Prosecution Insights
Last updated: April 19, 2026
Application No. 19/066,000

Systems and Methods for Detecting Patients Susceptible to Falls and Wounds and Providing Notifications for Preventing or Mitigating Falls and Wounds Incurred by the Susceptible Patients

Non-Final OA §101§102§103
Filed
Feb 27, 2025
Examiner
HAYNES, DAWN TRINAH
Art Unit
3686
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Saiva AI Inc.
OA Round
1 (Non-Final)
2%
Grant Probability
At Risk
1-2
OA Rounds
4y 7m
To Grant
5%
With Interview

Examiner Intelligence

Grants only 2% of cases
2%
Career Allow Rate
1 granted / 67 resolved
-50.5% vs TC avg
Minimal +4% lift
Without
With
+3.5%
Interview Lift
resolved cases with interview
Typical timeline
4y 7m
Avg Prosecution
32 currently pending
Career history
99
Total Applications
across all art units

Statute-Specific Performance

§101
38.6%
-1.4% vs TC avg
§103
36.2%
-3.8% vs TC avg
§102
10.7%
-29.3% vs TC avg
§112
12.3%
-27.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 67 resolved cases

Office Action

§101 §102 §103
DETAILED ACTION The present office action represents a nonfinal action on the merits. 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 . Priority This application claims the priority date of provisional application 63/558,890 of February 28, 2024. Status of Claims Claims 1-20 are pending. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 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. Claims 1-11 are drawn to method of notifying caretakers of patient's risk of falling or incurring a wound, which is within the four statutory categories (i.e., process). Claims 12-16 are drawn to a system, which is within the four statutory categories (i.e., machine). Claims 17-20 are drawn to a non-transitory computer-readable storage medium storing instructions, which is within the four statutory categories (i.e., machine). Claims 1-11 recite a method of notifying caretakers of patient's risk of falling or incurring a wound, the method comprising: at a computer system having one or more processors and memory storing one or more programs that are executable by the computer system: obtaining historical patient data via one or more databases communicatively coupled with the computer system; generating a training set including a subset of the historical patient data, the training set including one or more features for training an injury detection system; training the injury detection system using the training set, wherein the injury detection system is configured to detect at least a fall risk and/or a wound risk for a patient; determining, based on new patient data provided to the injury detection system, a patient's fall risk and/or wound risk; generating, based on the patient's fall risk and/or wound risk, a patient report; providing caretakers remote access to the patient report, wherein the patient report: presents the patient's fall risk and/or wound risk, and includes one or more user interface elements for receiving additional information about the patient; and in response to receiving a user input via the one or more user interface elements: creating updated patient data, the updated patient data including the new patient data and the information, determining, based on the updated patient data provided to the injury detection system, the patient's updated fall risk and/or updated wound risk, generating, based on the patient's updated fall risk and/or updated wound risk, an updated patient report, and providing a notification to the caretakers, the notification providing the caretakers remote access to the updated patient report, wherein the updated patient report replaces the patient report. Claims 12-16 recite a system, comprising: a memory storing instructions; and one or more processors coupled to the memory resource, the one or more processors being configured to execute the instructions to: obtain historical patient data via one or more databases communicatively coupled with the system; generate a training set including a subset of the historical patient data, the training set including one or more features for training an injury detection system; train the injury detection system using the training set, wherein the injury detection system is configured to detect at least a fall risk and/or a wound risk for a patient; determine, based on new patient data provided to the injury detection system, a patient's fall risk and/or wound risk; generate, based on the patient's fall risk and/or wound risk, a patient report; provide caretakers remote access to the patient report, wherein the patient report: presents the patient's fall risk and/or wound risk, and includes one or more user interface elements for receiving additional information about the patient; and in response to receiving a user input via the one or more user interface elements: create updated patient data, the updated patient data including the new patient data and the information, determine, based on the updated patient data provided to the injury detection system, the patient's updated fall risk and/or updated wound risk, generate, based on the patient's updated fall risk and/or updated wound risk, an updated patient report, and provide a notification to the caretakers, the notification providing the caretakers remote access to the updated patient report, wherein the updated