DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
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.
Claims 1-3, 5-13, 17-20, 23 and 24 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1, 1, 3, 4, 6-9, 23, 23, 25, 28, 24, 26, 29, 29, 30 and 32 respectively of U.S. Patent No. 12,033,166 in view of Counts (pub. no. 20090063099). The respective claims of the ‘166 patent would anticipate the instant claims except that the ‘166 patent claims do not disclose associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude. Counts however, teaches associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude (“FIG. 4 illustrates a methodology 400 of inferring user activity based on routing data in accordance with an aspect of the subject innovation. While the exemplary method is illustrated and described herein as a series of blocks representative of various events and/or acts, the subject innovation is not limited by the illustrated ordering of such blocks. For instance, some acts or events may occur in different orders and/or concurrently with other acts or events, apart from the ordering illustrated herein, in accordance with the innovation. In addition, not all illustrated blocks, events or acts, may be required to implement a methodology in accordance with the subject innovation. Moreover, it will be appreciated that the exemplary method and other methods according to the innovation may be implemented in association with the method illustrated and described herein, as well as in association with other systems and apparatus not illustrated or described. Initially and at 410 a user switches on a portable device that can log route data via a positioning system such as a global positioning system. Next, and at 420 the user engages in an activity wherein routing information can be collected throughout performance of the activity. For example, acquiring data can include collection of latitude/longitude/altitude data when the user is engaging in sporting events (e.g., hiking, parachuting, and the like). Additional information such as users' physiological and other biometric data can further be acquired to facilitate subsequent inference for type of activity based on the acquired routing data. At 430, the collected data (e.g., the raw data can be uploaded to a server or to a network. Subsequently, such collected data can be analyzed to infer user activity, at 440. For example, if there is a rapid and substantial decrease in elevation while the longitude and latitude position remains relatively constant, an inference can be made that the user is involved in an activity that requires a quick shift in elevation such as parachuting. Likewise, if there occurs a change in altitude in conjunction with changes in longitude and latitude, an inference can be made that the user is involved in an activity that results in changes in all coordinates such as skiing or biking.
FIG. 5 illustrates a related methodology 500 of inferring user activity in accordance with a particular aspect of the subject innovation. Initially and at 510, biometric and physiological data can be collected form a body of a user who is engaged in an activity (e.g., collection of pulse rate, blood pressure during sporting engagements). Subsequently and at 520, routing data collected during such activity can be acquired and uploaded with the biometric data to a server. At 530, based on the uploaded biometric data, the server performs an analysis on the routing data. It is to be appreciated that contextual data (e.g., user demographics) current events, calendar, time of day, can further be employed in such analysis. At 540, the inferred activity and classification can be presented to other users who can search such classifications through a plurality of user interfaces. For example, sensors attached to a user's body can capture and continuously sample a range of data about the user and their states such as motion from an accelerometer, contextual variables like altitude and temperature, and biological data such as heart rate. Such inputs can data can then be processed and automatically integrated into a route document that contains rich information about motion through time and space annotated with a variety of metadata and digital objects. Such route document can inform a user about: stress levels experienced when taking a particular route; potential physical training affects; levels of difficulty as defined base on a predetermined criteria; scenic possibilities and the like}, [0030] & [0031]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘166 patent and Counts are directed methods of analyzing activity data. To add the biometric and physiological data to the other activity data as taught by Counts to the ‘166 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘166 invention to include associating the Counts biometric and physiological data to the other recorded activity data. To do so would allow the feedback to provide a richer data package thereby increasing the perceived value of the method.
Claims 25 and 36 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 1 respectively of U.S. Patent No. 12,033,166 in view of Jallon (pub. no. 20120078594). The respective claims of the ‘166 patent would anticipate the instant claims except that the ‘166 patent claims do not disclose generating a graph that indicate activity types and associating the activity type with effort or resistance. Jallon however, teaches generating a graph indicating activity types and associating the activity type with effort or resistance (“FIG. 3 illustrates an exemplary recording of a walking session of a user of the system, within the first graph the three curves representing the values of x1, x2 and x3 equal respectively to dva1, dva2 and va transmitted by the device DISP, as a function of time, and in the second graph, the walking state of the patient determined by the system SYST.
