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 1-29 currently pending.
Response to Arguments
Applicant’s amendments and remarks filed December 5, 2025 have been fully considered.
Response to arguments with respect to Double Patenting:
In response to Applicant’s argument with respect to the provisional double patenting rejections that amendments patentably distinguish the instant claims from reference application 17332352, Examiner respectfully disagrees. The rejected claims are obvious over copending Application No. 17332352 (reference application) in view of WO 2017156492 A1 to Chen. See Double Patenting section for detailed analysis.
Response to arguments with respect to rejections under 35 U.S.C. § 112(b):
Rejections under 35 U.S.C. § 112(b) have been overcome due to amendments and remarks filed December 5, 2025.
Response to arguments with respect to rejections under 35 U.S.C. § 103:
Applicant’s arguments with respect to the rejections under 35 U.S.C. § 103 have been considered but are not persuasive as discussed below.
Argument 1 (Remarks pg. 9-11): Applicant submits that Golander does not teach amended claim 1.
Response 1: Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Argument 2 (Remarks pg. 11-12): Applicant submits that Chen (‘492) does not teach “grouping the set of biometric features into subsets of biometric features that are respectively associated with one occupant of the at least two distinct occupants” as required by amended claim 1 because Applicant “understands the ‘estimating’ of Chen as an estimate of an aggregate count of individuals corresponding to the aggregate count of breathing rates, without specifically assigning each rate to a particular individual.” Applicant further submits that claims 17 and 22 are allowable for similar reasons and dependent claims are allowable by nature of dependency upon allowable claims.
Response 2: Examiner respectfully disagrees. Chen (‘492) teaches: Figs. 4, 7; [0093] – “Breathing rates are estimated at 432 according to the statistics of the merged clusters. I[t] can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” Therefore, in addition to estimating an aggregate count of individuals, Chen (‘492) teaches estimation of the breathing rate of individual people. See rejection under 35 U.S.C. § 102 for detailed citations and analysis.
Argument 3 (Remarks pg. 12): Applicant submits that Chen does not teach “determines, for each occupant of at least two distinct occupants in the space, an occupant-specific signature derived from the radio signals and based on the channel state information, wherein determining the occupant-specific signature for each occupant includes grouping the set of biometric features into subsets of biometric features that are respectively associated with one occupant of the at least two distinct occupants” as recited by claim 1 because “Chen is silent as to determining how to know that any particular biometric feature is associated with any particular individual, or how to know the path delay associated with such biometric feature.” Applicant further submits that claims 17 and 22 are allowable for similar reasons and dependent claims are allowable by nature of dependency upon allowable claims.
Response 3: Examiner respectfully disagrees. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “how to know the path delay associated with such biometric feature.”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. Further, Chen teaches geometric estimation and path delay determination based on CSI, e.g. paras 56-57, 118-125.
Chen teaches grouping the set of biometric features into subsets of biometric features that are respectively associated with one occupant of the at least two distinct occupants / determining occupant-specific signatures for each occupant by clustering / merging at: Figs. 4, 7; [0093] – “Breathing rate candidates are partitioned at 426 by clustering, and criteria are calculated for each cluster based on statistics. Clusters are merged at 428 when centroid distance between two clusters is less than a threshold. Statistics of the merged clusters are recalculated at 430. Breathing rates are estimated at 432 according to the statistics of the merged clusters. In can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” Set of biometric features corresponds to jumbo set of breathing rate candidates. Grouped subsets of biometric features correspond to clustered/merged jumbo set breathing rate candidate. Occupant-specific signature for each occupant may correspond to breathing rate estimation for each person. See rejection under 35 U.S.C. § 102 for detailed citations and analysis.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Instant claims 1, 17, and 22 provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over reference claim 1 of copending Application No. 17332352 (reference application) in view of WO 2017156492 A1 to Chen. See analysis regarding claim 1 below. Instant claims 17 and 22 are substantially similar to instant claim 1 and are obvious for similar reasons as those discussed below with respect to claim 1.
This is a provisional nonstatutory double patenting rejection.
Instant claims 2-14 provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over reference claims 2-3, 6-16 of copending Application No. 17332352 (reference application) in view of WO 2017156492 A1 to Chen. Instant claims 2-14 are substantially similar to reference claims 2-3, 6-16.
This is a provisional nonstatutory double patenting rejection.
The elements of instant claim 1 not taught by reference claim 1 are taught by Chen as follows:
Chen (‘492) teaches:
determines a set of biometric features (Figs. 2, 4; [0092] – “If breathing is detected at 422, then a jumbo set of breathing rate candidates may be formulated at 424 for a multi-antenna system by repeating the steps 420, then the process moves on to 426.” Examiner notes that their broadest interpretation of the term “biometric feature” in light of the specification includes a human’s motion, breathing, heartrate, the state of a human, the health of a human, changes to the state or health of a human, and other characteristics of a human. See instant application specification paras. 52-53. Set of biometric features corresponds to jumbo set of breathing rate candidates.) indicated in the channel state information, (Fig. 4; [0090] – “Eigenvalue Decomposition (EVD) is performed at 402 on a TRRS matrix that is obtained based on CSIs, where the CSIs may be extracted from received wireless signals that may be impacted by breathing of a person.” Examiner notes that step 420, used to determine set of biometric features as cited above, comprises step 402.)