patient report replaces the patient report. Claims 17-20 recite a non-transitory computer-readable storage medium storing instructions that when executed by a processor, causes the processor to: obtain historical patient data via one or more databases communicatively coupled with a computer system; generate a training set including a subset of the historical patient data, the training set including one or more features for training an injury detection system; train the injury detection system using the training set, wherein the injury detection system is configured to detect at least a fall risk and/or a wound risk for a patient; determine, based on new patient data provided to the injury detection system, a patient's fall risk and/or wound risk; generate, based on the patient's fall risk and/or wound risk, a patient report; provide caretakers remote access to the patient report, wherein the patient report: presents the patient's fall risk and/or wound risk, and includes one or more user interface elements for receiving additional information about the patient; and in response to receiving a user input via the one or more user interface elements: create updated patient data, the updated patient data including the new patient data and the information, determine, based on the updated patient data provided to the injury detection system, the patient's updated fall risk and/or updated wound risk, generate, based on the patient's updated fall risk and/or updated wound risk, an updated patient report, and provide a notification to the caretakers, the notification providing the caretakers remote access to the updated patient report, wherein the updated patient report replaces the patient report. The bolded limitations, given the broadest reasonable interpretation, cover a certain method of organizing human activity and/or mathematical concepts, but for the recitation of generic computer components (e.g., a computer system, one or more processors, memory, one or more databases, the memory resource, a system, an injury detection system, etc.). The underlined limitations are not part of the identified abstract idea (the method of organizing human activity or mathematical concepts) and are deemed “additional elements,” and will be discussed in further detail below. Dependent claims 2-11, 13-16, and 18-20 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide an inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination. These limitations only serve to further limit the abstract idea (or contain the same additional elements found in the independent claim), and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 12, and 17. The dependent claims include additional limitations, but these only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 12, and 17. The additional elements from the claims include: a computer system (apply it, MPEP 2106.05(f)). one or more processors (apply it, MPEP 2106.05(f)). memory storing one or more programs that are executable (apply it, MPEP 2106.05(f)). one or more databases (apply it, MPEP 2106.05(f)). an injury detection system (apply it, MPEP 2106.05(f)). one or more user interface elements (apply it, MPEP 2106.05(f)). a system (apply it, MPEP 2106.05(f)). a memory storing instructions (apply it, MPEP 2106.05(f)). the memory resource (apply it, MPEP 2106.05(f)). the one or more processors being configured to execute the instructions (apply it, MPEP 2106.05(f)). a non-transitory computer-readable storage medium storing instructions that when executed by a processor, causes the processor to (apply it, MPEP 2106.05(f)). These additional elements, in the independent claims are not integrated into a practical application because the additional elements (i.e., the limitations not identified as part of the abstract idea) amount to no more than limitations which: Amount to mere instructions to apply an exception – for example, the recitation of a computer system, one or more processors, memory storing one or more programs that are executable, one or more databases, an injury detection system, one or more user interface elements, a system, a memory storing instructions, the memory resource, the one or more processors being configured to execute the instructions, a non-transitory computer-readable storage medium storing instructions, which amounts to merely invoking a computer as a tool to perform the abstract idea e.g., see Specification Paragraphs [0018]-[0022], [0029]-[0030], [0055], and [0080]-[0085] (See MPEP 2106.05(f)). Furthermore, the claims do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because, the additional elements (i.e., the elements other than the abstract idea) amount to no more than limitations which: amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by: The Specification discloses that the additional elements are well-understood, routine, and conventional in nature (i.e., the Paragraphs [0018]-[0022], [0029]-[0030], [0055], and [0080]-[0085] disclose that the additional elements (i.e., a computer system, one or more processors, memory storing one or more programs that are executable, one or more databases, an injury detection system, one or more user interface elements, a system, a memory storing instructions, the memory resource, the one or more processors being configured to execute the instructions, a non-transitory computer-readable