Two if the recited judicial exception is integrated into a practical application of that exception.
Step 2A, Prong 1: Under the MPEP § 2106.04, the Step 2A (Prong 1) analysis requires determining whether a claim recites an abstract idea, law of nature, or natural phenomenon.
Claims 1, 15, and 18 recite the following steps which fall under the mental processes groupings of abstract ideas:
fusing the first sensor data and the second sensor data to obtain fused combination-sensor data;
determining/determine, based on the fused combination-sensor data, one or more first features related to the user's activity;
determining/determine, based on the one or more first features, an initial classification of the user's activity;
determining/determine whether the initial classification indicates a class that includes one or more subclasses that are more distinguishable by one of the sensors relative to the other sensor; and
when the initial classification indicates a class that includes one or more subclasses that are more distinguishable by one of the sensors relative to the other sensor, then: determining/determine one or more second features based solely on sensor data from the one sensor; and determining/determine, based on the second features, a specific subclassification of the user's activity; or
when the initial classification does not indicate a class that includes one or more subclasses that are more distinguishable by one of the sensors relative to the other sensor, then determining/determine a final classification of the user's activity based on the one or more first features.
The identified claim limitations falls into the group of abstract ideas of mental processes, for the following reasons. In this case, fusing first and second sensor data encompasses merely organizing information, including appending the first sensor data to the second sensor data to create a merged/fused dataset, which can be practically performed in the mind aided with pen and paper. Determining one or more first features from already collected first and second sensor data amounts to a mere analysis of information, such as analyzing heart rate data (e.g. from a wrist sensor) and temperature data (from a body sensor) to determine a level of exertion. Determining an initial classification based on the first features encompasses determining a user is running or standing of the level of exertion is high (e.g. which is more distinguishable by a heart rate sensor). Determining one or more second features from the one sensor encompasses analyzing the heart rate sensor data to determine the user was sprinting (i.e. a subclassification). Determining a final classification of the user’s activity based on the one or more first features if the initial classification does not indicate a class that includes one or more subclasses, encompasses determining the user is standing. That is, other than reciting the limitations are carried out by a processor in claims 15 and 18, nothing in the claims precludes the steps from being practically performed in the mind. See MPEP 2106.04(a)(2) III.
Dependent claims 6-7, 9-12, and 14 further recite an abstract idea and/or are part of the abstract idea of claim 1 above. Dependent claims 6-7 further limits the mental process of determining the initial classification to be a user motion, user non-motion, or user posture indicating a class that includes standing, sitting, and lying down subclasses. Dependent claims 9-10 further recite the mental process of changing a classification of a portion of the classified user-activity data based on one or more characteristics of the stream of classified user-activity data by changing a classification of a portion of the stream when that portion is less than a size threshold. Dependent claim 11 further recites the mental process of determining that a segment of the first or second sensor data is unreliable based on a comparison of the segment with a threshold or with a data signature (i.e. data comparisons), and excluding that segment from sensor data that is accessed (i.e. filtering information). Dependent claim 12 further recites the mental process of determining, based on features and on a set of class weights, the initial classification of the user’s activity. Dependent claim 14 further recites the mental process of adding to a user activity log an identification of the subclassification or final classification and a length of time, which encompasses mentally identifying the subclassification or final classification, a duration associated with the classification, and writing via pen and paper the information in a log. Therefore, claims 1-20 recite an abstract idea. [Step 2A, Prong 1: YES]
Step 2A: Prong 2: Under the MPEP § 2106.04, the Step 2A, Prong 2 analysis requires identifying whether there are any additional elements recited in the claim beyond the judicial exception(s), and evaluating those additional elements to determine whether they integrate the exception into a practical application of the exception. This judicial exception is not integrated into a practical application for the following reasons.
Dependent claims 6-7, 10-11, and 14 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception.
