DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed 2/06/2026 has been entered. Claims 1 - 20 are pending.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10, 11, and 14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In regard to claims 10, line 1 recites, “the forecasted performance”. However, it is unclear if “the forecasted performance” is referring to the “performance forecast” introduced in claim 1 or if “the forecasted performance” is a separate component. Consistent language should be used to improve the clarity of the claim. Additionally, “the forecasted performance,” lacks antecedent basis. Claim 11 is rejected under the same premise as claim 10 in regard to “the forecasted performance” and by virtue of dependence on claim 10.
In regard to claim 14, line 2 recites, “the mobile or wearable device,” which also lacks antecedent basis.
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.
Claims 1, 2, 7 - 13, and 16 - 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Morlock (US 20140303892 A1 - cited by applicant).
In regard to claims 1 & 12, Morlock discloses a method and system comprising:
obtaining, with at least one processor of a mobile or wearable device, personal prior assessment information associated with a user, the personal prior assessment data including at least one of walking speed, step length, double support time, or walking asymmetry; Morlock discloses a method of generating a route suggestion based on parameters of a user (FIG. 5) that includes obtaining personal prior assessment information, such as age and gender (paragraph [0079]) as well as past sensor data relating to a user’s past activity (paragraph [0040]) which includes speed data collected from movement probe data (paragraph [0046]), such as speed of travel (paragraph [0039]). One of ordinary skill in the art would recognize that “speed of travel” would be understood to be generally commensurate in scope with “walking speed” as the movement monitored by Morlock includes walking, jogging, running, or any other movements carried out by the user’s own power (paragraph [0010]). Morlock further discloses the use of a processor to carry out all methods (paragraph [0108]), wherein the device is a mobile device arranged to be carried by a user, such as a smart watch (paragraph [0032]).
obtaining, with the at least one processor, historical performance information for a previous activity associated with the user or other users; Morlock discloses that an ability profile of a user is uploaded and utilized by the system to make recommendations to a user (paragraph [0038]). The ability profile includes data for individual users including sensed data relating to the user’s historic performance (paragraph [0040]).
obtaining, with the at least one processor, activity assessment information associated with a current activity; Morlock discloses that the method includes acquiring environmental data about the activity performed, including the surface of the trail and weather data (paragraph [0048]).
inputting, with the at least one processor, the personal assessment information, historical performance information and the activity assessment information into a machine learning model. Morlock further discloses that a machine learning model (paragraphs [0047] & [0146] - [0149]) is used to calculate a cost associated with traversing a trail segment (paragraph [0012]). The calculated cost associated with a trail segment is calculated using the ability profile entered by the user or generated based on sensor data that includes the physical characteristics of the user, fitness level of the user, equipment type of the user, and environmental data (paragraphs [0037] - [0040], [0178]). Morlock additionally discloses that the machine learning model generates a fitness profile to develop a functional relationship between the personal assessment information, historical performance information and the activity assessment information input to the machine learning model (paragraph [0086]) in the form of the sensor data that includes the physical characteristics of the user, fitness level of the user, equipment type of the user, and environmental data (paragraphs [0037] - [0040], [0178])
predicting, with the machine learning model, a performance score for the current activity by the user. Morlock further discloses that a machine learning model (paragraphs [0047] & [0146] - [0149]) is used to calculate a cost associated with traversing a trail segment (paragraph [0012]). Examiner notes that this interpretation for performance score as a rating of difficulty in terms of a calculated cost associated with a user traversing a segment of trail is consistent with the description of the invention as put forth in paragraph [0032] of the specification, which states that “the performance forecast can be in the form of a text description and/or a metric. For example, the user can be given a performance score for the proposed route, where the score is personalized to the user”.
And presenting, with the at least one processor, a performance forecast to the user based on the performance score. Morlock discloses that the method and apparatus present a performance forecast in the form of a suggested route through a network of segments for the individual user where the cost data generated by the machine learning model is used to generate a route that meets a given level or exertion range specified by a user or which is deemed suitable based on the assessment of the personal assessment information, historical performance information and the activity assessment information input to the machine learning model (paragraphs [0237] - [0238]).
Morlock further discloses that the system includes:
at least one processor (paragraph [0108])
memory storing instruction that when executed by the at least one processor, cause the at least one processor to perform operations to carry out the method outlined above (paragraph [0185]).
In regard to claims 2 and 13, Morlock discloses the invention as set forth for claims 1 & 12 above, wherein the personal prior assessment information includes health or fitness information computed from sensor data provided by one or more sensors of the mobile or wearable device. Morlock discloses that physical exertion data indicative of one or more measures of the physical exertion of the user is obtained from one or more sensors associated with the mobile or wearable device, where the sensors are located within a main housing of the device (paragraph [0034]). Measurements can include heart rate, pulse, blood oxygen content, Borg rating of perceived exertion, and CO2 blood saturation (paragraph [0036]).