storage medium storing instructions) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions that are well understood routine, and conventional activities previously known to the pertinent industry (i.e., a computer); Relevant court decisions: The following example of court decision demonstrating well understood, routine and conventional activities, e.g., see MPEP 2106.05(d)(II): Receiving patient data, e.g., see Intellectual Ventures v. Symantec – similarly, the current invention obtains patient data. Dependent claims 2-11, 13-16, and 18-20 include other limitations, but none of these functions are deemed significantly more than the abstract idea. Thus, taken alone, the additional elements do not amount to “significantly more” than the above identified abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves any other technology, and their collective functions merely provide conventional computer implementation. The application, is an attempt to organize human activity or mathematical concepts, for detecting patients susceptible to falls and wounds and providing notification for preventing or mitigating falls and wounds incurred by the susceptible patients, which is not patentable. Therefore, whether taken individually or as an ordered combination, claims 1-20 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. 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. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1-4, 6, 10-15, and 17-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Main (U.S. Pub. No. 2022/0087617 A1). Regarding claim 1, Main discloses a method of notifying caretakers of patient's risk of falling or incurring a wound, the method comprising (Paragraphs [0006]-[0009] discuss notification generated based on patient pressure injury outcome or fall outcome to healthcare professionals.): at a computer system having one or more processors and memory storing one or more programs that are executable by the computer system (Paragraph [0061] discusses the computing server that executes code instructions to cause one or more processors to perform various processes.): obtaining historical patient data via one or more databases communicatively coupled with the computer system (Paragraphs [0006], [0008], and [0082]-[0083] discuss a database of patient health data and a data store that stores continuous collection of historical patient data.); generating a training set including a subset of the historical patient data, the training set including one or more features for training an injury detection system (Paragraph [0083] discusses the historical patient data may be utilized by one or more machine learning models to train the models to determine pressure injury outcomes and/or fall outcomes for current or future patients.); training the injury detection system using the training set, wherein the injury detection system is configured to detect at least a fall risk and/or a wound risk for a patient (Paragraphs [0009]-[0012] and [0083] discuss historical patient data may be utilized by one or more machine learning models to train the models to determine pressure injury outcomes and/or fall outcomes for current or future patients and the computer predicts a pressure injury outcome and/or a fall outcome based on the pressure data. The pressure injury outcome includes a prediction of risk of the patient developing a pressure injury. The fall outcome includes a prediction of risk of the patient experiencing a fall.); determining, based on new patient data provided to the injury detection system, a patient's fall risk and/or wound risk (Paragraph [0057] discusses the weight support device may generate sensor signals and be in communication with a computer to automatically detect a pressure injury outcome and/or a fall outcome of the person, the pressure readings and other sensor readings (e.g., surface moisture readings), may be provided to a computer with an artificial intelligence system to identify the pressure injury outcome (e.g., a risk of the person developing a pressure injury) or the fall outcome (e.g., a risk of the person falling off of the weight support device).); generating, based on the patient's fall risk and/or wound risk, a patient report (Paragraphs [0093]-[0094], [0145]-[0147], [0169]-[0170] and FIGS. 1B, 6A, 7A, 9B discuss notify/alert nurse of risk of fall or pressure injury and compile compliance reports related to pressure injury outcomes and/or fall outcomes of patient(s).); providing caretakers remote access to the patient report, wherein the patient report (Paragraphs [0147], [0151], [0176] discuss computer (e.g., the local computer, the user device, and/or the management device) can display the graphical user interface (GUI) inform the healthcare professional and/or other caregiver via an alert or notification about patient risk of developing pressure injury and/or fall injury.): presents the patient's fall risk and/or wound risk, and includes one or more user interface elements for receiving additional information about the patient (Paragraphs [0153], [0159], [0170], and FIGS. 6A, 9B discuss the fall outcome includes a risk of the person developing a pressure injury and/or falling off of the weight support device and/or an indication that the person experienced a fall (that a fall occurred) is communicated to a user (e.g., a healthcare