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
Claims 1 & 3-13 were previously pending in this application. The amendment filed 07 April 2026 has been entered and the following has occurred: Claims 1 & 5 have been amended. Claims 14-15 have been added. No claims have been cancelled.
Claims 1 & 3-15 remain pending in the application.
Claim Analysis - 35 USC § 101
Note: this section of the Office Action is not a rejection, and instead merely represents a step-by-step analysis of the Alice/Mayo framework for determining whether the claims represent patent-eligible subject matter.
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 & 3-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The claims recite subject matter within a statutory category as a machine (claims 1 & 3-15) (Subject Matter Eligibility (SME) Test Step 1: Yes) which recite associated steps of:
a data collection system comprising a first processor coupled to a database and coupled to a multiplicity of patient monitoring devices, wherein
each patient monitoring device of said multiplicity of patient monitoring devices is configured to obtain a time series of patient data samples, said patient data samples comprising vital sign values of one or more associated patient parameters;
receive one or more threshold values;
when said patient data samples are outside said one or more threshold values, generate an alarm; and
transmit alarm data to said first processor, wherein
said alarm data comprises said patient data samples while said alarm is active, wherein
said one or more threshold values comprise an upper threshold and a lower threshold;
said first processor is configured to collect said alarm data from said each patient monitoring data;
generate an alarm summary record associated with said alarm data and store said alarm summary record in said database, wherein
said alarm summary record comprises:
said alarm;
an alarm start time;
an alarm duration;
a minimum value of said patient data samples of said alarm data; and
a maximum value of said patient data samples of said alarm data; and,
an alarm threshold analysis system comprising a second processor coupled to said database, wherein
said second processor is configured to retrieve alarm summary records over a time period from said database; and,
process said alarm summary records and calculate an expected change in a number of alarms over said time period as a function of one or more modified threshold values based on said alarm summary records, wherein
said one or more modified threshold values comprise a modified upper threshold value as a modification to the upper threshold and a modified lower threshold value as a modification to the lower threshold; wherein
the one or more modified threshold values are selected to reduce the number of alarms to a desired level;
determine said one or more modified threshold values based on analysis and extrapolation of alarm-summary records and corresponding patient-data samples;
wherein said calculate said expected change in said number of alarms over said time period comprises eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records, wherein
said alarm summary records are used to evaluate effects of said modified threshold values on said number of alarms over said time period;
evaluate a range of modified threshold values of said one or more modified threshold values for a desired time period to generate a functional relationship between potential modifications to the one or more modified threshold values and a resulting number of alarms;
determine and select a new threshold value of said one or more modified threshold values based on said functional relationship; and
transmit said new threshold value to one or more of said multiplicity of patient monitoring devices to replace one or more of said one or more threshold values that exist in said one or more said multiplicity of patient monitoring devices to reduce the number of alarms to the desired level;
wherein said new threshold value modifies one or more of said upper threshold or said lower threshold used by said one or more of said multiplicity of patient monitoring devices to generate said alarm;
said collect said alarm data, said generate said alarm summary record, said retrieve alarm summary records, said process said alarm summary records, said determine said one or more modified threshold values, and said replace one or more of said one or more threshold values that exist in said one or more of said multiplicity of patient monitoring devices are fully automated to form a closed-loop system that iteratively adjusts device behavior to achieve a desired rate of alarms.
These steps of monitoring one or more patients on one or more patient monitoring devices, receiving one or more threshold values, transmitting an alarm when said patient data samples are outside said one or more threshold values, generating a record of one or more of the transmitted alarms and retrieving said alarm summary record and calculating an expected change in a number of alarms over a future time period based on said received alarm summary record, as drafted, under the broadest reasonable interpretation, includes methods of organizing human activity. That is, the performance of the steps by the system effectively manages the typical behavior of medical staff regarding one or more patients that are being monitored under their care. For instance, said performance of the steps recited relates to human activity at least by monitoring one or more actions and/or physiological data of the patient and potentially generating an alarm and an associated alarm summary record for future management of said patient by the hospital staff. That is, the typical behavior of the hospital staff regarding the issuing of alarms is effectively managed by the system performing the steps recited. Further, while aspects of the threshold values and automated updating thereof via a closed-loop system are specified in the limitations found at the end of the claim, i.e. potentially representing additional limitations, these aspects still fall in line with managing the typical behavior of medical staff regarding one or more patients that are being monitored under their care, but recited for specifically tailoring alarms to certain conditions. This is further supported by the dependent claims reciting actions relating to issuance of one or more alarms, such as editing one or more thresholds for alarm issuance in order to effect the change in a number of alarms over said future period of time. Accordingly, the claim recites an abstract idea.
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 3-15, reciting particular aspects of how determining a new threshold value, classifying an alarm summary record, performing various forms of analysis on said alarm summary record in view of patient physiological data, e.g. clustering analysis, and generating a frequency distribution may be performed but for recitation of generic computer components) (SME Test Step 2A, Prong 1: Yes).
The claims include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements go beyond well-understood, routine, and conventional activity in particular fields, at least by amounting to an inventive concept, such as via improvements to the technical field of patient monitoring by effectively reducing alarm fatigue and/or amounting to an ordered combination that accomplishes said inventive concept, allowing for improvements in the field of interconnected patient monitoring systems. For example, by substantially describing the algorithm regarding collecting alarm data over time, responsiveness to said alarms, determining a functional relationship between adjustment of various patient vital sign thresholds and the resulting effects/change in the number of alarms, and implementing said adjustments into the multiplicity of patient devices to produce a desired level/number of alarms and thereby reducing perceived alarm fatigue between multiple devices in a clinical setting. Furthermore, fully automating the replacement efforts to form a closed-loops system that iteratively adjusts device behavior to achieve a desired rate of alarms represents a meaningful limitation beyond generally linking the use of the judicial exception to a particular technological environment, at least by manipulating the device behavior/configurational settings and output of one or more alarms for a multiplicity of patient monitoring devices. Therefore, the claims represent patent-eligible subject matter under 35 U.S.C. 101 (SME Test Step 2A, Prong 2: Yes).
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.
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 1 & 3-14 are rejected under 35 U.S.C. 103 as being unpatentable over De Waele et al. (U.S. Patent Publication No. 2016/0051206), hereinafter “De Waele”, in view of Dyell et al. (U.S. Patent Publication No. 2023/0363678), hereinafter “Dyell”, further in view of Menzel et al. (U.S. Patent Publication No. 2022/0319304), hereinafter “Menzel”.