The additional elements of independent claims 1, 15, and 18 include:
one or more non-transitory computer readable storage media (claims 15 and 18 only);
one or more processors (claims 15 and 18 only);
accessing/access first sensor data from a first sensor worn on a first portion of a user's body (i.e. receiving data); and
accessing/access second sensor data from a second sensor worn on a second portion of the user's body (i.e. receiving data);
The additional elements of dependent claims 2-5, 8-9, 12-13, 16-17, and 19-20 include:
wherein the first portion of a user's body comprises a limb and the second portion of the user's body comprises a trunk or a head (claims 2, 16, and 19);
wherein the first portion of the user's body comprise an arm and the second portion of the user's body comprises the head (claims 3, 17, and 20);
wherein the first sensor is part of a wrist-worn device (claim 4);
wherein the wrist-worn device comprises a watch and the second sensor comprises a pair of earbuds (claim 5);
wherein: the first sensor is more able to distinguish between the standing and sitting subclasses than is the second sensor; and the second sensor is more able to distinguish between the sitting and lying down subclasses than is the first sensor (claim 8);
accessing a stream of classified user-activity data (i.e. receiving data) (claim 9);
accessing information identifying a context associated with the user during a time associated with the first sensor data and the second sensor data (claim 12); and
wherein either or both of the first sensor and the second sensor are initially calibrated to the user (claim 13).
The additional elements of a non-transitory computer readable media (i.e. memory), one or processors, and accessing/receiving data are generic computer components and/or functions. The courts have found the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
The additional elements of claims 2-5, 8, 13, 16-17, and 19-20 include limitations that further limit the first and/or second sensor. These limitations only serve to further define the first sensor data and second sensor data being received/accessed in independent claims 1, 15, and 18, and thus are part of the additional element of accessing data. Therefore these additional elements do not provide integration for the same reasons discussed above regarding the “accessing” in the independent claims.
Further regarding the limitations pertaining to accessing first and second sensor information, these limitations only serve to collect data necessary for the abstract idea, which amounts to insignificant extra-solution activity which does not integrate the recited judicial exception into a practical application. See MPEP 2106.05(g).
Therefore, the additionally recited elements amount to insignificant extra-solution activity and/or merely invoke computers as a tool, and as such, the claims as a whole do not integrate the abstract idea into practical application. Thus, claims 1-20 are directed to an abstract idea. [Step 2A, Prong 2: NO]
Step 2B: In the second step it is determined whether the claimed subject matter includes additional elements that amount to significantly more than the judicial exception. See MPEP § 2106.05.
The claims do not include any additional steps appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception for the following reasons.
Dependent claims 6-7, 10-11, and 14 do not recite any elements in addition to the judicial exception, and thus are part of the judicial exception. The additional elements of claims 1-5, 8-9, 12-13, and 15-20 are outlined above under step 2A, Prong 2.
The additional elements of a non-transitory computer readable media (i.e. memory), one or processors, and accessing/receiving data are conventional computer components and/or functions. The additional elements of claims 2-5, 8, 13, 16-17, and 19-20 include limitations that further limit the first and/or second sensor, which only serve to further define the first sensor data and second sensor data being received/accessed in independent claims 1, 15, and 18. The courts have found the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit).
Therefore, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself. [Step 2B: NO]
Therefore, the instantly rejected claims are not drawn to eligible subject matter as they are directed to an abstract idea (and/or natural correlation) without significantly more. For additional guidance, applicant is directed generally to applicant is directed generally to the MPEP § 2106.
Response to Arguments
Applicant's arguments filed 22 Sept. 2026 regarding 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant remarks the specification does provide an improvement because paragraph 12 of the specification explains sensors incorporated into body worn devices are unable to accurately distinguish between various body positions or movements of the wearer, and paragraph 13 explains fusing data from multiple sensors can sometimes improve accuracy, but also leads to loss of information or improper sensing weighting, and the techniques of the invention address these problems and improve detection and classification accuracy by correcting short-term inaccuracies that occur due to similarities (Applicant’s remarks at pg. 10, para. 7 to pg. 11, para. 3). Applicant further remarks the claims do recite features that give rise to the described improvement, including making an initial classification based on fused sensor data, and subsequently determining whether the initial classification indicates a class that includes one or more subclasses, thereby utilizing individual sensors’ abilities to differentiate between poses and movements and describing a technical improvement in wearable device’s capabilities to detect wearer body positions and movements (Applicant’s remarks at pg. 11, para. 4-5).