professional, a caregiver, the person, etc.) via a notification displayed in a graphical user interface.); and in response to receiving a user input via the one or more user interface elements (Paragraphs [0075] and [0079] discuss receive patient inputs include at least the raw sensor data measured by the pressure sensing elements, raw sensor data measured by the surface moisture sensing elements, raw surface temperature data generated from the thermistors, a health record of an individual, sensor data from the hand-held sensors (e.g., moisture data from a hand-held edema sensor), any additional information input by a user (e.g., results of a blanch test), information from the sensor mapping engine, and information from the machine visions engine.): creating updated patient data, the updated patient data including the new patient data and the information, determining, based on the updated patient data provided to the injury detection system, the patient's updated fall risk and/or updated wound risk, generating, based on the patient's updated fall risk and/or updated wound risk, an updated patient report, and providing a notification to the caretakers, the notification providing the caretakers remote access to the updated patient report, wherein the updated patient report replaces the patient report (Paragraphs [0006], [0148], [0151]-[0153], and [0155] discuss the computer monitors continuous collection of patient data and time progress tracker tracks the poses and positions of the person over time, display turns and other position adjustments of the person as a timeline, and be interactive, for example, a user (e.g., the person or a healthcare provider) may rewind to a particular time instance and the heatmap will depict various information about the person and the weight support device at the particular time instance.). Regarding claims 2, 13, and 18 Main discloses wherein: the new patient data includes respective patient data for a plurality of patients (Paragraph [0006] discusses continuous patient monitoring and continuous collection of patient data and a high-resolution visualization of areas of high pressure, the patient monitoring solution helps clinicians improve patient safety, clinicians and patients are provided visual, easy-to-understand pressure images that identify areas that are experiencing elevated pressures.); a respective patient's fall risk and/or wound risk is determined for each patient of the plurality of patients using the injury detection system and based on the respective patient data for the plurality of patients (Paragraphs [0083] and [0089] discuss the data store may store historical patient data that includes health record data, sensors data, and analysis results for patients to be utilized by one or more machine learning models to train the models to determine pressure injury outcomes and/or fall outcomes for current or future patients, then the system monitors and tracks the pressure injury outcomes regarding risk of pressure injury.); and a respective patient report is generated for each patient of the plurality of patients (Paragraphs [0153], [0169]-[0170], and FIG. 7C discuss the GUI may present a visual representation of the person with certain body parts labeled with an amount of time until a pressure injury may occur at that particular body part, determine a risk of fall outcome that may be communicated to a user (e.g., a healthcare professional, a caregiver, the person, etc.) via a notification displayed in a graphical user interface.).). Regarding claim 3, Main discloses further comprising: determining, using the injury detection system, a human-readable explanation for the patient's fall risk (Paragraph [0086] discusses interface may include various visualizations and graphical elements to display notifications and/or information to users, a GUI which includes graphical elements to display a digital heatmap, other pressure injury-related information, or other fall-related information.); determining, using the injury detection system, a human-readable explanation for the patient's wound risk (Paragraph [0147] discusses the GUI may display information related to the positioning (e.g., related to a pose) of the person, such as a side label, display one or more symbols (e.g., circles of different sizes, colors, etc.) that are used to represent specific areas of the heatmap, the specific areas may include body parts (e.g., joint locations), areas of surface moisture, areas of high surface temperature, areas of the person at risk of developing pressure injury, or any combination thereof, detected by the computer.); and wherein the patient report includes the human-readable explanation for the patient's fall risk and the human-readable explanation for the patient's wound risk (Paragraphs [0086], [0147], [0151], [0153], and [0164] discuss interface may include various visualizations and graphical elements to display notifications and/or information to users, a GUI which includes graphical elements to display a digital heatmap, other pressure injury-related information, or other fall-related information, for example, the GUI includes a heatmap that depict pressure data for the person, surface moisture data of the weight support device, surface temperature data of the person and/or weight support device, area(s) of the person at risk of a pressure