In this example, the user has walked on the flat (state 1) for 5 seconds, has then walked up a climb (state 3) for 10 seconds, has then walked down a descent (state 2) for 3 seconds, has then walked on the flat (state 1) for 60 seconds, has then walked down a descent (state 2) for 37 seconds, has then walked up a climb (state 3) for 69 seconds, has then walked down a descent (state 2) for 12 seconds, has then walked up a climb (state 3) for 11 seconds, and has then climbed a staircase (state 4) for 22 seconds”, [0059] & [0060]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘166 patent and Jallon are directed methods of analyzing activity data. To add a graph that indicates activity type as taught by Jallon to the ‘166 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘166 invention to include the Jallon graph indicating activity type. To do so would express activity classification in an intuitive manner thereby increasing the perceived value of the method.
Claims 1-3, 5-8, 10, 11, 19 and 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 1, 5, 28, 25, 14, 14, 29, 29, 31 and 31 respectively of U.S. Patent No. 11,410,188 in view of Counts (pub. no. 20090063099). The respective claims of the ‘188 patent would anticipate the instant claims except that the ‘188 patent claims do not disclose associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude. Counts however, teaches associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude ([0030] & [0031]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘188 patent and Counts are directed methods of analyzing activity data. To add the biometric and physiological data to the other activity data as taught by Counts to the ‘188 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘188 invention to include associating the Counts biometric and physiological data to the other recorded activity data. To do so would allow the feedback to provide a richer data package thereby increasing the perceived value of the method.
Claims 25 and 26 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 1 respectively of U.S. Patent No. 11,410,188 in view of Jallon (pub. no. 20120078594). The respective claims of the ‘188 patent would anticipate the instant claims except that the ‘188 patent claims do not disclose generating a graph that indicate activity types and associating the activity type with effort or resistance. Jallon however, teaches generating a graph indicating activity types and associating the activity type with effort or resistance ([0059] & [0060]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘188 patent and Jallon are directed methods of analyzing activity data. To add a graph that indicates activity type as taught by Jallon to the ‘188 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘188 invention to include the Jallon graph indicating activity type. To do so would express activity classification in an intuitive manner thereby increasing the perceived value of the method.
Claims 1-11, 14, 17-21, 23 and 24 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 1, 27, 26, 29, 25, 1, 10, 4, 32, 32, 32, 33, 33, 40, 40, 42, 41 and 43 respectively of U.S. Patent No. 11,023,903 in view of Counts (pub. no. 20090063099). The respective claims of the ‘903 patent would anticipate the instant claims except that ‘903 patent claims fail to disclose associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude. Counts however, teaches associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude ([0030] & [0031]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘903 patent and Counts are directed methods of analyzing activity data. To add the biometric and physiological data to the other activity data as taught by Counts to the ‘903 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘903 invention to include associating the Counts biometric and physiological data to the other recorded activity data. To do so would allow the feedback to provide a richer data package thereby increasing the perceived value of the method.
Claims 25 and 26 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 1 respectively of U.S. Patent No. 11,023,903 in view of Jallon (pub. no. 20120078594). The respective claims of the ‘903 patent would anticipate the instant claims except that the ‘903 patent claims fail to disclose generating a graph that indicate activity types and associating the activity type with effort or resistance. Jallon however, teaches generating a graph indicating activity types and associating the activity type with effort or resistance ([0059] & [0060]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘903 patent and Jallon are directed methods of analyzing activity data. To add a graph that indicates activity type as taught by Jallon to the ‘903 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘903 invention to include the Jallon graph indicating activity type. To do so would express activity classification in an intuitive manner thereby increasing the perceived value of the method.
Claims 1, 2, 6, 7, 10, 11, 19, 20 and 22 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 1, 25, 7, 26, 26, 28, 28 and 29 respectively of U.S. Patent No. 10,019,721 in view of Counts (pub. no. 20090063099). The respective claims of the ‘721 patent would anticipate the instant claims except that ‘721 patent claims fail to disclose associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude. Counts however, teaches associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude ([0030] & [0031]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘721 patent and Counts are directed methods of analyzing activity data. To add the biometric and physiological data to the other activity data as taught by Counts to the ‘721 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘721 invention to include associating the Counts biometric and physiological data to the other recorded activity data. To do so would allow the feedback to provide a richer data package thereby increasing the perceived value of the method.