This argument is not persuasive. It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. Furthermore, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. See MPEP 2106.05(a).
In the instant case, the alleged improvement in detection and classification accuracy, provided by the limitations of making an initial classification and determining whether the initial classification indicates a class that includes one or more subclasses are part of the abstract idea, and therefore, cannot provide the improvement alone. Overall, Applicant’s arguments relate to an improvement in analyzing sensor data to make classifications of user activity, which is an improvement to the abstract idea and not a technology. While Applicant states that the technical improvement is in the wearable device’s capability to detect wearer body positions and movements, Applicant has not provided a technical explanation regarding how the physical sensors and measurements of the physical sensors are improved such that the claims would reflect an improvement in a sensors capabilities. Instead, the improvement is provided solely by the process in which sensor data is being analyzed, which is part of the abstract idea as discussed above.
Applicant remarks that Applicant disagrees with the analysis set forth regarding which features are abstract, but these disputes do not need to be resolved because under prong 2, the limitations containing judicial exceptions and additional elements need to be evaluated together, and because the claims as a whole recite a technical improvement, the claims are eligible (Applicant’s remarks at pg. 12, para. 1).
This argument is not persuasive. It is agreed that under Step 2A, Prong 2, the claims are evaluated as a whole. However, under step 2A, Prong 2, it is the additional elements that are evaluated to determine whether they integrate the judicial exception into a practical application. The judicial exception cannot integrate itself into a practical application, as discussed above. Therefore, which claim elements are additional elements versus part of the judicial exception is highly relevant to the analysis under Step 2A, Prong 2.
Claim Rejections - 35 USC § 102
The rejection of claims 1-10 and 13-20 under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Kamali (2015) in the Office action mailed 22 June 2026 has been withdrawn in view of claim amendments received 22 Sept. 2026.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims are 1-10 and 13-20 rejected under 35 U.S.C. 103 as being unpatentable over Kamali (2016). This rejection is newly recited and necessitated by claim amendment.
Cited reference: Kamali et al., US 2016/0051168 A1, effectively filed 18 Aug. 2015 (previously cited).
Regarding claims 1, 15, and 18, Kamali discloses a method for determining an activity of a user (Abstract; [0011]) and a system for carrying out the method comprising a non-transitory computer-readable medium storing software instructions and a processor configured to execute the software instructions ([044]; [0047]; FIG. 1), wherein the method comprises the following steps.
Kamali discloses accessing data from a plurality tracking devices each having a plurality of sensors, including a first tracking device of a watch (i.e. a first sensor on a first portion of a user’s body) and a second tracking device of a hat (i.e. a second sensor worn on a second portion of the user’s body) ([0047]-[0048], e.g. sensor information accessed and translated; FIG. 1, sensors #114 and 116; FIG. 3, e.g. collect sensor input data from various sensors; [0074] and FIG. 13, e.g. various sensor collecting data))
Kamali comparing the sensor inputs to activity signatures, thus determining features of the sensor inputs that match activity signatures (i.e. one or more first features related to the user’s activity) ([0057]).
Kamali discloses determining, based on the comparisons of the sensor inputs to known activity signatures, a classification of an activity of the user ([0017]; [0057], e.g. activities include walking, running, resting, sitting, driving, flying, playing specific sports, etc. [0074], e.g. determination of running).
Kamali discloses the set of potential activities of the user could change from context to context, such as selecting from reading, watching TV, playing a game, or getting a massage if the user was classified as at rest or selecting from restless sleep, restful sleep, deep sleep, silent sleep, and snoring sleep if the subject is classified as asleep (i.e. determining whether the initial classification indicates a class with one or more subclasses) ([0053], e.g. context selected based on past activity; [0057], e.g. determining resting and sleeping activity has subclasses). Furthermore, Kamali discloses the first sensor is a watch and the second sensor is a hat, such that the first sensor is able to better distinguish between sitting and standing and the second sensor is better at distinguishing between sitting and lying down, as evidenced by Applicant’s specification at para. [0012] (and discussed in more detail below with respect to claim 8), demonstrating subclasses are more distinguishable by one sensor relative to another (e.g. a massage is better distinguishable by the second hat sensor, while activities in which a head orientation is the same is better distinguished by the watch, such as watching tv, reading, etc.).
