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 .
DETAILED ACTION
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.
Claim 31 is 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.
The at least on biosensor is indefinite. It appears the “on” should be “one”. Correction is required.
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 1-11, 13, 15-20, 23-29, 31, 32 and 35-38 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Al-Ali et al (US 2022/0296161).
Regarding claim 1, Al-Ali discloses a system for monitoring one or more addictive activities by an addict, the system comprising:
at least one biosensor 102 configured to measure physiological data from the addict;
a processor 110 configured to generate a notification when the addict has participated in the one or more addictive activities based on the physiological data, see paragraphs [0104] and [0105]; and
a communication system comprising 126 and 128 configured to send the notification to one or more devices of the addict and/or of members of an addiction support network of the addict to notify that the addict has participated in the addictive activities, see FIG. 1C.
Regarding claim 2, Al-Ali discloses the at least one biosensor 102 is attached to the addict, see paragraph [0116].
Regarding claim 3, Al-Ali discloses the at least one biosensor 102 is combined into a housing and attached to the addict, see paragraph [0116].
Regarding claim 4, Al-Ali discloses the at least one biosensor 102 is contained in a band-mounted wearable device that is worn by the addict, see paragraph [0116].
Regarding claim 5, Al-Ali discloses the at least one biosensor is contained in an adhesive-based wearable device that is attached to the addict, see paragraph [0117].
Regarding claim 6, Al-Ali discloses the at least one biosensor 102 is configured to transmit biosensor data of the addict to the processor 110 via wireless communication or wired communication, see paragraph [0114].
Regarding claim 7, Al-Ali discloses the processor 110 is configured to process the biosensor data received from the at least one biosensor 102 to identify and characterize artifacts, to extract candidate features for classification and storage and/or to compare to previously acquired candidate features, and to generate a report see paragraphs [0114] and [0127].
Regarding claim 8, Al-Ali discloses the processor 110 is configured to determine if the addict has participated in one or more addictive activities, see paragraphs [0038] and [0104].
Regarding claim 9, Al-Ali discloses the processor 110 is configured to determine if the addict has signs of withdrawal or addictions, see paragraph [0108].
Regarding claim 10, Al-Ali discloses the processor 110 is configured to determine if the addict has urges for the one or more addictive activities, see paragraph [0108].
Regarding claim 11, Al-Ali discloses the processor 110 is configured to determine if the addict is compliant with a prescription, see FIG. 16A and FIG. 16B and paragraphs [0255], [0256] and [0257].
Regarding claim 13, Al-Ali discloses the processor 110 is configured to determine if the addict is experiencing adverse events from participating in the one or more addictive activities, see paragraphs [0122] and [0123].
Regarding claim 15, Al-Ali discloses the processor 110 is configured to determine whether to send the biosensor data to members of the addiction support network of the addict, and sends the biosensor data to the one or more devices of the members of the addiction support network upon determining to send the biosensor data to the members of the addiction support network, see FIG. 3A, FIG. 3B and FIG. 3C and paragraphs [0173] and [0176].
Regarding claim 16, Al-Ali discloses a wearable device containing the at least one biosensor 102, the wearable device being worn by the addict, wherein the processor 110 is configured to display the notification on the wearable device and/or transmit the notification to members of the addiction support network, see paragraph [0100], [0116] and [0132].
Regarding claim 17, Al-Ali discloses the communication system is configured to communicate with an artificial intelligence-driven human-like avatar or bot, the examiner is interpreting the human-like avatar or bot to be an intended use limitation capable of being performed using the artificial intelligence program disclosed in Al-Ali, see paragraph [0330].
Regarding claim 18, Al-Ali discloses the processor 110 is configured to automatically determine when a parameter 118 of the addict from the at least one biosensor 102 is out of range due to participation in addictive activities, and automatically establish, via the communication system, uni-directional or bi-directional communication with the addict to send the notification, see paragraphs [0158] to [0160] and [0206].