Claim 1 –
Regarding Claim 1, De Waele discloses a system that efficiently calculates and sets alarm thresholds for patient monitoring devices, comprising:
a data collection system comprising a first processor coupled to a database and coupled to a multiplicity of patient monitoring devices (See De Waele Par [0020] which discloses one or more medical monitors which receive vital sign signal values from monitored patients, such as a non-invasive or invasive blood pressure (BP) monitor, SpO2 or blood oximetry device, respiratory rate (RR) monitor, electrocardiogram (ECG) monitor, Heart Rate (HR) monitor and the like; See De Waele Par [0028]-[0029] & Fig .1 which disclose the system containing one or more processing devices and/or connected databases, data structures, non-transitory computer readable media, etc., for storing alarm settings or alarm profiles, the suggested profiles, the monitor log, the central log, the normative settings, the normative vital sign signals, and the patient data) wherein
each patient monitoring device of said multiplicity of patient monitoring devices is configured to obtain a time series of patient data samples, said patient data samples comprising vital sign values of one or more associated patient parameters (See De Waele Par [0020] which discloses one or more medical monitors which receive vital sign signal values from monitored patients, such as a non-invasive or invasive blood pressure (BP) monitor, SpO2 or blood oximetry device, respiratory rate (RR) monitor, electrocardiogram (ECG) monitor, Heart Rate (HR) monitor and the like; See De Waele Par [0007] which discloses alarm settings including at least one of an upper limit and a lower limit, i.e. value, for at least one monitored vital sign);
receive one or more threshold values (See De Waele Par [0002] which discloses one or more minimum and/or maximum threshold limit values; See De Waele Par [0021] which discloses receiving one or more alarm setting such as one or more upper and/or lower limit, i.e. threshold, values for a vital signal);
when said patient data samples are outside said one or more threshold values, generate an alarm (See De Waele Par [0002] which discloses one or more minimum and/or maximum threshold limit values, and upon exceeding one or more of the threshold limit values, sending an alert/generating an alarm; See De Waele Par [0021] which discloses receiving one or more alarm setting such as one or more upper and/or lower limit, i.e. threshold, values for a vital signal); and
transmit alarm data to said first processor (See De Waele Par [0023] which discloses a monitor log including alarm settings at an alarm event, alarm setting change history, etc., constituting alarm data), wherein
said alarm data comprises said patient data samples while said alarm is active (See De Waele Par [0023] which discloses including a vital sign signal history and/or vital sign signals according to alarm events or other time intervals), wherein
said one or more threshold values comprise an upper threshold and a lower threshold (See De Waele Par [0007] which discloses alarm settings including at least one of an upper limit and a lower limit, i.e. value, for at least one monitored vital sign);
said first processor is configured to collect said alarm data from said each patient monitoring device (See De Waele Par [0023] which discloses a monitor log, i.e. alarm summary record, including alarm settings at an alarm event, alarm setting change history, etc., constituting alarm data and is stored by the medical monitoring unit which can then possibly be received by a central log);
generate an alarm summary record associated with said alarm data and store said alarm summary record in said database (See De Waele Par [0023] which discloses a monitor log, i.e. alarm summary record, including alarm settings at an alarm event, alarm setting change history, etc., constituting alarm data and is stored by the medical monitoring unit which can then possibly be received by a central log), wherein
said alarm summary record comprises:
said alarm (See De Waele Par [0023] which discloses a monitor log, i.e. alarm summary record, including alarm settings at an alarm event, alarm setting change history, etc., constituting alarm data);
an alarm start time (See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, and would thereby constitute an “alarm start time” under BRI because this represents a time segment, i.e. start time to end time, that a certain alarm parameter is used);
an alarm duration (See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, and would thereby constitute an “alarm duration” under BRI because this represents a duration of time that a certain alarm parameter is used);
a minimum value of said vital sign values of said patient data samples of said alarm data during an alarm (See De Waele Par [0007] which discloses alarm settings including at least one of an upper limit and a lower limit, i.e. value, for at least one monitored vital sign); and
a maximum value of said vital sign values of said patient data samples of said alarm data during an alarm (See De Waele Par [0007] which discloses alarm settings including at least one of an upper limit and a lower limit, i.e. value, for at least one monitored vital sign); and,
an alarm threshold analysis system comprising a second processor coupled to said database (See De Waele Par [0028]-[0029] & Fig .1 which disclose the system containing one or more processing devices and/or connected databases, data structures, non-transitory computer readable media, etc., for storing alarm settings or alarm profiles, the suggested profiles, the monitor log, the central log, the normative settings, the normative vital sign signals, and the patient data), wherein
said second processor is configured to retrieve alarm summary records over a time period from said database (See De Waele Par [0023] which discloses a monitor log, i.e. alarm summary record, including alarm settings at an alarm event, alarm setting change history, etc., constituting alarm data and is stored by the medical monitoring unit which can then possibly be received by a central log);
process said alarm summary records and calculate an expected change in a number of alarms over said time period as a function of one or more modified threshold values based on said alarm summary records (See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period), wherein
said one or more modified threshold values comprise a modified upper threshold value as a modification to the upper threshold and a modified lower threshold value as a modification to the lower threshold (See De Waele Par [0022] which discloses a setting manager configured to receive changes, i.e. new or updated values, to alarm settings by electronic transmission from a suggested profile data store; See De Waele Par [0027] which discloses the observational analyzer recommending changes to alarms settings for the patient based on current vital sign data and/or alarm data, and sends the recommended changes to the alerting device or other computing device), wherein
the one or more modified threshold values are selected manually or automatically, to reduce the number of alarms to a desired level (See De Waele Par [0022] which discloses a setting manager configured to receive changes, i.e. new or updated values, to alarm settings by electronic transmission from a suggested profile data store; See De Waele Par [0027] which discloses the observational analyzer recommending changes to alarms settings for the patient based on current vital sign data and/or alarm data, and sends the recommended changes to the alerting device or other computing device);