determines, for each occupant of at least two distinct occupants in the space, an occupant-specific signature (Figs. 4, 7; [0053] – “the breathing rates can be estimated at 222” [0093] – “Breathing rates are estimated at 432 according to the statistics of the merged clusters. I[t] can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” Occupant-specific signature for each occupant may correspond to breathing rate estimation for each person.) derived from the radio signals and based on the channel state information, (Figs. 2, 4; [0092] – “If breathing is detected at 422, then a jumbo set of breathing rate candidates may be formulated at 424 for a multi-antenna system by repeating the steps 420, then the process moves on to 426.”) (Fig. 4; [0090] – “Eigenvalue Decomposition (EVD) is performed at 402 on a TRRS matrix that is obtained based on CSIs, where the CSIs may be extracted from received wireless signals that may be impacted by breathing of a person.” Examiner notes that step 420 used to determine set of biometric features comprises step 402.) wherein determining the occupant-specific signature for each occupant includes grouping the set of biometric features into subsets of biometric features that are respectively associated with one occupant of the at least two distinct occupants, (Figs. 4, 7; [0093] – “Breathing rate candidates are partitioned at 426 by clustering, and criteria are calculated for each cluster based on statistics. Clusters are merged at 428 when centroid distance between two clusters is less than a threshold. Statistics of the merged clusters are recalculated at 430. Breathing rates are estimated at 432 according to the statistics of the merged clusters. In can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” Clustered/merged jumbo set breathing rate candidates correspond to grouped subsets of biometric features.) and
outputs an occupancy signal based on the occupant-specific signatures derived from the channel state information and associated with each occupant of the at least two distinct occupants. ([0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” Examiner notes that the broadest reasonable interpretation of “occupancy signal” in light of the specification includes any signal that represents, contains data representing, or is otherwise indicative of the occupancy in the space 105, e.g., that a human is present, that more than one human is present, that a certain number of humans are present, that an animal is present, that a window has opened, that a door has opened, that at least one person is present but not moving, that a person has fallen, that a person has moved to a different space 105, or any other condition of the space 105 determined at 340. Examiner further cites ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system.” [claim 13] – “estimating a quantity of the one or more living beings based on the number of clusters after merging.”))
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Chen’s known technique to Reference Application No. 17332352 claim 1 ready for improvement to yield predictable results. Such a finding is proper because (1) to Reference Application No. 17332352 claim 1 teaches a base method of occupancy determination based on determined CSI; (2) Chen teaches a specific technique of particular occupancy determinations such as occupant discrimination, movement tracking, breathing tracking, and occupancy counting based on determined CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in a more efficient system capable of estimating additional biometric features of occupants; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-3, 15, 17, 20, 22, 24, 25 s/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by WO 2017156492 A1 to Chen.
Regarding claim 1,
Chen (‘492) teaches:
(Currently Amended) A method for determining occupancy in a space, the method comprising:
transmitting radio signals over a channel in the space; (Figs. 1-2; [0052] – “At 202, a transceiver/transmitter/Bot can transmit radio signals (e.g., a pulse or a pseudo random sequence) via a multipath channel”)
receiving the transmitted radio signals that have traveled through the space; ([0052] – “204, a receiver/another transceiver/Origin can receive the signals from the multipath channel”) and
implementing an occupancy-centric algorithm with at least one processor that determines channel state information based on the radio signals transmitted over the channel, (Fig. 2; [0052] – “receive the signals from the multipath channel that are impacted by the breathing of a person. The CSIs are extracted at 206 from the received radio signals using channel estimation… process the CSIs to obtain processed CSIs”) that,
determines a set of biometric features (Figs. 2, 4; [0092] – “If breathing is detected at 422, then a jumbo set of breathing rate candidates may be formulated at 424 for a multi-antenna system by repeating the steps 420, then the process moves on to 426.” Examiner notes that their broadest interpretation of the term “biometric feature” in light of the specification includes a human’s motion, breathing, heartrate, the state of a human, the health of a human, changes to the state or health of a human, and other characteristics of a human. See instant application specification paras. 52-53. Set of biometric features corresponds to jumbo set of breathing rate candidates.) indicated in the channel state information, (Fig. 4; [0090] – “Eigenvalue Decomposition (EVD) is performed at 402 on a TRRS matrix that is obtained based on CSIs, where the CSIs may be extracted from received wireless signals that may be impacted by breathing of a person.” Examiner notes that step 420, used to determine set of biometric features as cited above, comprises step 402.)