Regarding claim 19, Al-Ali discloses the processor 110 is configured to initiate auto-injection of antidote substances to counter consumption of addictive substances by the addict, see paragraph [0241] and FIG. 9C.
Regarding claim 20, Al-Ali discloses the processor 110 is configured to monitor physiological parameters in the physiological data in a time series analysis using at least one of logistic regression/classification, discriminant analysis, tree-based methods, fuzzy logic, genetic algorithms, or machine learning, see paragraph [0330] and FIG. 9C.
Regarding claim 23, Al-Ali discloses the at least one biosensor 110 is configured to record the physiological data, see paragraph [0114].
Regarding claim 24, Al-Ali discloses the processor 110 is configured to analyze the physiological data and determine when the addict has participated in the one or more addictive activities, see paragraph [0158].
Regarding claim 25, Al-Ali discloses the processor 110 is configured to analyze the physiological data in real-time, see paragraph [0182].
Regarding claim 26, Al-Ali discloses the notification is an alarm or an alert, see paragraph [0103].
Regarding claim 27, Al-Ali discloses the notification enables the addict or the members of the addiction support network to intervene and/or prevent the addict from participating in the one or more addictive activities, see paragraph [0168].
Regarding claim 28, Al-Ali discloses the processor 110 is a virtual sobriety partner for the addict, and the processor is configured to communicate with either a human or an artificial intelligence-based engine, see paragraph [0330].
Regarding claim 29, Al-Ali discloses the processor 110 is configured to intervene with the addict to prevent or minimize participation in the one or more addictive activities, see paragraph [0108].
Regarding claim 31, Al-Ali discloses a mobile system containing the at least on biosensor, wherein the processor 1802 is configured to notify, via the communication system, the addict and/or an addiction support network of the addict that the mobile system is not being worn by the addict based on the physiological data, see paragraph [0291] and FIG. 18A13.
Regarding claim 32, Al-Ali discloses a system for providing a virtual sobriety partner for an addict, the system comprising:
at least one biosensor 102 configured to measure physiological data from the addict;
and a processor 110 configured to communicate with one or more devices of either a human or an artificial intelligence-based engine to notify the human or the artificial intelligence-based engine that the addict has participated in one or more addictive activities based on the physiological data, see paragraphs [0100], [0108] and [0330].
Regarding claim 35, Al-Ali discloses the processor 110 is configured to analyze the physiological data comprising parameters 118, and determine when the addict has participated in one or more addictive activities based on the physiological data, see paragraph [0158].
Regarding claim 36, Al-Ali discloses the processor 110 is configured to analyze the physiological data in real-time, see paragraph [0182].
Regarding claim 37, Al-Ali discloses the processor 110 is configured to intervene with the addict to prevent or minimize participation in the addictive activities, see paragraph [0108].
Regarding claim 38, Al-Ali discloses the at least one biosensor 102 is configured to the physiological data, see paragraphs [0111] and [0114].
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 12, 14, 21, 22, 30, 33, 34 and 39-53 are rejected under 35 U.S.C. 103 as being unpatentable over Al-Ali et al (US 2022/0296161) in view of Williams et al (US 2022/0116736).
Regarding claim 12, Al-Ali does not disclose the processor 110 is configured to determine if the addict is exhibiting signs of detoxification or withdrawal of the one or more addictive activities.
Williams teaches it is desirable to detect early warning signs of an eventual medical situation of asymptomatic patients, see paragraph [0502].
One of ordinary skill in the art would have found it obvious to configure the processor 110 to determine if the addict is exhibiting signs of detoxification or withdrawal of the one or more addictive activities because the activities eventually will need medical attention or intervention if the activities continue.
Regarding claim 14, Al-Ali does not disclose the processor 110 is configured to determine if the addict is engaged in a secondary support associated activity.
Williams teaches it is desirable to detect early engagement in activities, see paragraph [0488].
One of ordinary skill in the art would have found it obvious to configure the processor 110 to determine if the addict is engaged in a secondary support associated activity because Williams suggests combining early detection by using secondary support activities of triggers or contexts.