In regard to claims 7 and 18, Morlock discloses the invention as set forth for claims 1 and 12 above, wherein the historical performance information includes at least one of heart rate, respiratory rate, body temperature, galvanic skin response, muscle activity, or user survey data. Morlock discloses that the historical performance information includes heart rate data, including maximal heart rate or any other heart rate values (paragraph [0036]).
In regard to claims 8 and 19, Morlock discloses the invention as set forth for claims 1 and 12 above, wherein the current activity is one of walking, running, jogging, cycling, strolling, or hiking. Morlock discloses that their system and method is directed towards the forecasting of a user’s ability to perform an activity on a segment of trail, where the activity includes running or hiking (paragraph [0072]).
In regard to claims 9 and 20, Morlock discloses the invention as set forth for claims 1 and 12 above, wherein the activity assessment information includes at least one of route or trail surface conditions, elevation, grade, weather conditions, sun exposure, vistas, availability of accommodations, or traffic density. Morlock discloses that the activity assessment information includes obtaining information about the surface type for at least a portion of the path traversed by the user and weather conditions for the geographical region (paragraph [0053]). The activity assessment information can additionally include information on the trail segment geography and characteristics, such as elevation (paragraph [0074]).
In regard to claim 10, Morlock discloses the invention as set forth for claim 1 above, wherein the forecasted performance is based on inferences drawn from similar activities performed by the user or other users. Morlock discloses that a comparison between the user and other user statistics for a given trail segment can be used in developing the user’s ability profile (paragraphs [0038] & [0210]), which is further used to forecast performance of a user on a trail segment.
In regard to claim 11, Morlock discloses the invention as set forth for claim 10 above, wherein the forecasted performance includes a description of how the user may feel during or after completion of the current activity. One of ordinary skill in the art would recognize that the difficulty score assigned to the trail segment suggested by the method disclosed by Morlock would be descriptive of how a user may feel during or after completion of the current activity in terms of fatigue or effort. For instance, a user would recognize that a higher score indicating a higher level of difficulty would result in a greater feeling of fatigue or effort during the activity then a lower score indicating a lower level of difficulty. As stated in paragraph [0033] of the specification, some examples of the performance forecast include if a user will feel comfortable, tired, or over-exerted after performing the activity which the method and system disclosed by Morlock addresses by indicating difficulty levels.
In regard to claim 16, Morlock discloses the invention as set forth for claim 12 above, wherein the personal prior assessment information includes a description of the user's age and one or more physical characteristics of the user. Morlock discloses that the personal prior assessment information includes age (paragraph [0079]) and other physical characteristics including gender (paragraph [0079]).
In regard to claim 17, Morlock discloses the invention as set forth for claim 12 above, wherein the personal prior assessment information includes a description of at least one of apparel, footwear, mobility aids, or items worn or carried by the user. Morlock specifically discloses that the personal prior assessment information includes an equipment profile that includes questions about running shoes, clothing, and other types of gear (paragraph 0214]).
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.
Claims 3, 5, 6, & 14 are rejected under 35 U.S.C. 103 as being unpatentable over Morlock (US 20140303892 A1 - cited by applicant) as applied to claim 1 above, and further in view of Futrell (US 20230211206 A1).
In regard to claims 3 and 14, Morlock discloses the invention as set forth for claim 1 and 12 above, wherein the personal prior assessment information is obtained from user input. Morlock further discloses that the ability profile, which is built from personal prior assessment information, is obtained by having the user answer a series of questions to establish an ability profile in addition to sensed data from the device associated with the user (paragraph [0040]). While Morlock discloses that user input is utilized to generate the ability profile and that the ability profile of the user may be obtained in any suitable manner (paragraph [0040]), they do not explicitly disclose that the personal prior assessment information is obtained from user input through a user interface of the mobile or wearable device.
However, Futrell teaches a wearable electronic device for stamina determination and prediction that includes a user interface (paragraph [0031]; FIG. 1, component 104) where a user may input data and commands to the device (paragraph [0031]).
It would have been obvious to one of ordinary skill in the art to have modified the method and system disclosed by Morlock with the teaching of Futrell that a user can enter data directly to the mobile device using a user interface because Morlock already discloses that the device can be a smart watch, like that taught by Futrell, and that the ability profile of the user may be obtained in any suitable manner (Morlock, paragraph [0040]), which would include entering the data via a user interface as taught by Futrell.