In the embodiment in which the initial classification does not indicate a class that includes one or more subclasses that are more distinguishable by one of the sensors relative to the other sensor (e.g. determining a class of running), Kamali discloses determining a final classification, including an average speed of running, of the user’s activity based on the activity signature ([0058]; [0074]).
Further regarding claim 1, Kamali does not disclose the following limitations:
Kamali does not explicitly disclose fusing the first sensor data and the second sensor data to obtain fused combination-sensor data, such that the determining one or more first features is based on the fused combination-sensor data.
However, Kamali does disclose the sensor data collected from the first and second sensor is accumulated for the latest time period and the features are determined based on the accumulated data including both the first and second sensor data, and then selects a body area context as a function of the accumulated sensor data ([0061]; Figure 3), which suggests the first and second sensor data are combined into a single “accumulated” dataset. Furthermore, given Kamali discloses a combination of the first and second sensor data use for determining features of the sensor inputs and ultimately determining an activity classification of the user ([0017];[0057]), this would necessarily require either having the first and second sensor data stored in separate datasets or having the first and second sensor data combined in a single dataset.
Therefore, 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 the method of Kamali to have used a single combined dataset of the first and second sensor data because it would have been obvious to try using a combined dataset from the finite set of either storing the first and second sensor data in separate datasets or storing the first and second sensor data in the same dataset. One of ordinary skill in the art could have pursued either solution to storing the first and second sensor data with a reasonable expectation of success given Kamali discloses the first and second sensor data forms an accumulated sensor input dataset, from which a user activity is detected as a function of the accumulated sensor input dataset ([0061]); one of ordinary skill in the art would recognize that inputs from the accumulated dataset could be applied to a function to predict a user activity, regardless of whether the first and second sensor data is stored in separate datasets or in the same combined dataset,
Furthermore, the courts have the use of a one piece construction rather than several parts as merely a matter of obvious engineering choice. See In re Larson, 340 F.2d 965, 968, 144 USPQ 347, 349 (CCPA 1965) (A claim to a fluid transporting vehicle was rejected as obvious over a prior art reference which differed from the prior art in claiming a brake drum integral with a clamping means, whereas the brake disc and clamp of the prior art comprise several parts rigidly secured together as a single unit. The court affirmed the rejection holding, among other reasons, "that the use of a one piece construction instead of the structure disclosed in [the prior art] would be merely a matter of obvious engineering choice."). See MPEP 2144.04 V. B. In the instant case, the limitation of “fusing” the first and second sensor data is merely making the first and second sensor data integral. However, analyzing first and second sensor data stored in a combined data set does not appear to provide any advantage or solve a stated problem when compared to analyzing all of the first and second sensor data from separate datasets, and thus the limitation does not demonstrate any insight that was contrary to the understandings and expectations of the art.
Regarding the dependent claims:
Regarding claims 2-3, 16-17, and 19-20, Kamali discloses the first sensor is a watch on the wrist of the user (i.e. the first portion of the user’s body is an arm) and the second sensor is a hat on the user’s head (i.e. the second portion of the user’s body comprises the head) (FIG. 1; [0011]-[0012], e.g. tracking device on wrist; [0047], e.g. watch and hat tracking devices; [0056], e.g. tracking device on head)
Regarding claim 4, Kamali discloses the first sensor is a watch on the wrist of the user (FIG. 1; [0047]).