Regarding claim 21, Al-Ali does not disclose the processor 110 is configured to disable heavy machinery, cars, planes, trains, boats, or dangerous equipment around the addict if the addict has participated in one or more addictive activities.
Williams teaches deactivating driving capabilities using addict-related sensors, see paragraph [0101].
One of ordinary skill in the art would have found it obvious to configure the processor 110 to disable heavy machinery, cars, planes, trains, boats, or dangerous equipment around the addict if the addict has participated in one or more addictive activities to prevent usage as suggested by Williams.
Regarding claim 22, Al-Ali does not disclose the processor 110 is configured to determine whether the addict is unfit for duty if the addict has participated in one or more addictive activities, and notify, via the communication system, members of the addiction support network that the addict is unfit for duty.
Williams teaches using addict-related sensors and networks 295 to access people or groups to prevent or mitigate high relapse risk situations, see paragraph [0102].
One of ordinary skill in the art would have found it obvious to configure the processor 110 to determine whether the addict is unfit for duty if the addict has participated in one or more addictive activities, and notify, via the communication system, members of the addiction support network that the addict is unfit for duty because Williams suggest such a configuration prevents or mitigates relapse.
Regarding claim 30, Al-Ali does not disclose at least one geographical location sensor that is configured to measure geographical location or proximity data of the addict, and the processor 110 is configured to notify, via the communication system, the addict that the addict has entered a defined dangerous geographical zone or exited a defined safe geographical zone based on the geographical location or proximity data.
Williams teaches using a locator unit 202 as a geographical location sensor that is configured to measure geographical location or proximity data of the addict, see paragraph [0092].
One of ordinary skill in the art would have found it obvious to configure the processor 110 to notify, via the communication system, the addict that the addict has entered a defined dangerous geographical zone or exited a defined safe geographical zone based on the geographical location or proximity data because the teaching of Williams is directed to this purpose for a similar device having a processor similar to processor 110.
Regarding claim 33, Al-Ali does not disclose the processor 110 is configured to conduct advanced therapy with the addict.
Williams teaches using various types of advanced therapy treatments for the addict, see paragraph [0039].
One of ordinary skill in the art would have found it obvious to configure the processor 110 to conduct advanced therapy with the addict because Williams suggest providing such treatment for an addict.
Regarding claim 34, Al-Ali does not disclose the advanced therapy includes at least one of cognitive-behavioral therapy, talk therapy, self-management and recovery training (SMART) recovery or cost-benefit therapy, or 12-step therapy.
Williams teaches using interventions as a type of advanced therapy treatment for the addict, see paragraph [0039].
One of ordinary skill in the art would have found it obvious to use talk therapy for the advanced therapy treatment because talk therapy includes interventions.
Regarding claim 39, Al-Ali discloses a system for monitoring a risk of participation in one or more addictive activities by an addict using geographical location or proximity data, the system comprising: at least one biosensor 102 configured to measure physiological data 118 from the addict.
Al-Ali does not disclose at least one geographical location sensor configured to measure geographical location or proximity data of the addict.
Williams teaches using a locator unit 202 as a geographical location sensor that is configured to measure geographical location or proximity data of the addict, see paragraph [0092].
One of ordinary skill in the art would have found it obvious to combine the locator unit 202 teaching of Williams with the processor 110 of Al-Ali to generate a notification when the addict has either entered a defined dangerous geographical zone or exited a defined safe geographical zone because the locator unit provides the location information usable with the processor 110 for location information.
Al-Ali discloses a communication system comprising 126 and 128 configured to send the notification to one or more devices of the addict to notify that the addict has entered the defined dangerous geographical zone or exited the defined safe geographical zone.
Regarding claim 40, Al-Ali discloses the processor 110 is configured to send a notification to one or more devices of members of an addiction support network of the addict that the addict has entered the defined dangerous geographical zone or exited the defined safe geographical zone to enable the members of the addiction support network to intervene and minimize the addictive activities by the addict, see paragraph [0038].
