Patent Description:
When the patient's vital signs are improving or deteriorating, an alarm is often manually reset according to newly established baselines for the patient. This requires additional action from clinicians, which can be labor-intensive and time consuming. When an alarm is not appropriately reset, often the alarm is repeatedly triggered, which can lead to alarm fatigue.

Additionally, clinicians are often unable to determine whether an alarm is triggered due to patient deterioration, or due to administered medications, treatments, and noise artifacts. This can lead to confusion regarding the need to respond to the alarm, and further alarm fatigue.

<CIT> describes monitoring physiological parameters of a patient. A threshold limit is set, automatically or manually, and the monitored parameter is continuously compared to the threshold limit, which may be constant of may vary with time. An alarm is triggered if the monitored parameter exceeds the threshold limit at any time, or if the monitored parameter has not reached a target value by the end of a predefined time period by which an administered drug or therapy should have been effective.

<CIT> describes a method and system for providing health-monitoring alarm management. The method comprises detecting at least one vital sign signal using a wearable sensor device and managing an alarm mechanism of the wearable sensor device based on the at least one vital sign signal. The system comprises a sensor for detecting at least one vital sign signal, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to manage an alarm mechanism of the wearable sensor device based on the at least one vital sign signal.

In general terms, the present disclosure relates to vital sign alarms and visualizations. In one possible configuration, a monitor device provides self-adjusting upper and lower alarm limits that can more accurately monitor a patient's measured vital signs, and reduce alarm fatigue. The monitor device can further provide enhanced visualization of the measured vital signs that can boost confidence in their accuracy, and help aid clinicians make decisions such as whether to intervene or adjust one or more alarm settings. Various vital signs can be monitored in accordance with implementations of the present disclosure. For instance, at least one of heart rate, blood pressure, blood oxygen saturation percentage, respiration rate, electrocardiogram, and end tidal carbon dioxide (etCO2) can be monitored. Various aspects are described in this disclosure, which include, but are not limited to, the following aspects.

In one aspect, a device for monitoring a physiological variable comprises: at least one processing device; and a memory device storing instructions which, when executed by the at least one processing device, cause the device to: determine a starting value for a self-adjusting alarm limit based on an abnormal state of the physiological variable; determine a new value for the self-adjusting alarm limit from physiological data values received during a time window; and when the new value for the self-adjusting alarm limit moves in a targeted direction, reset the self-adjusting alarm limit at the new value.

In another aspect, a method of continuous physiological monitoring comprises: determining a starting value for a self-adjusting alarm limit based on an abnormal state of the physiological variable; determining a new value for the self-adjusting alarm limit from physiological data values received during a time window; resetting the self-adjusting alarm limit at the new value when the new value for the self-adjusting alarm limit moves in a targeted direction; and triggering an alarm when the new value for the self-adjusting alarm limit moves in a direction opposite of the targeted direction.

In another aspect, not part of the invention, a device for monitoring a physiological variable comprises: at least one processing device; and a memory device storing instructions which, when executed by the at least one processing device, cause the device to: receive physiological data values from a physiological sensor; receive artifact data including audio signals captured from an audio sensor; process the audio signals to determine one or more artifacts; and display the physiological data values to distinguish values effected by the one or more artifacts from values not effected by the one or more artifacts.

In another aspect, not part of the invention, a device for monitoring a physiological variable comprises: at least one processing device; and a memory device storing instructions which, when executed by the at least one processing device, cause the device to: receive physiological data values from a physiological sensor; receive a treatment event; determine an expected effect of the treatment event on the physiological data values, the expected effect being a targeted effect or a side effect; display the treatment event overlayed on the physiological data values; display a normal range overlayed on the physiological data values, the normal range having a first set of upper and lower limits; and display a modified range overlayed over the physiological data values, the modified range having a second set of upper and lower limits that are based on the expected effect of the treatment event.

<FIG> illustrates an example of a monitoring system <NUM> for monitoring vital signs of a patient P who is shown resting on a patient support system <NUM>. The monitoring system <NUM> includes the patient support system <NUM>, as well as a monitor device <NUM>, a motion sensor <NUM>, and a physiological sensor <NUM>, which are all shown inside an area <NUM>. In some examples, the area <NUM> is a patient room, a pre-operative or post-operative holding area, an operating room, a waiting room, or other type of area within a healthcare facility such as a hospital, a surgical center, a nursing home, a long term care facility, or similar type of facility.

The patient P is a person, such as a patient, who is being clinically treated by one or more clinicians in the area <NUM>. Examples of clinicians include primary care providers (e.g., doctors, nurse practitioners, and physician assistants), nursing care providers (e.g., nurses), specialty care providers (e.g., professionals in various specialties), and health professionals that provide preventive, curative, promotional and rehabilitative health care services.