determine said one or more modified threshold values based on analysis and extrapolation of alarm-summary records and corresponding patient-data samples (See De Waele Par [0027] which discloses the observational analyzer recommending changes to alarms settings for the patient based on current vital sign data and/or alarm data, and sends the recommended changes to the alerting device or other computing device; See De Waele Par [0037]-[0038] which discloses collected patient vital signs, i.e. patient-data samples, being averaged over a time interval, such that if the average vital sign data stream exceeds a threshold limit for time sufficiently long to infer that exceeding the limit is not a short term aberration, the data associated during that time (i.e. the data described in De Waele Par [0027] including vital sign data and/or alarm data) is collected over said time span to define a new alarm limit threshold, i.e. the new/modified threshold is extrapolated based on historical alarm/threshold values and patient-data samples from the time span associated with the exceeding of the threshold limit for a prolonged timeframe, and specifically states that a time interval, ether a minimum or maximum after which a different alarm setting value is recommended, i.e. future time period and therefore constitutes extrapolation of said data); wherein
alarm summary records are used to evaluate effects of said modified threshold values on said number of alarms over said time period (See De Waele Par [0021] which discloses alarm settings or alarm profiles defining alarm threshold values for one or more vital signals, and can include upper and/or lower limits, i.e. threshold values, such that the limits can be further refined based on alarm parameters, vital signs, validity, etc.; See De Waele Par [0027] which discloses over time, vital sign signals and/or alarm data can be tracked over time to develop an alarm/settings profiles, albeit not explicitly mentioned for specific effects of the threshold values over time on the number of alarms rather than a general refinement of alarm parameters, vital signs, etc.);
determine and select a new threshold value of said one or more modified threshold values (See De Waele Par [0027] which discloses the observational analyzer recommending changes to alarms settings for the patient based on current vital sign data and/or alarm data, and sends the recommended changes to the alerting device or other computing device; See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.); and
transmit said new threshold value to one or more of said multiplicity of patient monitoring devices to replace one or more of said one or more threshold values that exist in said one or more of said multiplicity of patient monitoring devices to reduce the number of alarms to the desired level (See De Waele Par [0022] which discloses a setting manager configured to receive changes, i.e. new or updated values, to alarm settings by electronic transmission from a suggested profile data store; See De Waele Par [0027] which discloses the observational analyzer recommending changes to alarms settings for the patient based on current vital sign data and/or alarm data, and sends the recommended changes to the alerting device or other computing device; See De Waele Par [0038] which discloses a notice sent with the recommendation, i.e. change, to alerting devices, i.e. multiplicity of monitoring devices and as in disclosed in De Waele Par [0003], these recommendations/changes are made to reduce overall alarm fatigue); wherein
said new threshold value modifies one or more of said upper threshold or said lower threshold used by said one or more of said multiplicity of patient monitoring devices to generate said alarm (See De Waele Par [0007] which discloses alarm settings including at least one of an upper limit and a lower limit, i.e. value, for at least one monitored vital sign; See De Waele Par [0022] which discloses a setting manager configured to receive changes, i.e. new or updated values, e.g. limit values, to alarm settings by electronic transmission from a suggested profile data store; See De Waele Par [0027] which discloses the observational analyzer recommending changes to alarms settings for the patient based on current vital sign data and/or alarm data, and sends the recommended changes to the alerting device or other computing device; See De Waele Par [0038] which discloses a notice sent with the recommendation, i.e. change, to alerting devices, i.e. multiplicity of monitoring devices and as in disclosed in De Waele Par [0003], these recommendations/changes are made to reduce overall alarm fatigue).
While De Waele generally discloses updating or modifying alarm settings by electronic transmission, such as to reduce the number of alarms generated, De Waele is generally silent regarding determining a functional relationship between potential modifications to the threshold values and a resulting number of alarms for said purposes of reducing the number of alarms and/or the various steps recited in a closed-loop system for iteratively adjusting device behavior as given by the following limitation:
evaluate a range of modified threshold values of said one or more modified threshold values for a desired time period to generate a functional relationship between potential modifications to the one or more modified threshold values and a resulting number of alarms;
alarm summary records are used to evaluate effects of said modified threshold values on said number of alarms over said time period
determine and select a new threshold value of said one or more modified threshold values based on said functional relationship;
wherein
said collect said alarm data, said generate said alarm summary record, said retrieve alarm summary records, said process said alarm summary records, said determine said one or more modified threshold values, and said replace one or more of said one or more threshold values that exist in said one or more of said multiplicity of patient monitoring devices are fully automated to form a closed-loop system that iteratively adjusts device behavior to achieve a desired rate of alarms.
However, Dyell discloses evaluate a range of modified threshold values of said one or more modified threshold values for a desired time period to generate a functional relationship between potential modifications to the one or more modified threshold values and a resulting number of alarms (See Dyell Par [0096]-[0099] which discloses the system monitoring trends in available data in order to trigger shifts in how alarms are presented, such that a fatigue model can be generated using a feedback loop, for example, as a user experiences more and more alarms throughout a shift (i.e. a desired time period), that user's alarm fatigue rises, and therefore, the systems sensing and quantifying a rise in alarm fatigue level automatically modulates, i.e. modifies, alarm outputs/conditions to mitigate effects of the user’s alarm fatigue; Dyell Par [0099] further specifies that frames of reference, e.g. desired time period, can span hours, days, weeks, months, and/or years); alarm summary records are used to evaluate effects of said modified threshold values on said number of alarms over said time period (It is understood by Examiner that “evaluating effects of said modified threshold values on said number of alarms over said time period” could merely be an overall increase or reduction in the number of alarms rather than a specific amount of increase or decrease, therefore see Dyell Par [0095] which discloses the result of changing the alarm conditions within the devices is a reduced number of alarms, thereby decreasing overall alarm fatigue); determine and select a new threshold value of said one or more modified threshold values based on said functional relationship (See Dyell Par [0096]-[0099] which discloses the system monitoring trends in available data in order to trigger shifts in how alarms are presented, such that a fatigue model can be generated using a feedback loop, for example, as a user experiences more and more alarms throughout a shift (i.e. a desired time period), that user's alarm fatigue rises, and therefore, the systems sensing and quantifying a rise in alarm fatigue level automatically modulates, i.e. modifies, alarm outputs/conditions to mitigate effects of the user’s alarm fatigue; Dyell Par [0099] further specifies that frames of reference, e.g. desired time period, can span