determines, for each occupant of at least two distinct occupants in the space, an occupant-specific signature (Figs. 4, 7; [0053] – “the breathing rates can be estimated at 222” [0093] – “Breathing rates are estimated at 432 according to the statistics of the merged clusters. I[t] can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” Occupant-specific signature for each occupant may correspond to breathing rate estimation for each person.) derived from the radio signals and based on the channel state information, (Figs. 2, 4; [0092] – “If breathing is detected at 422, then a jumbo set of breathing rate candidates may be formulated at 424 for a multi-antenna system by repeating the steps 420, then the process moves on to 426.”) (Fig. 4; [0090] – “Eigenvalue Decomposition (EVD) is performed at 402 on a TRRS matrix that is obtained based on CSIs, where the CSIs may be extracted from received wireless signals that may be impacted by breathing of a person.” Examiner notes that step 420 used to determine set of biometric features comprises step 402.) wherein determining the occupant-specific signature for each occupant includes grouping the set of biometric features into subsets of biometric features that are respectively associated with one occupant of the at least two distinct occupants, (Figs. 4, 7; [0093] – “Breathing rate candidates are partitioned at 426 by clustering, and criteria are calculated for each cluster based on statistics. Clusters are merged at 428 when centroid distance between two clusters is less than a threshold. Statistics of the merged clusters are recalculated at 430. Breathing rates are estimated at 432 according to the statistics of the merged clusters. In can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” Clustered/merged jumbo set breathing rate candidates correspond to grouped subsets of biometric features.) and
outputs an occupancy signal based on the occupant-specific signatures derived from the channel state information and associated with each occupant of the at least two distinct occupants. ([0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” Examiner notes that the broadest reasonable interpretation of “occupancy signal” in light of the specification includes any signal that represents, contains data representing, or is otherwise indicative of the occupancy in the space 105, e.g., that a human is present, that more than one human is present, that a certain number of humans are present, that an animal is present, that a window has opened, that a door has opened, that at least one person is present but not moving, that a person has fallen, that a person has moved to a different space 105, or any other condition of the space 105 determined at 340. Examiner further cites ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system.” [claim 13] – “estimating a quantity of the one or more living beings based on the number of clusters after merging.”))
Regarding claim 2,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, wherein the at least one processor is integrated with a receiver ([0052] – “204, a receiver/another transceiver/Origin can receive the signals from the multipath channel… The CSIs are extracted at 206 from the received radio signals using channel estimation.”) radio device that receives the transmitted radio signals that have traveled through the space. (Figs. 1-2; [0052] – “At 202, a transceiver/transmitter/Bot can transmit radio signals (e.g., a pulse or a pseudo random sequence) via a multipath channel”)
Regarding claim 3,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, wherein the at least one processor is integrated with a transmitter radio device (Figs. 1-2; [0052] – “At 202, a transceiver/transmitter/Bot can transmit radio signals (e.g., a pulse or a pseudo random sequence) via a multipath channel”) (Fig. 2; [0052] – “receive the signals from the multipath channel that are impacted by the breathing of a person. The CSIs are extracted at 206 from the received radio signals using channel estimation… process the CSIs to obtain processed CSIs”)
Regarding claim 15,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, wherein the radio signals indicate the set of biometric features of each occupant of the at least two distinct occupants, (Figs. 2, 4; [0092] – “If breathing is detected at 422, then a jumbo set of breathing rate candidates may be formulated at 424 for a multi-antenna system by repeating the steps 420, then the process moves on to 426.” Examiner notes that their broadest interpretation of the term “biometric feature” in light of the specification includes a human’s motion, breathing, heartrate, the state of a human, the health of a human, changes to the state or health of a human, and other characteristics of a human. See instant application specification paras. 52-53. Set of biometric features corresponds to candidates of the jumbo set of breathing rate candidates that will be associated with a cluster/person.) and
determining the occupancy further comprises associating each indicated biometric feature of the set of biometric features with at least one occupant of the at least two distinct occupants. (Figs. 4, 7; [0093] – “Breathing rate candidates are partitioned at 426 by clustering, and criteria are calculated for each cluster based on statistics. Clusters are merged at 428 when centroid distance between two clusters is less than a threshold. Statistics of the merged clusters are recalculated at 430. Breathing rates are estimated at 432 according to the statistics of the merged clusters. In can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” Associating an indicated biometric feature with an occupant corresponds to associating a breathing rate candidate with a cluster.)
Regarding claim(s) 17, 22,
Claim(s) 17, 22, is/are claims corresponding to claim(s) 1. Accordingly, the Examiner’s remarks and application of the prior art with respect to claim(s) 17, 22 are substantially the same as those made above with respect to claim(s) 1.
Regarding claim(s) 20, 25,
Claim(s) 20, 25 is/are claims corresponding to claim(s) 15. Accordingly, the Examiner’s remarks and application of the prior art with respect to claim(s) 20, 25, are substantially the same as those made above with respect to claim(s) 15.
Regarding claim 24,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The sensor system of claim 22, wherein the occupancy signal indicates a state of at least one of the at least two distinct occupants. ([0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”)
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 4-14, 18-19, 23, 27-29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen (‘492) in view of US 20170343658 A1 to Ramirez.