injury, or any combination thereof to the healthcare provider or caregiver; notification may include an alert or message to a user (e.g., a nurse) that the person supported by the weight support device is at risk of falling off of the weight support device, which side(s) of the weight support device the person is at risk of falling off of and/or a recommendation for how best to adjust a positioning of the person to avoid the fall..). Regarding claim 4, Main discloses further comprising: determining, using the injury detection system, a first plurality of factors contributing to the patient's fall risk (Paragraphs [0162] and [0165] discuss computer predicts fall risk, based on the pressure data recommendations regarding position adjustments of the person may be based on tracked sensor data, for example, if the person consistently lays on a particular edge of the weight support device.); determining, using the injury detection system, a second plurality of factors contributing to the patient's wound risk (Paragraph [0147] discusses the GUI includes a heatmap corresponding to a person supported by a weight support device and depict pressure data for the person, surface moisture data of the weight support device, surface temperature data of the person and/or weight support device, area(s) of the person at risk of a pressure injury, or any combination thereof.); and wherein the patient report includes the first plurality of factors and the second plurality of factors (Paragraphs [0147]-[0149] and [0164] discuss the GUI includes circles that represent the areas of the person at risk of developing pressure injury, for example, a circle may be in a first color (e.g., yellow) for a certain amount of pressure and may turn to a second color (e.g., red) if the amount of pressure detected at the body part exceeds a threshold pressure amount; the computer displays a notification, alert or message to a user (e.g., a nurse) that the person supported by the weight support device is at risk of falling off of the weight support device, which side(s) and/or a recommendation for how best to adjust a positioning of the person to avoid the fall.). Regarding claim 6, Main discloses further comprising: determining, using the injury detection system, one or more first mitigating suggestions for ameliorating the patient's fall risk (Paragraphs [0162] and [0165] discuss computer predicts, based on the pressure data recommendations regarding position adjustments of the person may be based on tracked sensor data, the computer may recommend via the notification that one or more pillows or bolsters be placed on that edge to prevent the person from falling off that edge of the weight support device.); determining, using the injury detection system, one or more second mitigating suggestions for ameliorating the patient's wound risk (Paragraphs [0093] and [0129] discuss the cloud actionable insight system provides notifications and recommendations to the patient or other caregiver to position the patient in a pose to allow the patient's body parts that were at risk of developing pressure injury to recover.); and wherein the patient report includes the first mitigating suggestions and the second mitigating suggestions for the patient's fall risk, respectively (Paragraphs [0164]-[0165] discuss the computer displays a notification, alert or message to a user (e.g., a nurse) that the person supported by the weight support device is at risk of falling off of the weight support device, which side(s) and/or a recommendation for how best to adjust a positioning of the person to avoid the fall, recommend one or more pillows be placed on that edge to prevent the person from falling.). Regarding claim 10, Main discloses further comprising: in response to detection of a triggering event associated with a respective patient, providing another notification to the caretakers, the other notification providing the caretakers remote access to a respective patient report (Paragraphs [0006], [0147], [0151], [0176] discuss clinicians and patients are provided visual, easy-to-understand pressure images that identify areas that are experiencing elevated pressures so that body position adjustments can be made efficiently and effectively, the computer (e.g., the local computer, the user device, and/or the management device) can display the graphical user interface (GUI) inform the healthcare professional and/or other caregiver via an alert or notification about patient risk of developing pressure injury and/or fall injury.). Regarding claim 11, Main discloses wherein the triggering event includes a fall risk above a predetermined fall risk threshold, a wound risk above a predetermined wound risk threshold, and an update to a patient report (Paragraphs [0071] discuss if the pressure sensing points in the contact area above a minimum pressure threshold show little variation over a period of time, then the person can be considered motionless. A variation threshold of 10% to 100% of the measured pressure can be used to determine if there is movement on a particular sensing point or group of sensing points.). Regarding claim 12, Main discloses a system, comprising: a memory storing instructions (Paragraph [0204] discusses instructions reside in the memory.); and one or more processors coupled to the memory resource, the one or more processors