hours, days, weeks, months, and/or years; See Dyell Par [0089]-[0093] specifically mentions considerations of particular medical devices that may be more prone to issuing excessive alarms because a threshold condition is too low, or has varying measurement sensitivities, such that the system can determine potential alarm conditions and consider a measurement sensitivity to determine a minimum amount of change a physiological measurement undergoes before the medical device detects the change for triggering alarms to reduce unnecessary alarm generation, such as by determining when fewer or greater alarms would be issued, and specifically recites if a medical device is set to detect body temperature changes only when the temperature change is 0.2 degrees or greater, fewer alarms would be generated based on small fluctuations around the threshold value, and thereby also establishes a functional relationship between potential modifications of said devices and a resulting number of alarms from said modifications based, for instance, measurement sensitivity) wherein, collect said alarm data, said generate said alarm summary record, said retrieve alarm summary records, said process said alarm summary records, said determine said one or more modified threshold values, and said replace one or more of said one or more threshold values that exist in said one or more of said multiplicity of patient monitoring devices are fully automated to form a closed-loop system that iteratively adjusts device behavior to achieve a desired rate of alarms (see Dyell Par [0097]-[0099] which discloses employing a closed-loop control system, such that the system can be configured to account for any hysteresis of its feedback loop, where hysteresis indicates a dependence of the output of system on its current input and its history of past inputs, i.e. outputs/behavior of the system forms a closed-loop system to iteratively adjust the system to prevent alarm fatigue, as specifically mentioned in Dyell Par [0095] & [0097], such that based on monitored trends, etc. in available data may trigger shifts in how alarms are to be outputted for corresponding devices; See Dyell Par [0089]-[0093] specifically mentions considerations of particular medical devices that may be more prone to issuing excessive alarms because a threshold condition is too low, or has varying measurement sensitivities, such that the system can determine potential alarm conditions and consider a measurement sensitivity to determine a minimum amount of change a physiological measurement undergoes before the medical device detects the change for triggering alarms to reduce unnecessary alarm generation, such as by determining when fewer or greater alarms would be issued, and specifically recites if a medical device is set to detect body temperature changes only when the temperature change is 0.2 degrees or greater, fewer alarms would be generated based on small fluctuations around the threshold value, and thereby also establishes a functional relationship between potential modifications of said devices and a resulting number of alarms from said modifications based, for instance, measurement sensitivity; See Dyell Par [0078] & [0092]-[0093] which discloses implementing or changing alarms and/or types of alarms based on alarm condition and this having a direct effect on how frequently the medical device generates alarms, such as potentially reducing the number of alarms). The disclosure of Dyell is directly applicable to the disclosure of De Waele because both disclosures share limitations and capabilities, such as being directed towards modifying and monitoring one or more alarm/alert parameters.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of De Waele which discloses updating or modifying alarm settings by electronic transmission, such as to reduce the number of alarms generated to further include evaluate a range of modified threshold values of said one or more modified threshold values for a desired time period to generate a functional relationship between potential modifications to the one or more modified threshold values and a resulting number of alarms and using a closed-loop system to iteratively adjust , as disclosed by Dyell, because this allows for an automatic fatigue model to be generated using a feedback loop, such that a system can automatically modulate, i.e. modify, the alarm outputs to that user to mitigate effects of the user’s alarm fatigue (See Dyell Par [0096]-[0099]).
While De Waele and Dyell generally disclose receiving one or more alarm records, comparing one or more alarm thresholds for reducing alarm fatigue, and determining effects of alarms over a certain time period, De Waele and Dyell are generally silent on eliminating and/or removing one or more alarm summary records, such as nuisance alarms as given by the following limitation:
eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records.
However, Menzel discloses eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records (See Menzel Par [0027]-[0029] which discloses in response to a comparison of a quantity of occurrences of at least one identified alarm nuisance behavior over a given analysis period for the at least one identified alarm nuisance behavior not meeting prescribed conditions of certain thresholds or occurrences, and said nuisance behavior being filtered or removed from a dataset and receiving information; See Menzel Par [0171]-[0172] which discloses determining behaviors indicating of alarm nuisance behaviors based on the use of one or more thresholds and number of alarms being compared to said thresholds and the system may iterate until the inferred threshold of number of alarms is considered significant and repetitive and eliminates nuisance alarm parameters/behaviors). The disclosure of Menzel is directly applicable to the combined disclosure of De Waele and Dyell, because the disclosures share limitations and capabilities, such as being directed towards predicting occurrence of one or more alarms and alarm nuisance behaviors thereof.
It would have been obvious to one of ordinary skill in the prior art before the effective filing date of the claimed invention to modify the combined disclosure of De Waele and Dyell which already discloses receiving one or more alarm records, comparing one or more alarm thresholds for reducing alarm fatigue, and determining effects of alarms over a certain time period to further include eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records, as disclosed by Menzel, because this allows for looped/iterative elimination of nuisance alarm parameters/behaviors that cause nuisance alarm behavior and/or alarm fatigue (See Menzel Par [0027]-[0029] & [0171]-[0172]).
Claim 3 –
Regarding Claim 3, De Waele and Dyell disclose the system of claim 1 in its entirety. De Waele further discloses a system, wherein:
said second processor is further configured to
determine said new threshold value as a modified threshold value that results in a target value of said expected change in said number of alarms over said time period (See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.; See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period).
Claim 4 –
Regarding Claim 4, De Waele and Dyell disclose the system of claim 1 in its entirety. De Waele further discloses a system, wherein:
said second processor is further configured to obtain or calculate a classification of each alarm summary record of said alarm summary records as
a high alarm corresponding to said patient data samples above said upper threshold (See De Waele Par [0036] which discloses deriving high limit and low limit setting values being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, and 99% quantile representing a “high” value above the separation value), or
a low alarm corresponding to said patient data samples below said lower threshold (See De Waele Par [0036] which discloses deriving high limit and low limit setting values being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, and 1% quantile representing a “low” value above the separation value).