Regarding claim 4,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, further comprising outputting a control signal to a control system with the at least one processor, ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “people counting based on breathing… the system can output K.sub.0— K breathing estimations with the highest likelihoods. Here, K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” [0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”)
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
wherein the control system is associated with a heating, ventilating, and cooling system for the space (Paragraph 0032, “The controlling purpose could be the automatically controlling of domestic appliances or facilities, in particular heating, climate control, lighting or security facility, or in general all aspects concerning home automation and home entertainment.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of generating outputs based on occupant detection with possible use in smart home applications ([00146-148] – “The disclosed breathing monitoring method can be used to detect the presence of human, since it is capable of breathing detection. This is useful for smart home applications”) ; (2) Ramirez (‘658) teaches a specific method of using detection of a person in a room to control settings in the room ([0084] – “Thus for example, when with respect to the living room a detection data DD or a detection signal is generated due to a movement of a person, e.g. walking in the cited room, the lightning in this room can switched ON provided that it was switched OFF before. In parallel, when with respect to the bedroom another detection data or another detection signal DS is generated due to a further movement of another person, e.g. also walking in the cited room, the lightning in this room can switched OFF provided that it was switched ON before”; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 5,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, further comprising outputting a control signal to a control system with the at least one processor, ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “people counting based on breathing… the system can output K.sub.0— K breathing estimations with the highest likelihoods. Here, K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” [0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
wherein the control system is associated with a security system for the space (Paragraph 0032, “The controlling purpose could be the automatically controlling of domestic appliances or facilities, in particular heating, climate control, lighting or security facility, or in general all aspects concerning home automation and home entertainment.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of generating outputs based on occupant detection with possible use in smart home applications ([00146-148] – “The disclosed breathing monitoring method can be used to detect the presence of human, since it is capable of breathing detection. This is useful for smart home applications”) ; (2) Ramirez (‘658) teaches a specific method of using detection of a person in a room to control settings in the room ([0084] – “Thus for example, when with respect to the living room a detection data DD or a detection signal is generated due to a movement of a person, e.g. walking in the cited room, the lightning in this room can switched ON provided that it was switched OFF before. In parallel, when with respect to the bedroom another detection data or another detection signal DS is generated due to a further movement of another person, e.g. also walking in the cited room, the lightning in this room can switched OFF provided that it was switched ON before”; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 6,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, further comprising outputting a control signal to a control system with the at least one processor, ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “people counting based on breathing… the system can output K.sub.0— K breathing estimations with the highest likelihoods. Here, K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” [0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”)
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
wherein the control system is associated with a lighting system for the space (Paragraph 0032, “The controlling purpose could be the automatically controlling of domestic appliances or facilities, in particular heating, climate control, lighting or security facility, or in general all aspects concerning home automation and home entertainment.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of generating outputs based on occupant detection with possible use in smart home applications ([00146-148] – “The disclosed breathing monitoring method can be used to detect the presence of human, since it is capable of breathing detection. This is useful for smart home applications”) ; (2) Ramirez (‘658) teaches a specific method of using detection of a person in a room to control settings in the room ([0084] – “Thus for example, when with respect to the living room a detection data DD or a detection signal is generated due to a movement of a person, e.g. walking in the cited room, the lightning in this room can switched ON provided that it was switched OFF before. In parallel, when with respect to the bedroom another detection data or another detection signal DS is generated due to a further movement of another person, e.g. also walking in the cited room, the lightning in this room can switched OFF provided that it was switched ON before”; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 7,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, further comprising outputting a control signal to a control system with the at least one processor, ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “people counting based on breathing… the system can output K.sub.0— K breathing estimations with the highest likelihoods. Here, K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” [0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”)
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
Ramirez (‘658) teaches:
wherein the control system is associated with a power system for the space (Paragraph 0032, “The controlling purpose could be the automatically controlling of domestic appliances or facilities, in particular heating, climate control, lighting or security facility, or in general all aspects concerning home automation and home entertainment.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of generating outputs based on occupant detection with possible use in smart home applications ([00146-148] – “The disclosed breathing monitoring method can be used to detect the presence of human, since it is capable of breathing detection. This is useful for smart home applications”) ; (2) Ramirez (‘658) teaches a specific method of using detection of a person in a room to control settings in the room ([0084] – “Thus for example, when with respect to the living room a detection data DD or a detection signal is generated due to a movement of a person, e.g. walking in the cited room, the lightning in this room can switched ON provided that it was switched OFF before. In parallel, when with respect to the bedroom another detection data or another detection signal DS is generated due to a further movement of another person, e.g. also walking in the cited room, the lightning in this room can switched OFF provided that it was switched ON before”; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 8,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, further comprising outputting a control signal to a control system with the at least one processor, ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.” [00116-117] – “people counting based on breathing… the system can output K.sub.0— K breathing estimations with the highest likelihoods. Here, K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system” [0104] – “The breathing estimator 826 in this example may be configured for resolving multiple breathing rates given the extracted channel profiles, providing the breathing rate estimations to the users in response to the request.” [0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”)
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
wherein the control system is associated with an entertainment system for the space. (Paragraph 0032, “The controlling purpose could be the automatically controlling of domestic appliances or facilities, in particular heating, climate control, lighting or security facility, or in general all aspects concerning home automation and home entertainment.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of generating outputs based on occupant detection with possible use in smart home applications ([00146-148] – “The disclosed breathing monitoring method can be used to detect the presence of human, since it is capable of breathing detection. This is useful for smart home applications”) ; (2) Ramirez (‘658) teaches a specific method of using detection of a person in a room to control settings in the room ([0084] – “Thus for example, when with respect to the living room a detection data DD or a detection signal is generated due to a movement of a person, e.g. walking in the cited room, the lightning in this room can switched ON provided that it was switched OFF before. In parallel, when with respect to the bedroom another detection data or another detection signal DS is generated due to a further movement of another person, e.g. also walking in the cited room, the lightning in this room can switched OFF provided that it was switched ON before”; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 9,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
(Original) The method of claim 1, wherein the radio signals comprise one or more subcarriers, ([0056] – “the information-bearing signal is sent over the available frequency band over a number of parallel subcarriers. Each subcarrier can be treated as an independent narrow-band channel, and the total transmitted signal is the superposition of all the signals on all subcarriers.”) and wherein the at least one processor:
(i) analyzes amplitude information associated with the one or more subcarriers, ([0056] – “The CSI may summarize the behavior of the wireless channel (transmission medium) in the frequency domain by describing how the amplitude and phase of the transmitted signal is affected over each subcarrier.”) and
(ii) determines the occupancy in the space ([00116-117] – “K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system.”)