being configured to execute the instructions to (Paragraph [0204] discusses instructions within the main memory or within the processor during execution thereof by the computer system.): Claim 12 discloses substantially the same limitations as Claim 1 and is rejected for similar reasons. Regarding claims 14 and 19, Main discloses wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Paragraph [0204] discusses instructions within the main memory or within the processor during execution thereof by the computer system.). Claims 14 and 19 disclose substantially the same limitations as Claim 3 and are rejected for similar reasons. Regarding claims 15 and 20, Main discloses wherein the instructions, when executed by the one or more processors, further cause the one or more processors to (Paragraph [0204] discusses instructions within the main memory or within the processor during execution thereof by the computer system.): Claims 15 and 20 disclose substantially the same limitations as Claim 4 and are rejected for similar reasons. Regarding claim 17, Main discloses a non-transitory computer-readable storage medium storing instructions that when executed by a processor, causes the processor to (Paragraphs [0081] and [0204] discuss the storage unit includes a non-transitory computer-readable medium on which is stored instructions.): Claim 17 discloses substantially the same limitations as Claim 1 and is rejected for similar reasons. 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 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 5, 7, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Main in view of Bly (U.S. Pub. No. 2022/0071551 A1). Regarding claims 5 and 16, Main does not explicitly disclose wherein factors of the first plurality of factors and the second plurality of factors are ranked from highest contributing factor to least contributing factor. Bly teaches: wherein factors of the first plurality of factors and the second plurality of factors are ranked from highest contributing factor to least contributing factor (Paragraphs [0094]-[0100] discuss factors can be considered in determining the POP Box Score, for example, one factor can be nutritional status and the presence of a feeding tube can be a rating of 1 with the absence of a feeding tube being a rating of 0, the factor can be weighted differently in determining the score.). Therefore, it would have been obvious to one of ordinary skill in the art to modify Main to include, wherein factors of the first plurality of factors and the second plurality of factors are ranked from highest contributing factor to least contributing factor, as taught by Bly, in order to provide a more extensive system than currently used and that is inclusive of interrelated variables that can effect integrity of skin or rather the impairment of skin integrity. (Bly Paragraph [0007]). Regarding claim 7, Main discloses wherein mitigating suggestions of the first mitigating suggestions and the second mitigating suggestions are provided (Paragraphs [0093], [0129], [0162], and [0165] discuss recommendations regarding position adjustments of the person may be based on tracked sensor data, one or more pillows or bolsters be placed on that edge to prevent the person from falling off that edge of the weight support device, recommendations to position the patient in a pose to allow the patient's body parts that were at risk of developing pressure injury to recover.). Main does not explicitly disclose: mitigating suggestions are ranked from highest contributing factor to least contributing factor. Bly teaches: mitigating suggestions are ranked from highest contributing factor to least contributing factor (Paragraphs [0094]-[0100] discuss factors can be considered in determining the POP Box Score, for example, the presence of a feeding tube can be a rating of 1 with the absence of a feeding tube being a rating of 0, the factor can be weighted differently in determining the score.). Therefore, it would have been obvious to one of ordinary skill in the art to modify Main to include, mitigating suggestions are ranked from highest contributing factor to least contributing factor, as taught by Bly, in order to provide a more extensive system than currently used and that is inclusive of interrelated variables that can effect integrity of skin or rather the impairment of skin integrity. (Bly Paragraph [0007]). Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Main in view of Kurfirst (U.S. Pub. No. 2022/0157144 A1). Regarding claim 8, Main discloses further comprising: in response to obtaining updated historical patient data via the one or more databases communicatively coupled with the computer system (Paragraphs [0006], [0008], and [0082]-[0083] discuss a database of patient health data and a data store that stores continuous collection of historical patient data.): generating a training set including a subset of the historical patient data, the training set including the one or more features for training an updated injury detection system (Paragraphs [0082]-[0083] discuss data store may receive data for the computing server to continuously monitor the pressure readings related to the patient and store sensor data received from the hand-held sensors, the data store may store historical patient data that includes health record data, sensors data, and