In the example shown in <FIG>, the patient support system <NUM> is a hospital bed. In other examples, the patient support system <NUM> is another type of bed, lift, chair, wheelchair, stretcher, surgical table, and the like, which can support the patient P in the area <NUM>.

The monitor device <NUM> is connected to the physiological sensor <NUM>, and includes a display device <NUM> for displaying physiological data acquired from the physiological sensor <NUM>. The physiological sensor <NUM> communicates wirelessly or via wired connection with the monitor device <NUM>. The monitor device <NUM> may also communicate with one or more additional sensing devices in the area <NUM>, including the patient support system <NUM> and the motion sensor <NUM>.

The monitor device <NUM> may be any suitable type of monitoring device. <FIG> illustrates the monitor device <NUM> as a multi-parameter device which displays multiple parameters on the display device <NUM>. The multiple parameters are detected from the physiological sensor <NUM> and from other sensing devices inside the area <NUM>. In alternative examples, the monitor device <NUM> may be a single-parameter device, such as an ECG monitor.

Examples of the physiological sensor <NUM> include an electrocardiogram (ECG) sensor, a blood oxygen saturation/pulse oximeter (SpO2) sensor, a blood pressure sensor, a heart rate sensor, a respiration rate sensor, an end tidal carbon dioxide (etCO2) sensor, and the like. The physiological sensor <NUM> can also combine two or more sensors in a single sensor device.

As shown in <FIG>, the monitor device <NUM> communicates with a server <NUM> via a communications network <NUM>. The server <NUM> operates to manage the patient P's medical history and information. The server <NUM> can be operated by a healthcare service provider, such as a hospital or medical clinic. The monitor device <NUM> sends physiological data acquired from the physiological sensor <NUM> to the server <NUM> via the connection to the communications network <NUM>. In at least some examples, the server <NUM> is a cloud server or similar type of server.

The server <NUM> can include an electronic medical record (EMR) system <NUM> (alternatively termed electronic health record (EHR)). Advantageously, the server <NUM> can automatically store the physiological data acquired from the monitor device <NUM> in an electronic medical record <NUM> or electronic health record of the patient P located in the EMR system <NUM> via the connection with the monitor device <NUM> over the communications network <NUM>.

The server <NUM> can also include an electronic medication administration records (EMAR) system <NUM>. The monitor device <NUM> can communicate with the EMAR system <NUM> via the connection to the communications network <NUM> to obtain access to a medication record <NUM> of the patient P that includes medications and time stamps when administered to the patient P.

In the example shown in <FIG>, the motion sensor <NUM> is a motion sensor positioned below, within, or on top of a mattress <NUM> of the patient support system <NUM>. The motion sensor <NUM> can include piezoelectric sensors, load cells, or combinations thereof that detect movements of the patient P while the patient P is supported on the patient support system <NUM>.

In alternative examples, the motion sensor <NUM> may be an accelerometer attached to the patient P, or incorporated into the physiological sensor <NUM> and/or into one or more other sensing devices that are attached to the patient P. In such examples, physiological sensing and motion detection functions are combined in one device. Multiple such devices may be used on the patient P. For example, a combined ECG/motion detection device and/or a combined pulse oximetry/motion detection device may be used on the patient P at the same time.

The motion sensor <NUM> detects motion by the patient P, which can affect or influence the heart rate, blood pressure, and respiration rate data sensed by the physiological sensor <NUM>. The motion sensor <NUM> senses motion by the patient P (for example by using piezoelectric or load cell sensors positioned below, within, or on top of a mattress <NUM> or accelerometers attached to the patient P), and transmits the sensed motion data to the monitor device <NUM> while the physiological sensor <NUM> senses physiological data such as the heart rate, blood pressure, or respiration rate of the patient P, and transmits the physiological data to the monitor device <NUM>.

The monitor device <NUM> processes the data from the motion sensor <NUM> to identify when the patient P is moving. The monitor device <NUM> can then flag the physiological data that was measured when the patient P was moving. For example, the monitor device <NUM> can display the physiological data that was acquired when the patient P was moving differently from when the patient P was not moving to aid a clinician's assessment of the patient P.

The communications network <NUM> communicates data between one or more devices, such as between the monitor device <NUM> and the server <NUM>. In some examples, the communications network <NUM> may also be used to communicate data between one or more devices inside the area <NUM> such as between the patient support system <NUM>, monitor device <NUM>, motion sensor <NUM>, physiological sensor <NUM>, and other sensor devices inside the area <NUM>.