Claim 5 –
Regarding Claim 5, De Waele and Dyell disclose the system of claim 4 in its entirety. De Waele and Menzel further disclose a system, wherein:
said eliminating said one or more alarm summary record comprises
eliminating said one or more alarm summary records when said maximum value of said patient data samples below said modified upper threshold value (Under broadest reasonable interpretation, contingent limitations require only those steps that must be performed and does not have to include steps that are not required to be performed because conditions precedent are not met; however, the BRI of a system claim having structure that performs a function that is conditional, at least requires the structure for performing the function should the condition occur, but still does not have to teach said function, see MPEP 2111.04(II); therefore, De Waele Par [0028]-[0029] & Fig. 1 disclosing the system containing one or more processing devices and/or connected databases, data structures, non-transitory computer readable media, etc., for storing and managing storage of alarm settings or alarm profiles, the suggested profiles, the monitor log, the central log, the normative settings, the normative vital sign signals, and the patient data and for editing or modifying threshold values effectively reads on the limitation herein because the conditions of “when one of said one or more modified threshold values corresponds to a modified upper threshold” does not have to ever necessarily be met under BRI, because all of the modified threshold values could correspond to a lower threshold; See Menzel Par [0027]-[0029] which discloses in response to a comparison of a quantity of occurrences of at least one identified alarm nuisance behavior over a given analysis period for the at least one identified alarm nuisance behavior not meeting prescribed conditions of certain thresholds or occurrences, and said nuisance behavior being filtered or removed from a dataset and receiving information; See Menzel Par [0171]-[0172] which discloses determining behaviors indicating of alarm nuisance behaviors based on the use of one or more thresholds and number of alarms being compared to said thresholds and the system may iterate until the inferred threshold of number of alarms is considered significant and repetitive and eliminates nuisance alarm parameters/behaviors); and
eliminating said one or more alarm summary records when said minimum value of said patient data samples above said modified lower threshold value (Under broadest reasonable interpretation, contingent limitations require only those steps that must be performed and does not have to include steps that are not required to be performed because conditions precedent are not met; however, the BRI of a system claim having structure that performs a function that is conditional, at least requires the structure for performing the function should the condition occur, but still does not have to teach said function, see MPEP 2111.04(II); therefore, De Waele Par [0028]-[0029] & Fig. 1 disclosing the system containing one or more processing devices and/or connected databases, data structures, non-transitory computer readable media, etc., for storing alarm settings or alarm profiles, the suggested profiles, the monitor log, the central log, the normative settings, the normative vital sign signals, and the patient data and for editing or modifying threshold values effectively reads on the limitation herein because the conditions of “when one of said one or more modified threshold values corresponds to a modified upper threshold” does not have to ever necessarily be met under BRI, because all of the modified threshold values could correspond to an upper threshold value; See Menzel Par [0027]-[0029] which discloses in response to a comparison of a quantity of occurrences of at least one identified alarm nuisance behavior over a given analysis period for the at least one identified alarm nuisance behavior not meeting prescribed conditions of certain thresholds or occurrences, and said nuisance behavior being filtered or removed from a dataset and receiving information; See Menzel Par [0171]-[0172] which discloses determining behaviors indicating of alarm nuisance behaviors based on the use of one or more thresholds and number of alarms being compared to said thresholds and the system may iterate until the inferred threshold of number of alarms is considered significant and repetitive and eliminates nuisance alarm parameters/behaviors).
It would have been obvious to one of ordinary skill in the prior art before the effective filing date of the claimed invention to modify the combined disclosure of De Waele and Dyell which already discloses receiving one or more alarm records, comparing one or more alarm thresholds for reducing alarm fatigue, and determining effects of alarms over a certain time period to further include eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records, as disclosed by Menzel, because this allows for looped/iterative elimination of nuisance alarm parameters/behaviors that cause nuisance alarm behavior and/or alarm fatigue (See Menzel Par [0027]-[0029] & [0171]-[0172]).
Claim 6 –
Regarding Claim 6, De Waele and Dyell disclose discloses the system of claim 4 in its entirety. De Waele further discloses a system, wherein:
said alarm summary record further comprises
a first value of said patient data samples of said alarm data (See De Waele Par [0007] which discloses alarm settings including at least one of an upper and a lower limit, i.e. value, for at least one monitored vital sign; See De Waele Par [0023] which discloses a monitor log, i.e. alarm summary record, including alarm settings at an alarm event, alarm setting change history, vital sign signals according to alarm events or other time intervals, etc.); and
said calculate the classification of said each alarm summary record comprises
apply a k-means clustering algorithm with two clusters to a dataset comprising said first value of said patient data samples of said alarm summary records (See De Waele Par [0034] which discloses applying a k-means algorithm for automated clustering, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles);
calculate a separation value as a mean of centroids of said two clusters (See De Waele Par [0034] which discloses applying a k-means algorithm for automated clustering, such that a representative or center value, i.e. centroid, of each cluster is computed as an alarm setting value in one or more suggested profiles; See De Waele Par [0036] which discloses deriving high limit and low limit setting values being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, ±2 standard deviations, etc.);
classify said each alarm summary record as said high alarm when said first value of said each alarm summary record is above said separation value (See De Waele Par [0036] which discloses deriving high limit and low limit setting values being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, and 99% quantile representing a “high” value above the separation value); and
classify said each alarm summary record as said low alarm when said first value of said each alarm summary record is below said separation value (See De Waele Par [0036] which discloses deriving high limit and low limit setting values being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, and 1% quantile representing a “low” value above the separation value).
Claim 7 –
Regarding Claim 7, De Waele and Dyell disclose the system of claim 6 in its entirety. De Waele further discloses a system, wherein:
said second processor is further configured to calculate one or both of said upper threshold and said lower threshold (See De Waele Par [0034] which discloses applying a k-means algorithm for automated clustering, such that a representative or center value, i.e. centroid, of each cluster is computed as an alarm setting value in one or more suggested profiles; See De Waele Par [0036] which discloses deriving high limit and low limit setting values, i.e. thresholds, being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, ±2 standard deviations, etc.).