Claims 25 and 26 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 1 respectively of U.S. Patent No. 10,019,721 in view of Jallon (pub. no. 20120078594). The respective claims of the ‘721 patent would anticipate the instant claims except that the ‘721 patent claims fail to disclose generating a graph that indicate activity types and associating the activity type with effort or resistance. Jallon however, teaches generating a graph indicating activity types and associating the activity type with effort or resistance ([0059] & [0060]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘721 patent and Jallon are directed methods of analyzing activity data. To add a graph that indicates activity type as taught by Jallon to the ‘721 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘721 invention to include the Jallon graph indicating activity type. To do so would express activity classification in an intuitive manner thereby increasing the perceived value of the method.
Claims 1-3, 6-11, 14-16, 18-20 and 24 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 1, 2, 14, 17, 14, 15, 23, 23, 24, 31, 31, 30, 39, 39 and 45 respectively of U.S. Patent No. 9,665,873 in view of Counts (pub. no. 20090063099). The respective claims of the ‘873 patent would anticipate the instant claims except that ‘873 patent claims fail to disclose associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude. Counts however, teaches associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude ([0030] & [0031]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘873 patent and Counts are directed methods of analyzing activity data. To add the biometric and physiological data to the other activity data as taught by Counts to the ‘873 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘873 invention to include associating the Counts biometric and physiological data to the other recorded activity data. To do so would allow the feedback to provide a richer data package thereby increasing the perceived value of the method.
Claims 25 and 26 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 1 respectively of U.S. Patent No. 9,665,873 in view of Jallon (pub. no. 20120078594). The respective claims of the ‘873 patent would anticipate the instant claims except that the ‘873 patent claims fail to disclose generating a graph that indicate activity types and associating the activity type with effort or resistance. Jallon however, teaches generating a graph indicating activity types and associating the activity type with effort or resistance ([0059] & [0060]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the ‘873 patent and Jallon are directed methods of analyzing activity data. To add a graph that indicates activity type as taught by Jallon to the ‘873 invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the ‘873 invention to include the Jallon graph indicating activity type. To do so would express activity classification in an intuitive manner thereby increasing the perceived value of the method.
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 1-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. According to the specification, the invention relates to a activity monitoring method and system that monitors activity data and provides feedback based on the data to the user. Exemplary claims 1, 10, 19 and 25 include the following underlined claim elements:
1. A method comprising: determining an effort parameter associated with a user during an activity based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the activity, or a step rate associated with the user during the activity, wherein the effort parameter comprises a value associated with the user that is determined relative to at least one of an anaerobic threshold of the user, an aerobic threshold of the user, a resting threshold of the user, or a maximum threshold of the user; determining a resistance experienced by the user during the activity, wherein the resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; generating a first comparison result based on comparing the effort parameter associated with the user to a first threshold criteria of a set of threshold criteria corresponding to an activity zone; generating a second comparison result based on comparing the resistance associated with the user to a second threshold criteria of the set of threshold criteria corresponding to the activity zone; classifying, based on the first comparison result and the second comparison result, the activity of the user as an activity type; and associating the activity type with at least one of electrocardiogram data of the user measured during the activity or blood pressure data of the user measured during the activity; wherein the method is executed by one or more processors
10. A system comprising: a memory comprising instructions; and a processor operatively coupled to the memory, the processor to execute the instructions to perform operations comprising: determining an effort parameter associated with a user during an activity based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the activity, or a step rate associated with the user associated with the user during the activity, wherein the effort parameter comprises a value associated with the user that is determined relative to at least one of an anaerobic threshold of the user, an aerobic threshold of the user, a resting threshold of the user, or a maximum threshold of the user; determining a resistance experienced by the user during the activity, wherein the resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; generating a first comparison result based on comparing the effort parameter associated with the user to a first threshold criteria of a set of threshold criteria corresponding to an activity zone; generating a second comparison result based on comparing the resistance associated with the user to a second threshold criteria of the set of threshold criteria corresponding to the activity zone; classifying, based on the first comparison result and the second comparison result, the activity of the user as an activity type; and associating the activity type with at least one of electrocardiogram data of the user measured during the activity or blood pressure data of the user measured during the activity