The communications network <NUM> can include any type of wired or wireless connections or any combinations thereof. Examples of wireless connections include broadband cellular network connections such as <NUM> or <NUM>. In some examples, wireless connections are also accomplished using Wi-Fi, ultra-wideband (UWB), Bluetooth, radio frequency identification (RFID), and similar types of wireless connections.

<FIG> illustrates an example of an audio sensor <NUM> that may also be a part of the monitoring system <NUM>. In the example shown in <FIG>, the audio sensor <NUM> is attached to an apparatus <NUM> connected to the patient P. The apparatus <NUM> can be a nasal cannula, a tracheal intubation tube, a face mask, a capnography monitor, or similar device such that the audio sensor <NUM> is positioned near to the patient P's mouth or chest. Alternatively, the audio sensor <NUM> can be attached directly to the patient P, or to another object near the patient P.

In the example shown in <FIG>, the physiological sensor <NUM> is also attached to the apparatus <NUM>. In this example, the physiological sensor <NUM> is a capnography sensor that can be used to measure the etCO2 and respiration rate of the patient P.

The audio sensor <NUM> captures audio sounds that can be used to detect when the patient P is coughing, talking, and eating, which can affect or influence the respiration rate and etCO2 data sensed by the physiological sensor <NUM>. The audio sensor <NUM> captures audio data by the patient P, and transmits the audio data to the monitor device <NUM>. Additionally, the physiological sensor <NUM> acquires etCO2 and respiration rate data of the patient P, and transmits the etCO2 and respiration rate data to the monitor device <NUM>.

The monitor device <NUM> processes the audio data from the audio sensor <NUM> to identify when the patient P is coughing, talking, and eating. The monitor device <NUM> can then flag the etCO2 and respiration rate data that was measured when the patient P was coughing, talking, and eating. For example, the monitor device <NUM> can display the etCO2 and respiration rate data that was acquired during coughing, talking, or eating differently from when the patient P was not coughing, talking, or eating to aid a clinician's assessment of the patient P.

<FIG> schematically illustrates an example of the monitoring system <NUM>. The monitor device <NUM> includes a computing device <NUM> having at least one processing device <NUM> and a memory device <NUM>. The at least one processing device <NUM> is an example of a processing unit such as a central processing unit (CPU). The at least one processing device <NUM> can include one or more CPUs. The at least one processing device <NUM> can include one or more digital signal processors, field-programmable gate arrays, or other electronic circuits.

The memory device <NUM> operates to store data and instructions for execution by the at least one processing device <NUM>, including an alarm application <NUM> and a visualization application <NUM>, which will both be described in more detail below. The memory device <NUM> includes computer-readable media, which may include any media that can be accessed by the monitor device <NUM>. By way of example, computer-readable media include computer readable storage media and computer readable communication media.

Computer readable storage media includes volatile and nonvolatile, removable and non-removable media implemented in any device configured to store information such as computer readable instructions, data structures, program modules, or other data. Computer readable storage media can include, but is not limited to, random access memory, read only memory, electrically erasable programmable read only memory, flash memory, and other memory technology, including any medium that can be used to store information that can be accessed by the monitor device <NUM>. The computer readable storage media is non-transitory.

Computer readable communication media embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term "modulated data signal" refers to a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, computer readable communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency, infrared, and other wireless media. Combinations of any of the above are within the scope of computer readable media.

The monitor device <NUM> further includes a sensor interface <NUM> that operates to communicate with the various sensors of the monitoring system <NUM>. The sensor interface <NUM> can include both wired interfaces and wireless interfaces. The motion sensor <NUM>, physiological sensor <NUM>, and audio sensor <NUM> can wirelessly connect to the sensor interface <NUM> through Wi-Fi, ultra-wideband (UWB), Bluetooth, and similar types of wireless connections. Alternatively, the motion sensor <NUM>, physiological sensor <NUM>, and audio sensor <NUM> can be connected to the monitor device <NUM> using wired connections that plug into the sensor interface <NUM>.

As shown in <FIG>, the monitor device <NUM> includes the display device <NUM>, which operates to display a user interface <NUM>. In some examples, the display device <NUM> is a touchscreen such that the user interface <NUM> operates to receive inputs from a clinician. In such examples, the display device <NUM> operates as both a display device and a user input device. The monitor device <NUM> can also support physical buttons on a housing of the device that operate to receive inputs from the clinician to control operation of the monitor device and enter data.