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
The method of claim 1, wherein the radio signals comprise one or more subcarriers (Paragraph 0022, “It is further an aspect of the embodiments of the invention to propose a method for detecting movement of objects and/or living beings in a radio range, in particular of an indoor area, which influence radio signals of at least one radio terminal transmitted on a number of radio channels divided each in at least one sub-channel, and received by a local fixed radio device in the radio range, whereby values of specific statistical parameters are combined to yield a chaos index value which is compared to a threshold value, and, if the comparison yields a predefined result, a notification procedures is started”), and wherein the at least one processor:
(i) analyzes amplitude information associated with the one or more subcarriers (see Fig. 6B where the intensity value of the signal (i.e. amplitude information as depicted by the darker/lighter shading) is associated with the horizontal axis (i.e. the “sub-channel (subcarrier) index”; see further paragraph 0111, “The FIG. 6a shows as the FIG. 5 again a 3D representation of the CSI-data which is similar to that in the FIG. 5, while the FIG. 6b shows a 2D-based “overhead”-view of the same data as in the FIG. 6a that is easier to interpret. On this “overhead”-view the vertical axis is the number of packets and the horizontal axis is the sub-channel (subcarrier) index.”), and
(ii) determines the occupancy in the space based on the amplitude information (see. Fig. 6B where occupancy is determined based on the intensity of the signal).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection in a room using CSI; (2) Ramirez (‘658) teaches a specific method of Ramirez (‘658) teaches a specific method of occupant detection using CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 10,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
(Original) The method of claim 1, wherein the radio signals comprise one or more subcarriers, ([0056] – “the information-bearing signal is sent over the available frequency band over a number of parallel subcarriers. Each subcarrier can be treated as an independent narrow-band channel, and the total transmitted signal is the superposition of all the signals on all subcarriers.”) and wherein the at least one processor:
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
The method of claim 1, wherein the radio signals comprise one or more subcarriers (Paragraph 0022, “It is further an aspect of the embodiments of the invention to propose a method for detecting movement of objects and/or living beings in a radio range, in particular of an indoor area, which influence radio signals of at least one radio terminal transmitted on a number of radio channels divided each in at least one sub-channel, and received by a local fixed radio device in the radio range, whereby values of specific statistical parameters are combined to yield a chaos index value which is compared to a threshold value, and, if the comparison yields a predefined result, a notification procedures is started”), and wherein the at least one processor:
(i) analyzes standard deviations of amplitude and phase of signals associated with the one or more subcarriers (Paragraph 0093, “Then for each set of CSI-values CSI-V of each sub-channel S-CH of the number of sub-channels a statistical parameter value SPV is determined or calculated, which is preferably a value parameterized by the average of the squared differences from the mean being in other words the variance. But it is also possible (although less preferable) to determine or calculate a value parameterized by the average of the absolute differences from the mean or to determine or calculate the square root of the average of the squared differences from the mean being in other words the standard deviation. Moreover it also possible to that the statistical parameter value SPV is determined or calculated only for a fraction of the CSI-values CSI-V of the set, which means in conclusion that the statistical parameter value SPV is calculated at least for a fraction of the CSI-values CSI-V.” further see, Paragraph 0109, “FIG. 6a shows a second graphical 3D representation of the measurement and evaluation of the change in the radio signals due to at least one of reflection, refraction, diffraction and absorption”, where in Fig. 6a, amplitude is shown by the peaks and phase change is shown by the time axis, therefore, standard deviation is calculated based on the amplitude and time change (i.e. phase) of the signals), and
(ii) determines occupancy in the space based on the standard deviations of amplitude and phase of the signals (Paragraph 0094-0095,” When this calculation is done for all sub-channels a set of statistical parameter values SPV is determined. Finally the statistical parameter values SPV of the determined set are added up to a “chaos index” value CIV…The algorithm for analysis consists of collecting CSI data over a “Sliding Window” of 50 consecutive packets, corresponding to roughly one second, and computing the variance for each of the 30 subcarriers independently within the window. Then these 30 variances are summed to determine a “chaos index” value for the window. If this “chaos index” value is over a certain arbitrary and/or experimentally or automatically determined value then movement is detected.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection in a room using CSI; (2) Ramirez (‘658) teaches a specific method of Ramirez (‘658) teaches a specific method of occupant detection using CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 11,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
(Original) The method of claim 1, wherein the radio signals comprise one or more subcarriers, ([0056] – “the information-bearing signal is sent over the available frequency band over a number of parallel subcarriers. Each subcarrier can be treated as an independent narrow-band channel, and the total transmitted signal is the superposition of all the signals on all subcarriers.”) and wherein the at least one processor:
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