Claim 8 –
Regarding Claim 8, De Waele discloses the system of claim 7 in its entirety. De Waele further discloses a system, wherein:
said calculate one or both of said upper threshold and said lower threshold comprises:
calculate a first frequency distribution of first values of said alarm summary records that are classified as high alarms (See De Waele Par [0033]-[0034] & Fig. 3 which discloses a correlation plot and/or cluster analysis of two alarm settings or limits, such that a first alarm limit and second alarm limit are represented and dots are sized to represent the frequency of occurrence in the analyzed monitor logs or extracted normative settings and/or normative vital sign signals, i.e. first and second frequency distributions for each alarm limit, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles, the higher center cluster value representing high alarm, and the lower center cluster value representing a low alarm);
calculate a first modal frequency as a frequency of a mode of all or a portion of said first frequency distribution (See De Waele Par [0033]-[0034] & Fig. 3 which discloses a correlation plot and/or cluster analysis of two alarm settings or limits, such that a first alarm limit and second alarm limit are represented and dots are sized to represent the frequency of occurrence in the analyzed monitor logs or extracted normative settings and/or normative vital sign signals, i.e. frequency distribution, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles);
calculate a second frequency distribution of first values of said alarm summary records that are classified as low alarms (See De Waele Par [0033]-[0034] & Fig. 3 which discloses a correlation plot and/or cluster analysis of two alarm settings or limits, such that a first alarm limit and second alarm limit are represented and dots are sized to represent the frequency of occurrence in the analyzed monitor logs or extracted normative settings and/or normative vital sign signals, i.e. first and second frequency distributions for each alarm limit, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles, the higher center cluster value representing high alarm, and the lower center cluster value representing a low alarm);
calculate a second modal frequency as a frequency of a mode of all or a portion of said second frequency distribution (See De Waele Par [0033]-[0034] & Fig. 3 which discloses a correlation plot and/or cluster analysis of two alarm settings or limits, such that a first alarm limit and second alarm limit are represented and dots are sized to represent the frequency of occurrence in the analyzed monitor logs or extracted normative settings and/or normative vital sign signals, i.e. frequency distribution, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles);
calculate said upper threshold as a smallest value above said separation value having a frequency in said first frequency distribution greater than a first fraction times said first modal frequency (See De Waele Par [0033]-[0034] & Fig. 3 which discloses a correlation plot and/or cluster analysis of two alarm settings or limits, such that a first alarm limit and second alarm limit are represented and dots are sized to represent the frequency of occurrence in the analyzed monitor logs or extracted normative settings and/or normative vital sign signals, i.e. frequency distribution, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles; See De Waele Par [0034] which discloses applying a k-means algorithm for automated clustering, such that a representative or center value, i.e. centroid, of each cluster is computed as an alarm setting value in one or more suggested profiles; See De Waele Par [0036] which discloses deriving high limit and low limit setting values, i.e. thresholds, being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, ±2 standard deviations, etc.; furthermore, this portion of the claim seems to read as routine optimization within prior art conditions or through routine experimentation, i.e. when the general conditions of a claim are disclosed in the prior art, it is not inventive to discover optimum or workable ranges or values by routine experimentation, such as in this case a smallest value above said separation value or a largest value below said separation value, and therefore De Waele generally disclosing the separation of both clusters and identifying distinct high and low clusters are different quantiles or standard deviations, choosing the value for the degree of separation such as a smallest value above said separation value or a largest value below said separation value does not add inventiveness or patentability of subject matter, and thereby seems to be entirely met by De Waele); and
calculate said lower threshold as a largest value below said separation value having a frequency in said second frequency distribution greater than a second fraction times said second modal frequency (See De Waele Par [0033]-[0034] & Fig. 3 which discloses a correlation plot and/or cluster analysis of two alarm settings or limits, such that a first alarm limit and second alarm limit are represented and dots are sized to represent the frequency of occurrence in the analyzed monitor logs or extracted normative settings and/or normative vital sign signals, i.e. frequency distribution, such that a representative or center value of each cluster is computed as an alarm setting value in one or more suggested profiles; See De Waele Par [0034] which discloses applying a k-means algorithm for automated clustering, such that a representative or center value, i.e. centroid, of each cluster is computed as an alarm setting value in one or more suggested profiles; See De Waele Par [0036] which discloses deriving high limit and low limit setting values, i.e. thresholds, being derived from cluster distribution such that separation values such as quantiles or standard deviations can be used to identify distinct high and low clusters, e.g. 1% and 99% quantiles, ±2 standard deviations, etc.; furthermore, this portion of the claim seems to read as routine optimization within prior art conditions or through routine experimentation, i.e. when the general conditions of a claim are disclosed in the prior art, it is not inventive to discover optimum or workable ranges or values by routine experimentation, see MPEP 2144.05(II), such as in this case, specifying the degree of separation for identifying lower and higher thresholds as a smallest value above said separation value or a largest value below said separation value, and therefore because De Waele generally discloses the separation of both clusters and identifying distinct high and low clusters at different quantiles or standard deviations, Applicant choosing the value for the degree of separation such as a smallest value above said separation value or a largest value below said separation value does not add inventiveness or patentability of subject matter, and therefore this claim seems to be rendered obvious by the disclosure of De Waele, unless these degrees of separation for identifying lower and higher thresholds are shown to be critical, are shown to be taught away by De Waele or other prior art, are not recognized as a result-effective variable in the prior art, and/or are only disclosed in a very broad range in the prior art so as to not invite optimization by one of ordinary skill in the art).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the disclosure of De Waele and Dyell by performing routine optimization within prior art conditions already described by De Waele, i.e. deriving high limit and low limit setting values/thresholds, from cluster distribution such that separation values can be used to identify distinct high and low clusters, in order to discover optimized separation values for determining higher and lower alarm thresholds, i.e. smallest value above said separation value or a largest value below said separation value, as described in the limitations found above.
Claim 9 –
Regarding Claim 9, De Waele and Dyell disclose the system of claim 4 in its entirety. De Waele further discloses a system, wherein:
said second processor is further configured to calculate an expected increase in said number of alarms over said time period when said upper threshold is decreased to a smaller upper threshold or said lower threshold is increased to a larger lower threshold (See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.; See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period).
Claim 10 –
Regarding Claim 10, De Waele and Dyell disclose the system of claim 9 in its entirety. De Waele further discloses a system, wherein:
said calculate said expected increase in said number of alarms over said time period comprises
obtain or estimate a distribution of said patient data samples (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution);
when said upper threshold is decreased to said smaller upper threshold, calculate said expected increase in said number of alarms as a frequency of said distribution between said smaller upper threshold and said upper threshold divided by a frequency of said distribution above said upper threshold multiplied by said number of alarms (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values, i.e. one or more distributions; See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.; See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period); and
when said lower threshold is increased to said larger lower threshold, calculate said expected increase in said number of alarms as a frequency of said distribution between said lower threshold and said larger lower threshold divided by a frequency of said distribution below said lower threshold multiplied by said number of alarms (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values, i.e. one or more distributions; See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.; See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period).
Claim 11 –
Regarding Claim 11, De Waele and Dyell disclose the system of claim 9 in its entirety. De Waele further discloses a system, wherein:
said calculate said calculate said expected increase in said number of alarms over said time period comprises:
calculate one or both of:
a first distribution of expected alarm maximum values based on extrapolation of a frequency distribution of said maximum value of said alarm summary records (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values, i.e. one or more distributions);
a second distribution of expected alarm minimum values based on extrapolation of a frequency distribution of said minimum value of said alarm summary records (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values, i.e. one or more distributions); and
when said upper threshold is decreased to said smaller upper threshold, calculate said expected increase in said number of alarms as a total frequency of said first distribution between said smaller upper threshold and said upper threshold (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values, i.e. one or more distributions; See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.; See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period); and
when said lower threshold is increased to said larger lower threshold, calculate said expected increase in said number of alarms as a total frequency of said second distribution between said lower threshold and said larger lower threshold (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values, i.e. one or more distributions; See De Waele Par [0032] which specifies said changes including changes in a single alarm setting value, or changes in combinations of one or more alarm setting values of one or more vital signs such as a change in upper limit value, i.e. upper threshold, of RR is recommended, changes in upper and lower limit values, i.e. upper and lower thresholds, of RR are recommended, or changes in upper and lower limit values of RR and SpO2, i.e. upper and lower thresholds of one or more vital signs, are recommended, etc.; See De Waele Par [0038] which discloses the system identifying a time interval, either a minimum or a maximum after which a different alarm setting value is recommended, such that after a predetermined time interval or function thereof is satisfied, a second alarm setting is recommended based on certain variables, including alarm counts, i.e. number of alarms over said time period).