<FIG> schematically illustrates an example of the alarm application <NUM> installed on the monitor device <NUM>. The alarm application <NUM> includes a normal alarm mode <NUM> and a crisis alarm mode <NUM>. A clinician can select either the normal alarm mode <NUM> or the crisis alarm mode <NUM> when operating the monitor device <NUM>. When the display device <NUM> is a touchscreen, the clinician can select the normal alarm mode <NUM> or the crisis alarm mode <NUM> on the display device <NUM>. Alternatively, the clinician can select one or more user input buttons on the monitor device <NUM> to select the normal alarm mode <NUM> or the crisis alarm mode <NUM>.

The normal alarm mode <NUM> is a mode of operation where fixed upper and lower alarm limits are set for the physiological data sensed from the physiological sensor <NUM>. In the normal alarm mode <NUM>, an alarm is triggered when the physiological data is above the upper alarm limit, or is below the lower alarm limit. Illustrative examples of the alarm include a local alarm on the monitor device <NUM> such as a visual alarm (e.g., blinking red light) and/or an audible alarm (e.g., beeping noise), and/or may also include notifications sent to mobile devices carried by clinicians (e.g., smartphones), and/or notifications sent to a nurses' station.

In the normal alarm mode <NUM>, the upper and lower alarm limits are based on normal or default values. As an illustrative example, a normal resting blood pressure for human adults is approximately <NUM>/<NUM> mmHg, a high blood pressure for human adults is considered to be <NUM>/<NUM> mmHg or higher, and a low blood pressure for human adults is considered to be <NUM>/<NUM> mmHg or lower. When monitoring the blood pressure of the patient P under the normal alarm mode <NUM>, an upper alarm limit can be set at <NUM>/<NUM> mmHg and a lower alarm limit can be set at <NUM>/<NUM> mmHg. When the blood pressure of the patient P is above <NUM>/<NUM> mmHg an alarm is triggered. Also, when the blood pressure of the patient P is below <NUM>/<NUM> mmHg, an alarm is triggered.

In some examples, the upper and lower alarm limits are automatically set by the alarm application <NUM> based on demographic data of the patient P, including the age and gender of the patient P, by acquiring the demographic data from the electronic medical record <NUM> in the EMR system <NUM> via the communications network <NUM>. Alternatively, the clinician can manually set the upper and lower alarm limits based on the demographic data of the patient P.

In some examples, the upper and lower alarm limits in the normal alarm mode <NUM> are set by the alarm application <NUM> or the clinician according to personalized baselines of the patient P. For example, when the patient P is known to have a pre-existing condition that causes low blood pressure, the lower alarm limit for blood pressure can be set lower than <NUM>/<NUM> mmHg. Similarly, when the patient P is known to have a pre-existing condition that causes high blood pressure, the upper alarm limit for blood pressure can be set higher than <NUM>/<NUM> mmHg.

In certain scenarios, it may be desirable to monitor physiological data of the patient P based on the patient P's progress during treatment. As an illustrative example, sepsis can cause the patient P to have low blood pressure. In response to a sepsis diagnosis, a clinician can intervene by administering a vasopressor medication to raise the blood pressure of the patient P. The clinician will then closely monitor the patient P to make sure that their blood pressure is increasing. As long as the blood pressure of the patient P is increasing, there is no cause for alarm. However, in such a scenario, fixed upper and lower alarm limits can lead to alarm fatigue because the lower alarm limit will be continuously triggered until the patient P's blood pressure stabilizes. In some instances, the clinician may decide to turn off the alarm which is undesirable. Alternatively, the clinician can manually reset the lower alarm limit as the condition of the patient P improves, however, this is labor-intensive and can lead to clinician burnout. Thus, fixed upper and lower alarm limits may be undesirable in such a scenario.

The crisis alarm mode <NUM> self-adjusts an upper or lower alarm limit in a targeted direction <NUM> until exit criteria <NUM> are met. A clinician can select the crisis alarm mode <NUM> when the patient P is receiving treatment that causes the data from the physiological sensor <NUM> to change in the targeted direction <NUM>. When the exit criteria <NUM> are met, the crisis alarm mode <NUM> ends and the alarm application <NUM> returns to the normal alarm mode <NUM>.

As shown in <FIG>, the targeted direction <NUM> can include an increasing targeted direction <NUM> or a decreasing targeted direction <NUM>. As an illustrative example, the increasing targeted direction <NUM> is selected when vasopressor medication is administered to raise the blood pressure of the patient P. As another illustrative example, the decreasing targeted direction <NUM> is selected when a medication or treatment is provided to decrease the heart rate of the patient P.

An alarm is triggered in the crisis alarm mode <NUM> when the physiological data values from the physiological sensor <NUM> move in a direction opposite of the targeted direction <NUM>. For example, an alarm is triggered when the increasing targeted direction <NUM> is selected and the physiological data values are decreasing. As another example, an alarm is triggered when the decreasing targeted direction <NUM> is selected and the physiological data values are increasing.