analysis results for patients that have historically been supported by the weight support device. The historical patient data may be utilized by one or more machine learning models to train the models to determine pressure injury outcomes and/or fall outcomes for current or future patients.). Main does not explicitly disclose: an updated training set including an updated subset of the historical patient data, the updated training set including the one or more features for training an updated injury detection system; training the updated injury detection system using the updated training set; and replacing the injury detection system with the updated injury detection system Kurfirst teaches: an updated training set including an updated subset of the historical patient data, the updated training set including the one or more features for training an updated injury detection system (Paragraphs [0090] discuss train and update machine learning dataset, the enterprise computing system may obtain data such as the indication of an individual falling, the location (e.g., geographical location) where the fall occurred, one or more medications taken by the individual, and/or a date/time stamp associated with the individual falling.). training the updated injury detection system using the updated training set (Paragraph [0090] discusses the enterprise computing system may use any type of machine learning dataset and/or algorithm to determine a causation event/cause of the individual falling and may train and/or update this machine learning dataset and/or algorithm.); and replacing the injury detection system with the updated injury detection system (Paragraph [0090] discusses the enterprise computing system may use any type of machine learning dataset and/or algorithm to determine a causation event/cause of the individual falling and may train and/or update this machine learning dataset and/or algorithm; after training the dataset, the enterprise computing system may test the trained model using the test data and perform another continuous or discreet analysis and render a decision.). Therefore, it would have been obvious to one of ordinary skill in the art to modify Main to include, an updated training set including an updated subset of the historical patient data, the updated training set including the one or more features for training an updated injury detection system, training the updated injury detection system using the updated training set, and replacing the injury detection system with the updated injury detection system, as taught by Kurfirst, in order to provide a system that uses devices to detect an occurrence of a fall as well as to improve the response time if/when a fall occurs. (Kurfirst Paragraph [0002]). Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Main in view of Amarasingham (U.S. Pub. No. 2015/0213225 A1). Regarding claim 9, Main discloses wherein the patient report includes a patient information indicating the patient's respective fall risk and/or wound risk (Paragraphs [0147], [0151], [0176] discuss computer (e.g., the local computer, the user device, and/or the management device) can display the graphical user interface (GUI) inform the healthcare professional and/or other caregiver via an alert or notification about patient risk of developing pressure injury and/or fall injury.). Main does not explicitly disclose: a patient rank indicating the patient's respective fall risk and/or wound risk in relation to other patients. Amarasingham teaches: a patient rank indicating the patient's respective fall risk and/or wound risk in relation to other patients (Paragraph [0062] discusses the module may rank the patients according to the risk scores, and provide a sortable list.). Therefore, it would have been obvious to one of ordinary skill in the art to modify Main to include, a patient rank indicating the patient's respective fall risk and/or wound risk in relation to other patients, as taught by Amarasingham, in order to provide timely identification of disease and appropriate engagement of patients and families required to offer patients appropriate care and treatment in order to avoid the progression of existing disease as well as the occurrence of a new adverse event, as well as to ensure that appropriate interventions and resources are available and deployed according to patients' needs. (Amarasingham Paragraph [0011]). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAWN TRINAH HAYNES whose telephone number is (571)270-5994. The examiner can normally be reached M-F 7:30-5:15PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Dunham can be reached on (571)272-8109. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /DAWN T. HAYNES/ Art Unit 3686 /RACHELLE L REICHERT/Primary Examiner, Art Unit 3686
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Prosecution Timeline

Feb 27, 2025
Application Filed
Mar 05, 2026
Non-Final Rejection — §101, §102, §103 (current)

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Study what changed to get past this examiner. Based on 2 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
2%
Grant Probability
5%
With Interview (+3.5%)
4y 7m
Median Time to Grant
Low
PTA Risk
Based on 67 resolved cases by this examiner. Grant probability derived from career allow rate.

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