Claim 12 –
Regarding Claim 12, De Waele and Dyell disclose the system of claim 11 in its entirety. De Waele further discloses a system, wherein:
said extrapolation of said frequency distribution of said maximum value and said extrapolation of said frequency distribution of said minimum value comprises linear regression (See De Waele Par [0030]-[0031] and Fig. 2 which discloses utilizing linear regression and extrapolation on a graph with dots representing a frequency of usage or a frequency of occurrence in a population of data, i.e. frequency distribution, for determining maximum and minimum value alarm settings and can utilize multi-parameter correlation of multiple alarm setting or limit values and corresponding multiple vital sign signal values).
Claim 13 –
Regarding Claim 13, De Waele and Dyell disclose the system of claim 1 in its entirety. De Waele further discloses a system, wherein:
said first processor is further configured to not store said alarm summary record when said alarm duration is below a duration threshold value (Under broadest reasonable interpretation, contingent limitations require only those steps that must be performed and does not have to include steps that are not required to be performed because conditions precedent are not met; however, the BRI of a system claim having structure that performs a function that is conditional, at least requires the structure for performing the function should the condition occur, but still does not have to teach said function, see MPEP 2111.04(II); therefore, De Waele Par [0028]-[0029] & Fig. 1 disclosing the system containing one or more processing devices and/or connected databases, data structures, non-transitory computer readable media, etc., for storing alarm settings or alarm profiles, the suggested profiles, the monitor log, the central log, the normative settings, the normative vital sign signals, and the patient data and for editing or modifying threshold values effectively reads on the limitation herein because the conditions of “when said alarm duration is below a duration threshold value” does not have to ever necessarily be met under BRI, because alarm duration can potentially always be above a duration threshold value; therefore this claim limitation is effectively met by De Waele under 35 U.S.C. 103).
Claim 14 –
Regarding Claim 14, De Waele, Dyell, and Menzel disclose the system of claim 1 in its entirety. Menzel further discloses a system, wherein:
said first processor is configured to discard alarm data associated with alarms having a duration below a duration threshold value prior to generating said alarm summary record (the duration being “below a duration threshold” represents an optimization within prior art conditions, such that the same or similar could be implemented with above a duration threshold and therefore, as long as the prior art expresses aspects of falling outside a threshold or occurrence and discarding alarm data for said condition, this claim is considered met in its entirety; therefore, See Menzel Par [0027]-[0029] which discloses in response to a comparison of a quantity of occurrences of at least one identified alarm nuisance behavior over a given analysis period for the at least one identified alarm nuisance behavior not meeting prescribed conditions of certain thresholds or occurrences, and said nuisance behavior being filtered or removed from a dataset and receiving information; See Menzel Par [0171]-[0172] which discloses determining behaviors indicating of alarm nuisance behaviors based on the use of one or more thresholds and number of alarms being compared to said thresholds and the system may iterate until the inferred threshold of number of alarms is considered significant and repetitive and eliminates nuisance alarm parameters/behaviors).
It would have been obvious to one of ordinary skill in the prior art before the effective filing date of the claimed invention to modify the combined disclosure of De Waele and Dyell which already discloses receiving one or more alarm records, comparing one or more alarm thresholds for reducing alarm fatigue, and determining effects of alarms over a certain time period to further include eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records, as disclosed by Menzel, because this allows for looped/iterative elimination of nuisance alarm parameters/behaviors that cause nuisance alarm behavior and/or alarm fatigue (See Menzel Par [0027]-[0029] & [0171]-[0172]).
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over De Waele, in view of Dyell, in view of Menzel, further in view of Wang et al. (U.S. Patent Publication No. 2008/0284582), hereinafter “Wang”.
Claim 15 –
Regarding Claim 15, De Waele, Dyell, and Menzel disclose the system of claim 1 in its entirety. De Waele, Dyell, and Menzel do not disclose a system, wherein:
said alarm summary records are generated only from patient data samples obtained while said alarm is active.
However, Wang discloses said alarm summary records are generated only from patient data samples obtained while said alarm is active (See Wang Par [0020] which discloses the system detecting alarms and classifying alarm patterns of said alarms and storing them in an alarm pattern database, such that the database may incorporate a chronological alarm file containing all alarm times and types during one or more monitored sessions, such that it is understood by Examiner that the alarm patterns of said alarms are only indicative of alarm data during said alarm timestamps, and as described in Wang Par [0021] said monitoring module monitors a patient’s physiological status when, i.e. during, an alarm pattern of significance). The disclosure of Wang is directly applicable to the combined disclosure of De Waele, Dyell, and Menzel, because the disclosures share limitations and capabilities, such as being directed towards monitoring one or more alarm patterns over time for determining alarm behavior/parameterization.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of De Waele, Dyell, and Menzel regarding generation of alarm summary records, to further specify that said alarm summary records are generated only from patient data samples obtained while said alarm is active, because this allows for generation and subsequent identification of alarm data patterns specifically during alarm times and monitoring a patient’s physiological status during an alarm pattern of significance, i.e. being able to identify patient physiological data when an alarm pattern is significant and is not a nuisance or false alarm (See Wang Par [0020]-[0021]).