19. A non-transitory computer readable medium comprising instructions, which when executed by a processor, cause the processor to perform operations comprising: determining an effort parameter associated with a user during an activity based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during an activity, or a step rate associated with the user associated with the user during an activity, wherein the effort parameter comprises a value associated with the user that is determined relative to at least one of an anaerobic threshold of the user, an aerobic threshold of the user, a resting threshold of the user, or a maximum threshold of the user; determining a resistance experienced by the user during the activity, wherein the resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; generating a first comparison result based on comparing the effort parameter associated with the user to a first threshold criteria of a set of threshold criteria corresponding to an activity zone; generating a second comparison result based on comparing the resistance associated with the user to a second threshold criteria of the set of threshold criteria corresponding to the activity zone; classifying, based on the first comparison result and the second comparison result, the activity of the user as an activity type; and associating the activity type with at least one of electrocardiogram data of the user measured during the activity or blood pressure data of the user measured during the activity
25. A method comprising: collecting, during a first time period, first performance data associated with an activity of a user; determining, based on the first performance data, a first effort associated with the user during the first time period based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the first time period, or a step rate associated with the user associated with the user during the first time period; determining, based on the first performance data, a first resistance experienced by the user during the first time period, wherein the first resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; determining the first effort satisfies a first condition associated with a first effort threshold zone of a set of effort threshold zones; determining the first resistance satisfies a second condition associated with a first resistance threshold zone of a set of effort threshold zones; classifying, based on the first effort threshold zone and the first resistance threshold zone, a first segment of the activity as a first activity type of a set of activity types; collecting, during a second time period, second performance data relating to the activity performed by a user; determining, based on the second performance data, a second effort associated with the user during the second time period based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the second time period, or a step rate associated with the user associated with the user during the second time period; determining, based on the second performance data, a second resistance experienced by the user during the second time period, wherein the second resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; determining the second effort satisfies a second condition associated with a second effort threshold zone of the set of effort threshold zones; determining the first resistance satisfies a second condition associated with a second resistance threshold zone of a set of effort threshold zones; classifying, based on the second effort threshold zone and the second resistance threshold zone, a second segment of the activity as a second activity type of the set of activity types; and generating a graph comprising a first indication of the first activity type associated with the first time period and a second indication of the second activity type associated with the second time period.
The underlined claim elements above are directed to the court enumerated abstract ideas of Mental Processes including observation, evaluation, and judgement because the claims are directed to series of steps that observe activity data, evaluate that data, determine a classification for the activity and provide an indication of the classification to the user. The claims do not go beyond requiring collection, analysis, and display of available information in a particular field, stating those functions in general terms without limitations to specific technical implementations for performing the functions that are an improvement to a computing system or advancement in a network technology. The claims simply define a desirable information-based result. The various dependent claims only further detail the abstract ideas or constitute insignificant extra solution activity and consequently are also considered abstract ideas.