In regard to claim 5, Morlock discloses the invention as set forth for claim 3 above, wherein the personal prior assessment information includes a description of the user's age and one or more physical characteristics of the user. Morlock discloses that the personal prior assessment information includes age (paragraph [0079]) and other physical characteristics including gender (paragraph [0079]).
In regard to claim 6, Morlock discloses the invention as set forth for claim 3 above, wherein the personal prior assessment information includes a description of at least one of apparel, footwear, mobility aids, or items worn or carried by the user. Morlock specifically discloses that the personal prior assessment information includes an equipment profile that includes questions about running shoes, clothing, and other types of gear (paragraph 0214]).
Claims 4 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Morlock (US 20140303892 A1 - Cited by Applicant) as applied to claim 1 above, and further in view of Pacione (US 20140221791 A1).
In regard to claims 4 and 15, Morlock discloses the invention as set forth for claim 1 and 12 above. While Morlock discloses the use of personal prior assessment information to determine an appropriate level of difficulty of a route (paragraph [0054]) and that the personal prior assessment information can include one or more factors affecting the ability of the individual to traverse one or more navigable segments and that the user can establish an ability profile by entering a series of answers to questions asked by the system, they do not specify that the personal prior assessment information includes mental wellbeing information obtained from user input.
However, Pacione teaches a wellness and fitness monitoring system and method that takes a combination of information collected from the apparatus and information entered by the user to provide predictive feedback to a user and provide recommendations for reaching dietary goals, such as recommendations on exercise programs (paragraphs [0021]; paragraph [0036]). In addition to using physiological measurements to determine predictive feedback (paragraph [0022]), the monitoring system also allows a user to enter a score indicating their mental wellbeing that day (FIG. 5, component 156f). The user provides a rating, preferably on a scale of 1 to 5, with respect to the following nine subject areas: mental sharpness; emotional and psychological wellbeing; energy level; ability to cope with life stresses; appearance; physical wellbeing; self-control; motivation; and comfort in relating to others (paragraph [0146]).
It would have been obvious to one of ordinary skill in that art prior to the effective filing date of the claimed invention to have modified the method and system disclosed by Morlock which uses a variety of personal prior assessment information along with other information to forecast the performance of a user on a trail segment with the teaching of Pacione that personal prior assessment information can include user entered assessments on mental wellbeing because it would be considered combining prior art elements, in this case the questions asked of a user to establish an ability profile, according to known methods to yield the predictable result of using personal prior assessment information to make a prediction about a user’s ability to perform an activity or task.
Response to Arguments
Applicant's arguments filed 2/06/2026, see Remarks, in regard to the rejection of claims 13 and 14 under 35 U.S.C. 112(b) have been fully considered and are partially persuasive. The rejection of claim 13 has been withdrawn. In regard to the rejection of claim 14 under 35 U.S.C. 112(b) issued in the non-final rejection mailed on 11/10/2025, Examiner acknowledges that the lack of antecedent basis of “the user input,” was updated in the amendment filed 2/06/2026. However, “the mobile or wearable device” in claim 14 still lacks antecedent basis.
Applicant's arguments filed 2/06/2026, see Remarks, in regard to the rejection of claims 1 - 20 under 35 U.S.C. 101 have been fully considered and are persuasive. The amendment includes the use of the positively claimed machine learning model that is utilized to predict a performance score for the current activity. As such, the claim language differentiates itself from a mental process as inputting data to a machine learning model to generate a result cannot be practically performed within the human mind. The rejection of claims 1 - 20 under 35 U.S.C. 101 have been withdrawn.
Applicant's arguments filed 2/06/2026, see Remarks, in regard to the rejection of claims 1, 2, 7 - 13, and 16 - 20 under 35 U.S.C. 102 and the rejection of claims 3 - 6, and 14 - 15 under 35 U.S.C. 103 have been fully considered and are not persuasive. Applicant argues that Morlock fails to disclose that “obtaining… personal prior assessment information associated with a user, the personal prior assessment data including at least one of walking speed, step length, double support time, or walking asymmetry…” However, Morlock discloses that previous motion data relating to a user’s past activity (paragraph [0040]) which includes speed data collected from movement probe data (paragraph [0046]), such as speed of travel (paragraph [0039]), is obtained and input into to the machine learning model to generate a performance score. As stated in the updated 35 U.S.C. 102 rejection of claims 1 and 12 above, one of ordinary skill in the art would recognize that “speed of travel” would be commensurate in scope with “walking speed”.
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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/ERIC F WINAKUR/Primary Examiner, Art Unit 3791
/S.C.P./Examiner, Art Unit 3791