Response to Arguments
Applicant's arguments filed 07 April 2026 have been fully considered but they are not persuasive:
Regarding 35 U.S.C. 101 rejections of claims 1 & 3-15, Applicant argues on p. 11-19 of Arguments/Remarks in view of Alice/Mayo Step 2A, Prongs 1 & 2 that the amended claims provide technological improvement in device operation and a specific improvement in computer and device functionality. Applicant further specifies aspects that purportedly integrate any such abstract idea into a specific technological solution, such as a closed-loop actuation and reimplementation of device configurational settings back into the multiplicity of devices. Examiner agrees with Applicant’s arguments. As explained above in the “Claim Rejections – 35 U.S.C. 101” section of this Office Action, The additional elements go beyond well-understood, routine, and conventional activity in particular fields, at least by amounting to an inventive concept, such as via improvements to the technical field of patient monitoring by effectively reducing alarm fatigue and/or amounting to an ordered combination that accomplishes said inventive concept, allowing for improvements in the field of interconnected patient monitoring systems. For example, by substantially describing the algorithm regarding collecting alarm data over time, responsiveness to said alarms, determining a functional relationship between adjustment of various patient vital sign thresholds and the resulting effects/change in the number of alarms, and implementing said adjustments into the multiplicity of patient devices to produce a desired level/number of alarms and thereby reducing perceived alarm fatigue between multiple devices in a clinical setting. Furthermore, fully automating the replacement efforts to form a closed-loops system that iteratively adjusts device behavior to achieve a desired rate of alarms represents a meaningful limitation beyond generally linking the use of the judicial exception to a particular technological environment, at least by manipulating the device behavior/configurational settings and output of one or more alarms for a multiplicity of patient monitoring devices. Therefore, the claims represent patent-eligible subject matter under 35 U.S.C. 101. Therefore, the previous 35 U.S.C. 101 rejections for claims 1 & 3-15 have been withdrawn.
Regarding 35 U.S.C. 103 rejections of claims 1 & 3-13, Applicant argues on p. 17-24 of Arguments/Remarks that De Waele and Dyell do not disclose the entirety of the claims in view of the newly amended limitations found in independent claim 1. More specifically, Applicant argues that De Waele and Dyell are silent regarding “alarm summary records that include: a minimum value of a patient data during an alarm, and a maximum value of patient data during an alarm”. Applicant further argues that Dyell does not disclose alarm summary records with min/max values during an alarm, or any structured dataset designed for predicting alarm frequency based on threshold changes. Examiner agrees with Applicant’s arguments. Therefore, the 35 U.S.C. 103 rejections for claims 1 & 3-13 have been withdrawn. However, upon further consideration, a new ground of rejection is made under 35 U.S.C. 103 over De Waele, in view of Dyell, further in view of Menzel. De Waele discloses various amended limitations via previously cited portions of De Waele, such as by transmitting/implementing changes to a multiplicity of patient monitoring devices. Newly cited portions of Dyell are relied upon to read on the newly amended limitation “alarm summary records are used to evaluate effects of said modified threshold values on said number of alarms over said time period” by Dyell Par [0095] effectively disclosing the result of changing the alarm conditions within the devices is a reduced number of alarms, thereby decreasing overall alarm fatigue, and thereby establishing a functional relationship between thresholds and alarm counts. Newly cited Menzel reads on efforts regarding “eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records” via Menzel Par [0027]-[0029] and Par [0171]-[0172]. While Applicant generally argues that De Waele and Dyell do not disclose alarm summary records with min/max values, generation of a functional relationship over a range of threshold and/or specific closed-loop optimization process recited, it is understood by Examiner that these portions are indeed effectively met by De Waele and Dyell. Therefore, claims 1 & 3-13 and newly pending claim 14 remain rejected under 35 U.S.C. 103 over a new ground of rejection made over De Waele, in view of Dyell, further in view of Menzel. Additionally, newly pending claim 15 remains rejected under De Waele, in view of Dyell, further in view of Menzel, further in view of Wang.
Regarding 35 U.S.C. 103 rejections of claims 1 & 3-13, Applicant argues on p. 24-27 of Arguments/Remarks that De Waele and Dyell do not effectively disclose an “eliminating alarm summary records based on threshold comparisons”, and therefore the 35 U.S.C. 103 rejections for independent claim 1 should be withdrawn. Examiner respectfully disagrees with Applicant’s arguments. While Examiner concedes that De Waele and Dyell do not disclose “eliminating one or more alarm summary records based on comparisons of said modified upper threshold value with said maximum value and said modified lower threshold value with said minimum value of said alarm summary records”, newly cited Menzel reads on these efforts in their entirety via Menzel Par [0027]-[0029] and Par [0171]-[0172]. Therefore, Applicant’s arguments regarding 35 U.S.C. 103 rejections for independent claim 1 should be withdrawn because De Waele and Dyell do not effectively disclose an “eliminating alarm summary records based on threshold comparisons” are effectively rendered moot. As such, claims 1 & 3-15 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 103 rejections of claims 1 & 3-15, Applicant argues on p. 27-28 of Arguments/Remarks that De Waele and Dyell do not disclose “discard alarm data associated with alarms having a duration below a duration threshold value prior to generating said alarm summary record” as found in newly pending claim 14. Examiner agrees with Applicant’s arguments. However, newly cited Menzel effectively discloses “discard alarm data associated with alarms having a duration below a duration threshold value prior to generating said alarm summary record”. Therefore, these limitations and claim 14 are effectively met by the combination of De Waele and Dyell, further in view of Menzel under 35 U.S.C. 103. As such, claims 1 & 3-15 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 103 rejections of claims 1 & 3-15, Applicant argues on p. 28 of Arguments/Remarks that De Waele and Dyell do not disclose “generating alarm summary records only from patient data samples obtained while an alarm is active” as found in newly pending claim 15. Examiner agrees with Applicant’s arguments. However, newly cited Wang effectively discloses “generating alarm summary records only from patient data samples obtained while an alarm is active”. Therefore, these limitations and claim 15 are effectively met by the combination of De Waele and Dyell, further in view of Menzel, further in view of Wang. As such, claims 1 & 3-15 remain rejected under 35 U.S.C. 103.
Regarding 35 U.S.C. 103 rejections of claims 1 & 3-15, Applicant argues on p. 28 of Arguments/Remarks that dependent claims, which depend from purportedly allowable independent claim 1, are also unobvious/allowable by virtue of dependency. Examiner respectfully disagrees with Applicant’s arguments. Independent claim 1 has been determined to be rejected under 35 U.S.C. 103 over a new ground of rejection made over De Waele and Dyell, further in view of Menzel. Therefore, Applicant’s arguments regarding independent claim 1 being allowable are effectively rendered moot because independent claim 1 is still rejected under 35 U.S.C. 103. As such, claims 1 & 3-15 remain rejected under 35 U.S.C. 103.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Shah et al. (U.S. Patent Publication No. 2025/0017518) discloses a system for an epilepsy monitor that provides consistent and continuous use of the monitor in the daily lives of people with epilepsy, and does not generate frequent false alarms that result in alarm fatigue in the users and caregivers.
Applicant's amendment necessitated the new ground 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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/H.R./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
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