This judicial exception is not integrated into a practical application because the claims do not recite additional elements that would integrate the abstract idea into a practical application. The recited “one or more processors”, “memory”, “processor”, and “non-transitory computer readable medium” amount to implementing the abstract idea on a general purpose computer, and/or do no more than generally link the use of a judicial exception to a particular technological environment or field of use. Applicant’s specification states “[t]he system (whether in the monitoring device, personal computer or remote server or elsewhere) processes the data by accessing memory 2500 (again this may be in the monitoring device, personal computer or remote server and is not necessarily in the same place as the processing circuitry) containing the classification system algorithms and threshold criteria (and preferably user information) to determine the activities conducted and the level of performance as described above”, [0741]. This supports a conclusion that the method operates in a general computing environment and that the claim provides mere instructions to apply the judicial exception on a computer. Even when the limitations are viewed in combination, the additional elements in this claim do no more than automate the mental processes needed to be performed, using the one of more computer components as tools. While this type of automation is an improvement in a general sense as opposed to performance manually, there is no change to the computers and other technology that are recited in the claim as automating the abstract ideas, and thus this claim cannot improve computer functionality or other technology There is no improvement made to computer technology since the claims are directed to and evaluating data to classify it. This is not related to a long standing problem in computer technology. Additionally, there is no practical application as there is no particular machine that is used to implement the claim language and only generic computer components are used to perform the invention. Also, there is no transformation of the machine used in the application into a different state or thing. Lastly, the claims do not attempt to apply the abstract idea in a meaningful way beyond simply using a generic computer. The various dependent claims only further detail the abstract idea or are insignificant extra solution activity and also fail to rise significantly more than the abstract ideas.
Claims 1, 10, 19 and 25 do not recite additional elements, individually or in combination, that amount to significantly more than the abstract idea. As discussed above with respect to the lack of a practical application, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here, i.e., mere instructions to apply an exception using generic computer component(s) cannot provide an inventive concept. The receiving, identifying, and generating of data does not indicate that the activity is anything other than a generic computer component performing the task. Court decisions cited in MPEP 2106.05(d)(II) indicate these are well-understood, routine, and conventional functions (See receiving or transmitting data over a network (MPEP 2106.05(d)(II)(i)), performing repetitive calculations (MPEP 2106.05(d)(II)(ii)), electronic recordkeeping (MPEP 2106.05(d)(II)(iii)), storing and retrieving information in memory (MPEP 2106.05(d)(II)(iv)), determining an estimated outcome and setting a price (MPEP 2106.05(d)(II)(v)), and arranging a hierarchy of groups, sorting information, eliminating less restrictive pricing information and determining a price (MPEP 2106.05(d)(II)(vi)).
Therefore, the claims are directed to an abstract idea that lacks significantly more and thus are not patent eligible.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 6, 17 and 23 are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. The claims expand the threshold criteria to include an ideal zone corresponding to a plurality of users. Consequently, the dependent claims do not further limit their respective parent claims. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter 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 pre-AIA 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims under pre-AIA 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of pre-AIA 35 U.S.C. 103(c) and potential pre-AIA 35 U.S.C. 102(e), (f) or (g) prior art under pre-AIA 35 U.S.C. 103(a).
Claims 1-6, 8, 10-13, 15 and 17-24 is/are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Yuen et al. (pub. no. 20120084054) in view of Counts (pub. no. 20090063099).
Regarding claim 1, Yuen discloses a method comprising: determining an effort parameter associated with a user during an activity based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the activity, or a step rate associated with the user during the activity, wherein the effort parameter comprises a value associated with the user that is determined relative to at least one of an anaerobic threshold of the user, an aerobic threshold of the user, a resting threshold of the user, or a maximum threshold of the user (“In another embodiment, data from one or more physiological sensors may be employed, alone or in combination with data of the motion sensor(s) and altitude sensor(s), to determine or assess the user state. (See, for example, FIGS. 4F and 4O). As discussed in more detail below, physiological sensor(s) determine, sense, detect, assess and/or obtain information which is representative of physiological condition and/or information of the user (for example, blood pressure, pulse rate, blood sugar and the waveform shape corresponding to the heart beat). Such an embodiment may, among other things, enhance the accuracy of identifying the user state and/or improve the confidence of the correctness/accuracy of the identified user state”, [0127]);
