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 .
Claims 1-16, 24-25, 28-42 and 48-51 have been presented for examination.
Claims 17-23, 26-27 and 43-47 have been cancelled.
Claim Objections
Claim50 is objected to because of the following informalities: The claim states “… according to any one of claim 1”. This should be corrected to recite “according to claim 1”. Appropriate correction is required.
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.
Claim(s) 1-2, 24-25, 28, 34, 36-38 and 48-49 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reiner US Pat. No. 10,614,388 in view of Marsden PGPUB 2005/0199752.
Referring to claim 1, Reiner teaches the system comprising:
an obtaining processor adapted to obtain one or more user factors indicative of a user state [claim 1].
an estimation processor adapted to identify a two-operation correlation between the obtained one or more user factors indicative of the user state and at least a first feedback action, the feedback action being expected to alter the user state as indicated at least in part by the one or more user factors [col. 13 lines 53-61, claims 8-9].
A feedback processor adapted to cause a modification of the one or more operations of at least one device of the delivery ecosystem according to at least a first feedback action identified by the estimation processor.
In summary, Reiner teaches a workflow system which monitors a user’s stress levels and in response, adjusts an interventional device such as an aromatherapy device in effort to calm and relax the user if it is determined that their stress level exceeded a threshold.
While Reiner teaches the invention substantially as claimed above, it is not explicitly taught that the aromatherapy is an aerosol delivery device that uses a heater to release compounds into the air. Marsden teaches an aerosol aromatherapy device which vaporizes an essential oil using a heating element to aerially disperse the substance [0003, 0005]. It would have been obvious to one of ordinary skill in the art before the effective filing date to use the aerosol device taught in Marsden in the Reiner system because Reiner requires an aromatherapy device and Marsden teaches such a device that could be used to provide the necessary aromatherapy. It is interpreted that in the Reiner-Marsden combination, that the user of the workflow device would also be a user of the aromatherapy device since such is part of the workflow device.
Referring to claim 2, Reiner teaches a first correlation including a user factor such as blood pressure or speech analysis (user factors) which relates to stress/fatigue (user state) [col. 3 lines 18-26]. The stress/fatigue level (user state) corresponds to control of an intervention device (feedback action) [col. 13 lines 53-64, claims 8-9].
Referring to claim 24, Reiner teaches the first physical property can be blood pressure [col. 3 lines 22-26].
Referring to claim 25, Reiner teaches the user factors (blood pressure/speech) relate to how intervention occurs according to user preferences (historical data providing background information relating to the user) or compared to other users with similar profiles (contextual data relating to the user) [cols. 13-14 lines 65-12]. In addition, it is further taught that the stress and fatigue levels can be caused by a working environment (environmental data relating to the user) [col. 11 lines 55-61].
Referring to claim 28, Reiner teaches controlling aromatherapy (aerosol delivery) as the intervening device [col. 13 lines 53-61 and claims 1, 9].
Referring to claim 34, Reiner teaches that the system not only includes aromatherapy (aerosol device) but also blood pressure monitors (wearable device) [col. 3 lines 22-26].
Referring to claim 36, Reiner suggests processor (106) is responsible for the operations of the estimating, obtaining and feedback processors found in claim 1. In particular, the processor in claim 1 teach the operations performed by the above processors. In addition, claim 1 includes the components found in the client computer in Fig. 1 which includes processor (106) [cols. 5-6 lines 21-31].
Referring to claims 37-38 and 48-49, these are rejected on the same basis as set forth hereinabove. Reiner teaches the system and therefore teaches the method, computer system and program performing the same.
Claim(s) 3-6, 8-9, 29-30, 32-33, 35-36, 39-40 and 50-51 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reiner and Marsden as applied to claims 1-2, 24-25, 28, 34, 36-38 and 48-49 above, and further in view of Addison1.
Referring to claim 3, while Reiner and Marsden teach the invention substantially as claimed above, it is not further taught to estimate a user state based upon a model comprising correlation between the factors and user states. Instead, Reiner includes predefined thresholds with which user factors are compared against to determine intervention measures. Addison teaches identifying a state of a user but does so by using a model to correlate user factors with user states [0055]. It would have been obvious to one of ordinary skill in the art before the effective filing date to try modifying the Reiner-Marsden combination to include a model to correlate the user factors (blood pressure, voice) to the stress/fatigue level because Addison implies that patients are different and their physiological parameters can vary from person to person under different circumstances thus requiring a individual analysis [0044,0055].
While the examiner acknowledges that Addison is concerned with a different user state and different user factors, there is still a strong teaching that there is a direct correlation between user states and user factors and application of a substance to affect user state. Thus, one would have reason to try incorporating Addison into systems dealing with similar types of relationships like that in Reiner.
Referring to claims 4-5, Addison teaches estimating and outputting a sedation level using a heuristic approach based on the physiological parameters using a model (i.e., machine learning) to control the amount of sedative [abstract, 0055].
Referring to claim 6, Addison teaches analyzing two or more physiological parameters which are eventually used for machine learning purposes (i.e. training and implementation) [0053, 0071]. In addition, Reiner also teaches evaluating two or more physiological parameters [col. 5 lines 1-6].
Referring to claim 8, Addison teaches further assessing a patient using an RAS or SAS score [0017, 0056] versus monitoring tidal volume, respiratory rate, etc.… [0058]. This is interpreted as via a separate analysis of user factors in that they are compared against assessment scales.