The method of claim 1, wherein the radio signals comprise one or more subcarriers (Paragraph 0022, “It is further an aspect of the embodiments of the invention to propose a method for detecting movement of objects and/or living beings in a radio range, in particular of an indoor area, which influence radio signals of at least one radio terminal transmitted on a number of radio channels divided each in at least one sub-channel, and received by a local fixed radio device in the radio range, whereby values of specific statistical parameters are combined to yield a chaos index value which is compared to a threshold value, and, if the comparison yields a predefined result, a notification procedures is started”), and wherein the at least one processor: (i) analyzes temporal and frequency correlations of amplitude and phase of signals associated with the one or more subcarriers (Paragraph 0097, “Later on the graphical 3D/2D representations depicted in FIGS. 5 to 6b illustrate well the importance of the use of the variance in the signal instead of some sort of comparison to a calibration period. If a comparison to a calibration period were used, it would be very difficult to detect instances when there is no movement but a new stability point such as when the second door was left open but there was little movement otherwise. It was found that, independent of the testing environment, the sum of the variances of each of the subcarriers over a given period of time, which is called the “chaos index”, will not exceed a certain amount unless there is movement in the environment. Therefore it is avoided this problem which is very common in other movement detection algorithms. The variance mentioned here is only an example of the signal processing; many other options exist.”, where Figs. 6a and 6b depicts the time and frequency of the signals in the sub-channels and therefore the variance is the correlation between the temporal and frequency values of the signals [Note: amplitude and phase is taken into account using the peaks and the time change (i.e. phase change)]), and
(ii) determines occupancy in the space based on the temporal and frequency correlations of amplitude and phase of the signals (Paragraph 0094-0095,” When this calculation is done for all sub-channels a set of statistical parameter values SPV is determined. Finally the statistical parameter values SPV of the determined set are added up to a “chaos index” value CIV…The algorithm for analysis consists of collecting CSI data over a “Sliding Window” of 50 consecutive packets, corresponding to roughly one second, and computing the variance for each of the 30 subcarriers independently within the window. Then these 30 variances are summed to determine a “chaos index” value for the window. If this “chaos index” value is over a certain arbitrary and/or experimentally or automatically determined value then movement is detected.”; Paragraph 0102, “In the following in a third flow chart state FCS-3 a statistical parameter value SPV for each sub-channel S-CH over, e.g. at least the last 50 or more than the last 50, sets of CSI-values CSI-V is determined or calculated. The statistical parameter value SPV is as already mentioned preferably a value parameterized by the average of the squared differences from the mean being in other words the variance. But it is also possible (although less preferable) to determine or calculate a value parameterized by the average of the absolute differences from the mean or to determine or calculate the square root of the average of the squared differences from the mean being in other words the standard deviation.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection in a room using CSI; (2) Ramirez (‘658) teaches a specific method of Ramirez (‘658) teaches a specific method of occupant detection using CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 12,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
(Original) The method of claim 1, wherein the radio signals comprise one or more subcarriers, ([0056] – “the information-bearing signal is sent over the available frequency band over a number of parallel subcarriers. Each subcarrier can be treated as an independent narrow-band channel, and the total transmitted signal is the superposition of all the signals on all subcarriers.”) and wherein the at least one processor:
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
The method of claim 1, wherein the radio signals comprise one or more subcarriers (Paragraph 0022, “It is further an aspect of the embodiments of the invention to propose a method for detecting movement of objects and/or living beings in a radio range, in particular of an indoor area, which influence radio signals of at least one radio terminal transmitted on a number of radio channels divided each in at least one sub-channel, and received by a local fixed radio device in the radio range, whereby values of specific statistical parameters are combined to yield a chaos index value which is compared to a threshold value, and, if the comparison yields a predefined result, a notification procedures is started”), and wherein the at least one processor:
(i) analyzes averages of amplitude and phase of signals associated with the one or more subcarriers (Paragraph 0093, “Then for each set of CSI-values CSI-V of each sub-channel S-CH of the number of sub-channels a statistical parameter value SPV is determined or calculated, which is preferably a value parameterized by the average of the squared differences from the mean being in other words the variance. But it is also possible (although less preferable) to determine or calculate a value parameterized by the average of the absolute differences from the mean or to determine or calculate the square root of the average of the squared differences from the mean being in other words the standard deviation. Moreover it also possible to that the statistical parameter value SPV is determined or calculated only for a fraction of the CSI-values CSI-V of the set, which means in conclusion that the statistical parameter value SPV is calculated at least for a fraction of the CSI-values CSI-V.” further see, Paragraph 0109, “FIG. 6a shows a second graphical 3D representation of the measurement and evaluation of the change in the radio signals due to at least one of reflection, refraction, diffraction and absorption”, where in Fig. 6a, amplitude is shown by the peaks and phase change is shown by the time axis, therefore, variance is calculated based on the amplitude and time change (i.e. phase) of the signals),), and