determining a resistance experienced by the user during the activity, wherein the resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; generating a first comparison result based on comparing the effort parameter associated with the user to a first threshold criteria of a set of threshold criteria corresponding to an activity zone; generating a second comparison result based on comparing the resistance associated with the user to a second threshold criteria of the set of threshold criteria corresponding to the activity zone; classifying, based on the first comparison result and the second comparison result, the activity of the user as an activity type (“The data from the altitude, motion and physiological sensors may also be used to determine, calculate, estimate, improve and/or classify other activity-related metrics such as, for example, user speed and distance (FIG. 4G). Indeed, the same sensor combinations may also be used to determine, identify and/or classify the user state in order to select the appropriate activity quantification algorithm--see, for example, FIG. 4H wherein calorie burn corresponding to level ground, up/down hill, up/down stairs walking or running. Likewise this set or subset of sensors may be used to estimate and/or calculate the probability of each user state, which may then be used to select the activity quantification algorithm with maximum likelihood (see FIG. 4I or 4M) or merged together to provide the expected value (see FIG. 4J or 4N). A number of methods may be devised to implement each of the embodiments shown in FIGS. 4A-4J and 4M-4R, including but not limited to, iterative and batch algorithms that use ad hoc logic, statistical filtering and classification techniques, neural networks, k-means classifiers, and decision trees. Such conventional techniques or methods may be implemented in the present inventions or adaptively modified as they are used in the invention. As such, these embodiments of the inventions are merely exemplary and are not intended to be exhaustive or limiting of the inventions to, for example, the precise forms, techniques, flow, and/or configurations disclosed”, [0128];
“In another embodiment, the portable monitoring device of the present inventions includes one or more physiological sensors to further assess the activity state of the user. For example, with reference to FIGS. 1B and 7, the physiological sensor(s) may provide data which is representative of the physiological condition of the user. The processing circuitry may correlate the data from the physiological sensor(s) with the (i) data which is representative of the altitude and/or changes in altitude and (ii) data which is representative of the motion of the user, to determine, estimate and/or calculate energy and/or calorie "burn" of the user. For example, an apparent increase in altitude coupled with the expected number of human steps and a correspondingly increase in heart rate enables the processing circuitry (and techniques implemented thereby) to assess such data and more accurately correlate the activity to a user state--for example, distinguish stair steps from a measurement artifact”, [0131];
“The portable monitoring device may include transmitter circuitry to communicate energy and/or calorie "burn" of the user to, for example, an external user interface, the internet, social or media site (for example, Fitbit or Facebook) and/or computing system. (See, for example, FIG. 1F). The portable monitoring device may also output raw or pseudo-raw sensor data as well as a correlation thereof (see, for example, FIG. 6). Indeed, the portable monitoring device may output the other activity-related metrics, including, for example, (i) in the context of running/walking on level, substantially level, or relatively level ground, (a) number of steps, which may be categorized according to the number of steps associated with a user state, for example, walking, jogging and/or running, (b) distance traveled and/or (c) pace, (ii) in the context of running/walking on stairs, hills or ground having a grade of greater than, for example, about 3%, (a) number of stair and/or hill steps, which may be categorized, correlated or organized/arranged according to, for example, the speed, pace and/or activity state of the user (for example, the number of stair and/or hill steps pertaining to walking, jogging and/or running), (b) number of flights of stairs, (c) ascent/descent distance on stairs and/or hills, (d) pace, (e) ascent/descent on elevators, (f) number of calories expended by walking/jogging/running on stairs and/or hills and/or (g) quantify/compare the additional calories expended or burnt from stairs/hills relative to, versus or over level ground, (iii) in the context of swimming, number of strokes, time between strokes, leg kicks and similar metrics (variance of stroke time, mean stroke time, etc.), depth underwater, strokes per lap, lap time, pace and/or distance, (iv) in the context of using a bicycle, wheelchair, skateboard, skis, snowboard, ladder, etc., (a) ascent/descent distance traversed, (b) number of additional calories expended, (c) time of a downward "run" or upward "climb", (d) number of calories expended, (e) number of pedal rotations, (f) arm or wheel rotation, (g) the grade of the surface, (h) pushes, kicks and/or steps. This list of activities (if applicable to the particular embodiment) is merely exemplary and is not intended to be exhaustive or limiting of the inventions to, for example, the precise forms, techniques, flow, and/or configurations disclosed”, [0179]).
Regarding claims 1 and 2, it is noted that Yuen does not disclose associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude. Counts however teaches associating the activity type with electrocardiogram data, blood pressure data, speed, power, step rate, gradient or altitude ([0030] & [0031]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both Yuen and Counts are directed methods of analyzing activity data. To add the biometric and physiological data to the other activity data as taught by Counts to the Yuen invention would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the Yuen invention to include associating the Counts biometric and physiological data to the other recorded activity data. To do so would allow the feedback to provide a richer data package thereby increasing the perceived value of the method.