Regarding claim 5, Kamali discloses the first sensor is a watch on the wrist of the user (FIG. 1; [0047]). Regardless, the limitations further limiting what the first sensor and second sensor are only serve to define the process in which the first sensor data and second sensor data was previously generated. If the product in the product-by-process claim is the same as or obvious from a product of the prior art, the claim is unpatentable even though the prior product was made by a different process." In re Thorpe, 777 F.2d 695, 698, 227 USPQ 964, 966 (Fed. Cir. 1985) (citations omitted). See MPEP 2113 I. In the instant case, the second sensor data from a hat on a head of the user, as discussed above, is considered the same product as sensor data determined from a pair of earbuds on a head of the user, and therefore Kamali reads on the claim. The claims do not require any particular type of second sensor that would serve to differentiate the second sensor data of Kamali with the second sensor data of the claims.
Regarding claim 6, Kamali discloses the initial classification is of running (i.e. motion) ([0017]).
Regarding claim 7, the embodiment in which the initial classification is user posture is not required by the claim and is instead presented as an alternative embodiment in claim 6. As discussed above for claim 6, Kamali discloses the initial classification is of running (i.e. motion) ([0017]), which reads on claim 7.
Regrading claim 8, Kamali discloses the first sensor is a watch on the wrist of a user and the second sensor is a hat on the head of the user, and the sensors include a gyroscope and accelerometer (i.e. an orientation sensor) (Figure 1; [0047]). The ability of the first sensor (e.g. the watch) to be able to better distinguish between the standing and sitting subclasses relative to the second sensor and of the second sensor to be able to better distinguish between the sitting and lying down position is inherent based on the first and second sensors having an orientation sensor, the positioning of the watch on a wrist of the user’s body, and the position of the hat sensor on the head of user. This is evidenced by Applicant’s own specification at para. [0012], which discloses a watch (e.g. the watch sensor in Kamali) is in a same spatial orientation when the user is sitting or lying down and thus an orientation sensor in the watch is unable to accurately determine the user’s orientation, and that an orientation sensor in a head-worn device (e.g. the hat sensor in Kamali) may not be able to distinguish between sitting and standing as the user’s head may be in the same orientation when sitting or standing. There is no requirement that a person of ordinary skill in the art would have recognized the inherent disclosure at the relevant time, but only that the subject matter is in fact inherent in the prior art reference. Schering Corp. v. Geneva Pharm. Inc., 339 F.3d 1373, 1377, 67 USPQ2d 1664, 1668 (Fed. Cir. 2003). See MPEP 2112 II.
Regarding claim 9, Kamali discloses accessing activity data and raw sensor information over time, indicating a user is first walking at 5 miles per hour at a first time (i.e. a stream of classified-user activity data) ([0017]).
Kamali discloses changing a classification of the classified user-activity data to be jogging at 5 miles per hour at a second time (i.e. a characteristic of the stream of classified user activity data) ([0017]).
Regarding claim 10, the step of changing a classification of the portion of the stream of classified user-activity data is not required under the broadest reasonable interpretation of the claim, because the condition precedent of that portion being less than a threshold size is not required by the claim See MPEP 2111.04. Therefore, claim 10 is rejected for the same reasons discussed above for claim 9.
Regarding claim 13, the process in which the first and second sensors were previously calibrated is a product by process limitation, but a step of calibrating the sensors is not required by the claim See MPEP 2113 I. Because the first and second sensor data of Kamali is the same product as disclosed in the claims, as applied to claim 1 above, Kamali discloses this limitation.
Regarding claim 14, Kamali discloses generating a log of activity detail records, which is a log of activities over time that the activity tracker device has detected through sensors ([0048]). Kamali discloses the activity log includes a second time period labelled with “running” or running with an average speed (i.e. the final classification and a length of time associated with the final classification) ([0058]).
Therefore, the invention is prima facie obvious.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Kamali (2015), as applied to claim 1 above, further in view of Seo (2018). This rejection is previously cited.
Cited references: Seo et al., US 2018/0132031 A1 (previously cited)
Regarding claim 11, Kamali makes obvious the invention of claim 1 as applied above.
Further regarding claim 11, Kamali, as applied to claim 1 above, does not disclose the following limitations:
Kamali does not disclose determining that a segment of the first sensor data or a segment of the second sensor data is unreliable, based on a comparison of the segment with a threshold or with a data signature indicating how a device that includes the sensor generating the segment is worn on the user's body; and in response to the determination that the segment of sensor data is unreliable, then excluding that segment from sensor data that is accessed.