(ii) determines occupancy in the space based on the averages of amplitude and phase of the signals (Paragraph 0094-0095,” When this calculation is done for all sub-channels a set of statistical parameter values SPV is determined. Finally the statistical parameter values SPV of the determined set are added up to a “chaos index” value CIV…The algorithm for analysis consists of collecting CSI data over a “Sliding Window” of 50 consecutive packets, corresponding to roughly one second, and computing the variance for each of the 30 subcarriers independently within the window. Then these 30 variances are summed to determine a “chaos index” value for the window. If this “chaos index” value is over a certain arbitrary and/or experimentally or automatically determined value then movement is detected.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection in a room using CSI; (2) Ramirez (‘658) teaches a specific method of Ramirez (‘658) teaches a specific method of occupant detection using CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 13,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
(Original) The method of claim 1, wherein the radio signals comprise one or more subcarriers, ([0056] – “the information-bearing signal is sent over the available frequency band over a number of parallel subcarriers. Each subcarrier can be treated as an independent narrow-band channel, and the total transmitted signal is the superposition of all the signals on all subcarriers.”) and wherein the at least one processor:
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
The method of claim 1, wherein the radio signals comprise one or more subcarriers (Paragraph 0022, “It is further an aspect of the embodiments of the invention to propose a method for detecting movement of objects and/or living beings in a radio range, in particular of an indoor area, which influence radio signals of at least one radio terminal transmitted on a number of radio channels divided each in at least one sub-channel, and received by a local fixed radio device in the radio range, whereby values of specific statistical parameters are combined to yield a chaos index value which is compared to a threshold value, and, if the comparison yields a predefined result, a notification procedures is started”), and wherein the at least one processor:
(i) analyzes energy in the peaks of CSI amplitude and phase of signals associated with the one or more subcarriers (see Fig. 6A which depicts the energy in peaks of the CSI amplitude and phase signals for the sub-channels; where in Fig. 6a, amplitude is shown by the peaks and phase change is shown by the time axis, therefore, variance is calculated based on the amplitude and time change (i.e. phase) of the signals),), and
(ii) determines occupancy in the space based on the energy in the peaks of CSI amplitude and phase of the signals (see Fig. 6b which shows the determination of occupancy based on the analysis of the energy in peaks of the CSI amplitude and phase signals for the sub-channels).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection in a room using CSI; (2) Ramirez (‘658) teaches a specific method of Ramirez (‘658) teaches a specific method of occupant detection using CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 14,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) does not explicitly teach the remainder of the claim elements.
Ramirez (‘658) teaches:
The method of claim 1, wherein the occupancy-centric algorithm is configured to determine occupancy in the space based on changes in one or more of signal amplitude (see Fig. 6B where occupancy is determined based on the amplitude of the signal), energy, amplitude change, energy change, amplitude spread, energy spread, amplitude spread change, and energy spread change of the radio signals.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Ramirez (‘658)’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection in a room using CSI; (2) Ramirez (‘658) teaches a specific method of Ramirez (‘658) teaches a specific method of occupant detection using CSI; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim 18,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The sensor system of claim 17, wherein the at least two distinct occupants impact at least one of an amplitude, a phase, or a timing of the radio signals distinctly. ([00118-125] – “geometric extraction to infer the position of the people under monitoring. This could be helpful in a scenario of two people breathing with identical breathing rates, since they may not be located at the same position and thus can be potentially distinguished from each other by different locations… Both the amplitude and phase are functions of the subcarrier index k. One can observe that: the amplitude |H.sub.fc(t) | changes periodically with the breathing frequency / across time t; the amplitude \H.sub.k(t) | almost changes periodically with the subcarrier index k given a fixed time t; the phase .H.sub.fc(t) contains crucial information about the path delay d.sub.1… From -H.sub.k(t), the system can estimate d.sub.x which is related to the position of the person under monitoring… the estimation of effective breathing strength and the extraction of geometric information about breathing can also be extended to multi-person breathing scenario.” Examiner further notes that this claim does not require any determination or distinction of the impacts.)
Regarding claim 19,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The sensor system of claim 17, wherein the occupancy signal indicates a state of at least one of the at least two distinct occupants. ([0118-119] – “In addition to the breathing rate estimations, the strength of breathing can also be an important indicator of medical conditions. For example, fast and shallow breathing can be an indicator of Tachypnea, an abnormal breathing caused by fever, fear, and other factors.
Meanwhile, it is useful to know the source location of the breathing signal, e.g., geometric extraction to infer the position of the people under monitoring.”)
Regarding claim 23,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The sensor system of claim 22, wherein the occupancy-centric algorithm tracks at least one of position and movement of the at least two distinct occupants in the space. ([00150] – “Therefore, the phase changes can be utilized to track human breathing.”)