Regarding claim 3, Yuen discloses determining the effort parameter is further based on at least one of an oxygen uptake of the user or a body weight of the user (“In one embodiment, the speed of the user may be calculated, determined and/or estimated as the user's step count over a time epoch multiplied by one or more step lengths of the user (which may be programmed, predetermined and/or estimated (for example, based on attributes of the user (for example, height, weight, age, leg length, and/or gender))), which may be estimated, obtained (for example, from a look-up table or database) and/or interpolated from the MET table to obtain the user's energy expenditure. In one embodiment, step length may take one of two values that are indicative of a walking and a running step length dependent on the step frequency and/or acceleration characteristics of the user. In a preferred embodiment, step length may be described as a linear function of step frequency”, [0066];
“The speed value may be converted to calorie expenditure by multiplying the corresponding MET value by the user's BMR. BMR may be obtained through any of a number of well-known equations based on height, weight, gender, age, and/or athletic ability or through designated BMR measurement devices”, [0076]).
Regarding claim 4, Yuen discloses the effort parameter is determined based on a period threshold, wherein the period threshold comprises a threshold period of time that the value of the effort parameter is maintained (“In one embodiment, the processing circuitry may employ a decision-tree based technique/algorithm to interpret or assess changes in altitude, motion and physiological condition of the user. The decision tree based technique/algorithm may employ the flow chart of FIG. 4L in which, as another embodiment, the processing circuitry determines the type of activity by evaluating the change in altitude of the user on a change in height per step basis ("ΔH-S") or the use of an elevator by a sustained rate of height change per temporal period (for example, seconds) ("ΔH-t") in the absence of steps in conjunction with heart rate ("HR"). The change in height per step, change in height per second, and heart rate are evaluated against a plurality of thresholds and/or ranges to determine whether the user is, for example, moving (for example, running or walking) on level ground, on an escalator or in an elevator, traversing stairs and/or traversing a hill or the like. In one embodiment, Threshold 1, Threshold 2, Threshold 3 and Threshold 4 have the relationship Threshold 1>;Threshold 2>;Threshold 3>;Threshold 4. Thus, in this embodiment, the processing circuitry employs data from the motion sensor to assess the user state based on data from the altitude sensor and physiological sensor. Similar techniques/algorithms may employ the flow of FIG. 4L and a similar flowchart based on thresholds in relation to other certain physiological conditions including blood pressure, pulse rate, blood sugar and the waveform shape corresponding to the heart beat”, [0132]).
Regarding claim 5, Yuen discloses generating at least one of visual feedback or auditory feedback associated with the activity; and providing the at least one of the visual feedback or the auditory feedback to the user (“In lieu of or in combination with stair steps, altitude gain, etc., the portable monitoring device may also calculate metrics (for example, motivational metrics) and/or calculate the state of avatars (for example, a digital "pet", a graphical representation of the user or his/her alter ego, a game character, or physical object that glows and/or changes physical configuration) that are partially or completely determined by user altitude changes. For example, the device may calculate (and, in addition, may display to the user) "elevation points", where one elevation point is representative of a change in altitude, a stair, and/or a flight of stairs (for example, one elevation point is equal to approximately ten feet, or one flight of stairs). A user may then be motivated to increase an elevation point score or total by, for example, traversing more stairs, flights of stairs and/or hills. Moreover, the device may also maintain the state of a virtual avatar, for example, a flower, whose growth and/or health is related to user altitude changes, or a building, whose size and/or growth is related to user altitude changes, or an entity that morphs between states that are indicative of increased or decreased elevation gains such as a stair case, ladder, hill, or mountain, or specific landmarks like the Eiffel Tower, Mt. Everest, and the Moon. Indeed, all games and/or avatars that are controlled in part or wholly by changes in altitude sensor data are intended as embodiments of the present inventions”, [0156]).
Regarding claim 6, Yuen discloses the set of threshold criteria further comprises at least one threshold criteria derived from an ideal zone, wherein the ideal zone corresponds to a plurality of users without being specific to the user ([0066], [0076]).