Regarding claim 41, Al-Ali discloses the processor 110 is configured to combine the geographical location or proximity data with the physiological data, and notify first responders to intervene and improve health of the addict, see paragraph [0038].
Regarding claim 42, Al-Ali discloses the geographical location sensor is a Global Positioning System sensor (GPS), see paragraph [0306].
Regarding claim 43, Al-Ali discloses the defined dangerous geographical zone and the defined safe geographical zone are user-defined in both space and time, see paragraph [0056].
Regarding claim 44, Al-Ali discloses the defined dangerous geographical zone and the defined safe geographical zone change based on a time of day and/or a spatial proximity for both fixed and moving risks for addictive activities of the addict, see paragraph [0056].
Regarding claim 45, Williams discloses determining whether a place is conducive to participating in addictive activities, see paragraph [0043].
One of ordinary skill in the art would have found it obvious to configure the processor 110 of Al-Ali to determine if the addict is in a place conducive to participating in addictive activities because the teaching of Williams suggests using such a feature as a trigger for intervention.
Regarding claim 46, Al-Ali discloses the processor 110 is configured to transmit geographical location information to one or more devices of members of an addiction support network of the addict to enable the members of the addiction support network to intervene and prevent the addict from participating in the addictive activities, see paragraphs [0098] and [0168].
Regarding claim 47, Williams teaches determining when the addict has either entered the defined dangerous geographical zone or exited the defined safe geographical zone based on the geographical location or proximity data, see paragraph [0122].
Based on this teaching in Williams, one of ordinary skill in the art would have found it desirable to configure the processor 110 in Al-Ali to analyze the geographical location or proximity data, and determine when the addict has either entered the defined dangerous geographical zone or exited the defined safe geographical zone based on the geographical location or proximity data.
Regarding claim 48, Al-Ali discloses the processor 110 is configured to analyze the geographical location or proximity data in real-time, see paragraph [0182].
Regarding claim 49, Al-Ali does not disclose a mobile system for identifying an addict that uses the mobile system to prevent an unauthorized use of the mobile system by another other than the addict.
Williams teaches an anticipated or predicted risk of unauthorized quarantine violation is a desirable consideration for addiction monitoring devices, see paragraph [0461].
One of ordinary skill in the art would have found it desirable based on the teaching in Williams to identify an addict that uses the mobile system to prevent an unauthorized use of the mobile system by another than the addict by configuring the mobile system comprising:
at least one biosensor 102 configured to measure physiological data from the addict; and
a processor 110 configured to send, via a communication system comprising 126 and 128, a notification to one or more devices of the addict and/or of members of an addiction support network of the addict that the mobile system is not being worn by the addict based on the physiological data wherein a processor 1802 is configured to notify, via the communication system, the addict and/or an addiction support network of the addict that the mobile system is not being worn by the addict based on the physiological data, see paragraph [0291] and FIG. 18A13.
Regarding claim 50, Al-Ali discloses the processor 110 is configured to compare the physiological data to baseline measurements, and determine if the mobile system is not being worn by the addict based on the comparison of the physiological data to the baseline measurements, see paragraph [0291] and FIG. 18A13.
Regarding claim 51, Al-Ali discloses the processor 110 is configured to analyze the physiological data, and determine when the mobile system is not being worn by the addict based on the physiological data, see paragraph [0291] and FIG. 18A13.
Regarding claim 52, Al-Ali discloses the processor 110 is configured to analyze the physiological data in real-time, see paragraph [0182].
Regarding claim 53, Al-Ali discloses the processor 110 is configured to communicate with the one or more devices via uni-directional or bi-directional communication to enable intervention and/or restoration of the mobile system on the addict, see paragraph [0136].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to George Manuel whose telephone number is (571) 272-4952.
The examiner can normally be reached on regular business days.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin Klein can be reached on (571) 270-5213. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/George Manuel/
Primary Examiner
Art Unit: 3792
2/3/2026