However, Seo discloses a method for determining an activity state of a user based on sensor data (Abstract; [0046]), which includes determining whether a sensor is normally worn or not based on obtained sensor data ([0092]; FIG. 5). Seo discloses comparing the obtained sensor data to a reference range indicating a range and a pattern (i.e. a signature) corresponding to the user’s activity stored in memory, and determining an abnormal wearing state (i.e. unreliable data) when the obtained sensor data is out of range ([0092]; FIG. 5). Seo discloses determining an activity state of the user using sensor data obtained in a wearing state (i.e. not the abnormal wearing state) ([0046]), demonstrating the sensor data of the abnormal wearing state is excluded from sensor data that is accessed. Seo further discloses body-fittable sensors may acquire inaccurate sensor data due to abnormal wearing of the electronic device ([0005]).
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 the method of Kamali to have determined a segment of the sensor data is unreliable as claimed, and then excluded the unreliable sensor data from data that is accessed according to the method of Seo, discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Kamali in view of Seo in order to avoid using inaccurate sensor data in classifying user activity, as shown by Seo ([0005]), thus resulting in more accurate activity classifications in Kamali. This modification would have had a reasonable expectation of success because Kamali uses sensor information from body-fittable sensors to classify user activity, and thus the method of detecting abnormal sensor wear of Seo is applicable to the method of Kamali.
Therefore, the invention is prima facie obvious.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Kamali (2015), as applied to claim 1 above, further in view of Banos (2013). This rejection is previously cited
Cited references: Banos et al., Human activity recognition based on a sensor weighting hierarchical classifier, 2013, Soft Comput, 17, pg. 333-343 (Previously cited)
Regarding claim 12, Kamali makes obvious the method of claim 1 as applied above.
Further regarding claim 12, Kamali discloses identifying a body area context for how the user is using the sensors over time ([0052]-[0053]). Kamali discloses the user activity is determined as a function of the sensor inputs as they related to the identified context ([0057]), in addition to features of the sensor data that match activity signatures (i.e. the one or more first features related to the user’s activity) ([0057]).
Further regarding claim 12, Kamali does not disclose the following limitation:
Kamali does not disclose determining the initial classification is based on a set of class weights associated with the identified user context.
However, Banos discloses a hierarchical classifier (HWC) based on sensor weighting for human activity recognition (Abstract), wherein the hierarchical classifier combines sensor data from multiple sensors/data sources to make a human activity prediction such as running, cycling, sitting, or lying down (Fig. 1 and pg. 335, col. 1, e.g. M sources, para. 2; Fig. 2 and pg. 337, col. 2, para. 3; pg. 338, col. 2, para. 3, e.g. classified activities). Banos discloses that even with an activity recognition chain (ARC) in the classifier is optimized, some sensors may be more specialized in the recognition of some activities based on the location of the sensors on the body, and therefore decisions for each individual ARC are fused together in the classifier to output the final decision (Abstract; pg. 336, col. 1, para. 3; Figure 1, e.g. see ARCs). Banos discloses that to solve this problem, each data source/sensor M has a set of N class classifiers in the hierarchical classifier, and that each class classifier is assigned a weight β (i.e. class weights associated with an identified context/source) representing the importance that the respective class classifier will have on the decision scheme for the respective data source used to make the final activity prediction (pg. 337, col. 2, para. 2-5; Figure 2, e.g. see each Data source 1-M has class level classifiers 1-N, with class weights β). Banos discloses multiple hierarchical weighted classifier for different numbers of sensors, demonstrating sensors at different body locations are better at predicting particular activity classes (pg. 341, col. 1, para. 2 to col. 2, para. 1; Abstract). Banos discloses the above methodology accounts for context-related factors (e.g. subject carrying items, unstable floor) of the subject (pg. 335, col. 1, para. 1 to col. 2, para. 2) and systematically outperforms results obtained by traditional multi-class models (Abstract).