Regarding claim 27,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, wherein the occupancy-centric algorithm further determines a count of occupants in the space ([00116-117] – “The disclosed system may use the likelihood of each cluster after merging clusters to formulate an estimation of K… Then, the system can output K.sub.0… K.sub.0 stands for an estimated number of people who breathed in the coverage area of the disclosed system. [claim 13] – “estimating a quantity of the one or more living beings based on the number of clusters after merging.”) based on grouping the set of biometric features into subsets of biometric features that are respectively associated with one occupant of the at least two distinct occupants, (Figs. 4, 7; [0093] – “Breathing rate candidates are partitioned at 426 by clustering, and criteria are calculated for each cluster based on statistics. Clusters are merged at 428 when centroid distance between two clusters is less than a threshold. Statistics of the merged clusters are recalculated at 430. Breathing rates are estimated at 432 according to the statistics of the merged clusters. In can be understood that because the centroid of each cluster represents an estimation of the breathing rate associated with one person. The system can detect one or more breathing rates of one or more persons at the same time, based on the centroid of each cluster.” Clustered/merged jumbo set breathing rate candidates correspond to grouped subsets of biometric features.) and wherein the occupancy signal indicates the determined count of occupants in the space. ([0055] – “generate outputs that quantify the breathing rates of people being in the vicinity of the wireless transceivers.”)
Regarding claim(s) 28 and 29,
Claim(s) 28 and 29 is/are claims corresponding to claim(s) 27. Accordingly, the Examiner’s remarks and application of the prior art with respect to claim(s) 28 and 29 are substantially the same as those made above with respect to claim(s) 27.
Claim(s) 16, 21, 26 s/are rejected under 35 U.S.C. 103 as being unpatentable over Chen (‘492) in view of Zhang (WiFi-ID: Human Identification using WiFi signal; 10.1109/DCOSS.2016.30; published May 2016).
Regarding claim 16,
Chen (‘492) teaches the invention as claimed and discussed above.
Chen (‘492) further teaches:
The method of claim 1, wherein the radio signals indicate the set of biometric features of each occupant of the at least two distinct occupants, (Figs. 2, 4; [0092] – “If breathing is detected at 422, then a jumbo set of breathing rate candidates may be formulated at 424 for a multi-antenna system by repeating the steps 420, then the process moves on to 426.” Examiner notes that their broadest interpretation of the term “biometric feature” in light of the specification includes a human’s motion, breathing, heartrate, the state of a human, the health of a human, changes to the state or health of a human, and other characteristics of a human. See instant application specification paras. 52-53. Set of biometric features corresponds to the jumbo set candidates. [00149] – “The disclosed breathing monitoring can also be used for monitoring other vital signs that exhibits a periodically changing pattern. For instance, when the breathing monitoring devices operate in high-center frequency, e.g., in 60 GHz, they can also monitor human heartbeat.” and the method further comprises
Zhang teaches:
recognizing at least one occupant of the at least two distinct occupants based on at least one biometric feature of the set of biometric features. ([I. Introduction] – “When a person walks through these spaces, they create a perturbation in this RF field. By closely examining these perturbations using the Channel State Information (CSI), it is possible to identify basic human activities such as standing, sitting, walking and running [25] and even hand gestures [19] and keystrokes typed on a keyboard [3]. In this paper, we show for the first time that WiFi signals can also be used to uniquely identify people. Everyone’s natural walking style (i.e. gait) is unique which is characterized by the differences in the limb (hand and feet) movement patterns and velocity [15]. These patterns are also highly repetitive.” [IV. Overview of WiFi-ID] – “The CSI data collected during the testing phase are processed in a similar manner to extract the same set of features which are then matched with those in the database to uniquely identify the test subjects.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have applied Zhang’s known technique to Chen (‘492)’s known method ready for improvement to yield predictable results. Such a finding is proper because (1) Chen (‘492) teaches a base method of occupant detection based on analysis of periodically changing CSI for use in smart home applications ([00149] – “The disclosed breathing monitoring can also be used for monitoring other vital signs that exhibits a periodically changing pattern. ([00146-148] – “The disclosed breathing monitoring method can be used to detect the presence of human, since it is capable of breathing detection. This is useful for smart home applications”); (2) Zhang teaches a specific method of analysis of periodically changing CSI measurements to uniquely identify/recognize people for possible use in smart home applications” ([I. Introduction] – “the goal is to uniquely a person from a group of N people. This is representative of a smart home or small office setting.”) ; (3) one of ordinary skill in the art would have recognized that applying the known technique would have yielded predictable results and resulted in an improved system; and (4) no additional findings based on the Graham factual inquiries are necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness (See MPEP 2143).
Regarding claim(s) 21 and 26,
Claim(s) 21 and 26 is/are claims corresponding to claim(s) 16. Accordingly, the Examiner’s remarks and application of the prior art with respect to claim(s) 21 and 26 are substantially the same as those made above with respect to claim(s) 16.
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.
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/JULIANA CROSS/Examiner, Art Unit 3648
/William Kelleher/Supervisory Patent Examiner, Art Unit 3648