Referring to claim 9, Addison teaches training the machine learning model using two or more physiological parameters [0053].
Referring to claims 29-30, Addison teaches displaying user state (sedation level) and notify how to control the delivery system (how much sedative to administer) [Fig. 9 and 0061, 0065].
Referring to claims 32-33, Addison teaches causing the amount of sedative to be administered or to prompt the user of the amount of sedative to be administered [0065].
Referring to claims 35-36, Addison also teaches at least one of the processors being provided at least in part also within one or more devices of the delivery system but also by a remote server [Fig. 2 and 0049].
Referring to claims 39-40, these are rejected on the same basis as set forth hereinabove.
Referring to claims 50-51, Reiner further teaches the user being able to select the option [cols. 13-14 lines 13-19] between more than one feedback options [cols. 13-14 lines 53-12]. Addison allows for automatic or manual administering [0065]. Therefore, it is interpreted that in the Reiner-Marsden-Addison, that the feedback option (i.e. temperature change, lighting, aromatherapy, music, etc… can be automatically or manually implemented.
Claim(s) 10-13, 15-16 and 41-42 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reiner, Marsden and Addison as applied to claims 1-6, 8-9, 24-25, 28-30, 32-40 and 48-51 above, and further in view of Brown2.
Referring to claim 10, while the Reiner-Marsden-Addison combination teaches the invention substantially as claimed above, it is not explicitly taught to model a correlation between the user state(s) and feedback action(s). Rather, the combination (i.e. specifically Addison) teaches only modeling the correlation between user factors and user state(s). Brown teaches that feedback actions (i.e. dosing amount) can be learned based on physiological parameters [0009]. While a physiological state is akin to the claimed user factors, Addison teaches the user factors correlate to the user state and is determined using machine learning [0055]. It should be apparent that all three (user factors, user state and feedback) all have a relationship with one another. Due to the ability of machine learning/neural networks to model the relationship between user factor/user state and user factor/feedback, it would have been obvious to try using machine learning/neural networks to model the relationship between user state and feedback because there is a reasonable expectation of success. In addition, it would have been obvious to one of ordinary skill in the art to incorporate a model to correlate the user state with feedback actions because doing so would allow for the Reiner-Marsden-Addison combination to learn how to the aromatherapy based on the determined user state and a person of ordinary skill has good reason to pursue the known options within his or her technical grasp.
Referring to claim 11, both Addison and Brown teach using heuristic approaches [Addison: 0055; Brown: 0009].
Referring to claim 12, Addison and Brown teach a dosing to be administered as the feedback action [Addison: 0065; Brown: 0009].
Referring to claim 13, Addison teaches training the machine learning model using two or more physiological parameters [0053].
Referring to claim 15, Addison teaches the user state (sedation level) involves analyzing two or more physiological parameters [0053].
Referring to claim 16, Addison teaches determining an amount to administer [0065].
Referring to claims 41-42, these are rejected on the same basis as set forth hereinabove.
Claim(s) 7 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reiner, Marsden, Addison and Brown as applied to claims 1-6, 8-13, 15-16, 24-25, 28-30, 32-42 and 48-51 above, and further in view of Rodziewicz3.
Referring to claim 7, while the Reiner-Marsden-Addison-Brown combination teach the invention substantially as claimed above, it is not taught that the machine learning model/neural network is trained on self-reported information. Rather, Addison is concerned with using a learning model for administering a dosage to a patient who is presumably sedated. Rodziewicz teaches a similar system wherein dosage can be determined using an almost identical methodology [0051]. Rodziewicz further teaches that the model for determining dosage can further include patient feedback (i.e., self-reported) [0051]. It would have been obvious to one of ordinary skill in the art before the effective filing date to allow for patient feedback in the Reiner-Marsden-Addison-Brown combination because doing so would allow for usage in other non-sedative related medication dosing while also improving accuracy by receiving input directly from the user.
Referring to claim 14, this is rejected on the same basis as set forth hereinabove.
Claim(s) 31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reiner, Marsden and Addison as applied to claims 1-6, 8-13, 15-16, 24-25, 28-30, 32-42 and 48-51, and further in view of Kilger4.
Referring to claim 31, while the Reiner-Marsden-Addison combination teaches the invention substantially as claimed above, it is not explicitly taught that feedback implementation is responsive to availability of respective devices for implementing those feedback actions. Kilger teaches a similar system wherein dosage (i.e., cannabis or nicotine) can be determined using an almost identical methodology. Specifically, Kilger teaches monitoring a user’s physiological state and administering the dosage in response while also incorporating artificial intelligence/machine learning for determining the dosage to administer [0045-0046, 0109, 0115-0119]. In addition, Kilger further teaches a verification step to lock/unlock the administering device or portions thereof for administering the medication [0055, 0211]. It would have been obvious to one of ordinary skill in the art before the effective filing date to include the teachings of Kilger into the Reiner-Marsden-Addison combination because doing so would allow for usage in other types of calming aerosols (nicotine and cannabis) [0001] while preventing usage by those who are not authorized [0211].
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-16, 24-25, 28-42 and 48-51 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.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARK A CONNOLLY whose telephone number is (571)272-3666. The examiner can normally be reached Monday-Friday 9am-5pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached at 571-272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MARK A CONNOLLY/Primary Examiner, Art Unit 2115 3/27/26
1 Cited in the previous office action.
2 Cited in the previous office action.
3 Cited in the previous office action.
4 Cited in the previous office action