It would have been prima facie face obvious, to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the method of Kamali to have determined the initial classification based on a set of class weights associated with the user context according to the method of Banos discussed above. One of ordinary skill in the art would have been motivated to combine the methods of Kamali and Banos in order to account for parts of the body that are specifically informative for the recognition of each particular activity and account for context-related factors of the subject, thus resulting in better activity classification as shown by Banos (Abstract; pg. 335, col. 1, para. 1-2; pg. 341, col. 2, para. 2). This modification would have had a reasonable expectation of success given both Kamali and Banos make activity predictions using data from multiple sensors, and furthermore, Banos explains using the classifier with different combinations of sensors only requires including or removing the associated knowledge-inference entities without requiring re-training (pg. 341, col. 2, para. 2). Therefore, the classifier of Banos is applicable to the method of Kamali.
Therefore, the invention is prima facie obvious.
Response to Arguments
Applicant's arguments filed 22 Sept. 2026 regarding 35 U.S.C. 102, as applicable to the 103 rejection set forth above, have been fully considered but they are not persuasive.
Applicant remarks that Kamali does not disclose “fusing the first sensor data and the second sensor data…” or “determining, based on the fused combination-sensor data, one or more first features…” (Applicant’s remarks at pg. 9, para. 4 to pg. 10, para. 2).
This argument is not persuasive. The plain meaning of term “fused” merely requires joining or connecting something to something else. Therefore, the limitation of “fusing the first sensor data and the second sensor data to obtain fused combination-sensor data” merely requires that the first sensor data and the second sensor data are combined in a single dataset, rather than being stored in separate datasets.
While Kamali does not explicitly mention the first and second sensor data are stored in a single dataset (i.e. the fused combination-sensor data), Kamali does disclose the sensor data collected from both the first and second sensor is accumulated for the latest time period and the features are determined based on the accumulated data including both the first and second sensor data, and then further discloses selecting a body area context as a function of the accumulated sensor data ([0061]; Figure 3), which suggests the first and second sensor data are combined into a single “accumulated” dataset for which a function is then applied. Furthermore, given Kamali discloses a combination of the first and second sensor data use for determining features of the sensor inputs and ultimately determining an activity classification of the user ([0017];[0057]), this would necessarily require either having the first and second sensor data stored in separate datasets or having the first and second sensor data combined in a single dataset.
Therefore, the reasons discussed in the above rejection, simply storing the first and second sensor data of Kamai together in a “fused combination-sensor data” would have been obvious to try. Furthermore, as explained above, the courts have the use of a one piece construction rather than several parts as merely a matter of obvious engineering choice. See In re Larson, 340 F.2d 965, 968, 144 USPQ 347, 349 (CCPA 1965). See MPEP 2144.04 V. B. Here, the limitation of “fusing” the first and second sensor data is merely making the first and second sensor data integral.
Applicant remarks that Kamali does not disclose “determining whether the initial classification indicates a class that includes one or more subclasses that are more distinguishable…”, and instead Kamali discloses matching sensor data to activity signatures to classify the user’s activity (Applicant’s remarks at pg. 10, para. 2).
This argument is not persuasive. Kamali discloses, after making an initial classification of a user activity, the set of potential activities of a user could change from context to context by selecting a new body area context as a function of a past activity (i.e. determining whether the initial classification has subclasses) ([0053]; [0057]). For example, Kamali discloses if a user is classified as at rest, the set of potential activities changes to comprise reading, watching TV, playing a game, or getting a massage (i.e. subclasses of resting) and similarly provides example subclasses for the activity of sleeping based on updating the body context ([0057]). Accordingly, Kamali discloses determining whether the initial classification includes subclasses by updating a body context based on whether an initial class is associated with a body context having various subclasses. Kamali further discloses one or more subclasses are more distinguishable by one sensor over the other, as explained in the above rejection.
Applicant remarks claims 15 and 18 recite similar features and are thus allowable for the same reasons as claim 1 (Applicant’s remarks at pg. 10, para. 3).
This argument is not persuasive for the same reasons discussed above for claim 1.
Conclusion
No claims are allowed.
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.
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/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685