Regarding claim 8, Yuen discloses at least a portion of the set of threshold criteria is based at least in part on one or more of historic data associated with the user, a planned threshold for the user, or the maximum threshold of the user (“The data and parameters derived by the portable monitoring device may be transferred, displayed, and/or modified remotely as in, for example, a computer program or website such as www.fitbit.com. Such content may furthermore be modified by the remote application and transferred back to the device for storage and display. For example, the user may adjust information regarding one or more physiological parameters that effect metabolism, which in turn are used to correct calorie burn estimates on the portable monitoring device. Likewise, the user may adjust information regarding height, step length, the intensity of a workout, the type of activity over a particular time duration (e.g., walking, running, weight lifting, driving or riding in an automobile, etc.) and this information may be used to adjust estimates of calorie burn, distance traveled, speed, avatar state, and other activity-related metrics stored and/or displayed on the portable monitoring device”, [0209]).
Claims 10-13, 15, 17 and 18 are directed to systems that implement the methods of claims 1, 2, 4, 5, 8, 6 and 3 respectively and are rejected for the same reasons as claims 1, 2, 4, 5, 8, 6 and 3 respectively.
Claims 19-24 are directed to an article of manufacture containing code that implements the methods of claims 1, 2, 4, 8, 6 and 3 respectively and are rejected for the same reasons as claims 1, 2, 4, 8, 6 and 3 respectively.
Claims 25 and 26 is/are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Yuen et al. (pub. no. 20120084054) in view of Jallon (pub. no. 20120078594).
Regarding claim 25, Yuen discloses a method comprising: collecting, during a first time period, first performance data associated with an activity of a user; determining, based on the first performance data, a first effort associated with the user during the first time period based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the first time period, or a step rate associated with the user associated with the user during the first time period ([0127]);
determining, based on the first performance data, a first resistance experienced by the user during the first time period, wherein the first resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; determining the first effort satisfies a first condition associated with a first effort threshold zone of a set of effort threshold zones; determining the first resistance satisfies a second condition associated with a first resistance threshold zone of a set of effort threshold zones; classifying, based on the first effort threshold zone and the first resistance threshold zone, a first segment of the activity as a first activity type of a set of activity types ([0128]);
collecting, during a second time period, second performance data relating to the activity performed by a user; determining, based on the second performance data, a second effort associated with the user during the second time period based on at least one of electrocardiogram heart rate data associated with the user, a power associated with the user, a speed associated with the user during the second time period, or a step rate associated with the user associated with the user during the second time period; determining, based on the second performance data, a second resistance experienced by the user during the second time period, wherein the second resistance comprises at least one of step rate, stride rate, stroke rate, cadence, or terrain; determining the second effort satisfies a second condition associated with a second effort threshold zone of the set of effort threshold zones; determining the first resistance satisfies a second condition associated with a second resistance threshold zone of a set of effort threshold zones; classifying, based on the second effort threshold zone and the second resistance threshold zone, a second segment of the activity as a second activity type of the set of activity types ([0131], [0179]).
Regarding claims 25 and 26 it is noted that the Yuen does not disclose generating a graph that indicate activity types and associating the activity type with effort or resistance. Jallon however, teaches generating a graph indicating activity types and associating the activity type with effort or resistance ([0059] & [0060]).
Exemplary rationales that may support a conclusion of obviousness include combining prior art elements according to known methods to yield predictable results. Here both the Yuen and Jallon are directed methods of analyzing activity data. To add a graph that indicates activity type as taught by Jallon to the Yuen would be to combine a prior art element according to a known method to yield a predictable result. Therefore, it would have been obvious to a person having ordinary skill in the art as of the effective filing date of the claimed inventio to modify the Yuen to include the Jallon graph indicating activity type. To do so would express activity classification in an intuitive manner thereby increasing the perceived value of the method.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAWRENCE STEFAN GALKA whose telephone number is (571)270-1386. The examiner can normally be reached M-F 6-9 & 12-5.
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/LAWRENCE S GALKA/Primary Examiner, Art Unit 3715
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