Additional types of targeted direction may also include recovery trend lines, curves, and the like. In such examples, an alarm is triggered in the crisis alarm mode <NUM> when a predetermined distance from the selected recovery trend line or curve is detected.

The targeted direction <NUM> can be automatically selected by the alarm application <NUM>, such as by using an algorithm that determines the targeted direction <NUM> based on the status or condition of the patient P (e.g., patient P is septic), and the medications and/or treatment provided to the patient P (e.g., (vasopressor medication administered to patient P). This information can be acquired by the alarm application <NUM> from the electronic medical record <NUM> of the patient P in the EMR system <NUM> via the communications network <NUM>.

Alternatively, the targeted direction <NUM> can be selected by the clinician. For example, in embodiments where the display device <NUM> is a touchscreen, the clinician can select the targeted direction <NUM> using the display device <NUM>. Alternatively, the clinician can select one or more user input buttons on the monitor device <NUM> to select the targeted direction <NUM>.

The exit criteria <NUM> can include a target value <NUM> and a time limit <NUM>. In some examples, only the target value <NUM> is selected for determining when the crisis alarm mode <NUM> ends. In alternative examples, both the target value <NUM> and the time limit <NUM> are selected.

The target value <NUM> is a physiological measurement that is within a normal range, such as one based on the demographics of the patient P (e.g., a blood pressure between <NUM>/<NUM> mmHg and <NUM>/<NUM> mmHg for adult humans). When the target value <NUM> is reached, the crisis alarm mode <NUM> ends, and the alarm application <NUM> returns to the normal alarm mode <NUM>.

The time limit <NUM> is a predetermined time that is set based on the condition, medications, or treatment of the patient P. For example, the time limit <NUM> can be set for <NUM> hour after a medication has been administered. In some examples, the crisis alarm mode <NUM> ends when the target value <NUM> is satisfied or the time limit <NUM> is satisfied, whichever occurs first. Alternatively, the crisis alarm mode <NUM> ends when both the target value <NUM> and the time limit <NUM> are satisfied. In some examples, the exit criteria <NUM> are selected such that the target value <NUM> must be reached within the time limit <NUM>, in order for the crisis alarm mode <NUM> to end.

The exit criteria <NUM> can be automatically set by the alarm application <NUM> based on the demographic data, health status, diagnoses, medications, and/or treatments administered to the patient P. The alarm application <NUM> can acquire this information from the electronic medical record <NUM> of the patient P through access to the EMR system <NUM> via the communications network <NUM>. Alternatively, the exit criteria <NUM> can be manually set by the clinician using the display device <NUM> or one or more user input buttons on the monitor device <NUM>.

As shown in <FIG>, the crisis alarm mode <NUM> further includes a sensitivity level <NUM> that is adjustable for the self-adjustment of an upper or lower alarm limit in the targeted direction <NUM>. For example, the sensitivity level <NUM> can be selected between high, medium, and low levels of sensitivity. The sensitivity level <NUM> can be automatically set by the alarm application <NUM> based on the demographic data, health status, diagnoses, medications, and/or treatments of the patient P. Alternatively, the sensitivity level <NUM> can be manually set by the clinician using the display device <NUM> or one or more user input buttons on the monitor device <NUM>.

<FIG> illustrates an example of the crisis alarm mode <NUM> applied to a chart <NUM> for monitoring a vital sign. In the example shown in <FIG>, the monitored vital sign is blood pressure, and the chart <NUM> includes a normal resting value <NUM> set at <NUM>/<NUM> mmHg, an upper alarm limit <NUM> set at <NUM>/<NUM> mmHg, and a lower alarm limit <NUM> set at <NUM>/<NUM> mmHg. The blood pressure of the patient is represented by trend line <NUM>. In this example, the patient is experiencing an abnormally low blood pressure (e.g., due to sepsis), and a treatment is administered to the patient (e.g., vasopressor medication) at a time of treatment T<NUM> to raise their blood pressure to a target value between the upper and lower alarm limits <NUM>, <NUM>.

As shown in <FIG>, a self-adjusting lower alarm limit <NUM> is initially set at a starting value X<NUM> based on an abnormal state of the blood pressure before the time of treatment T<NUM>. In this example, the starting value X<NUM> is based on blood pressure measurements collected during a sliding window defined as a time interval between T-<NUM> and T<NUM>. The self-adjusting lower alarm limit <NUM> is set at time T<NUM> to be lower than the lower alarm limit <NUM> of <NUM>/<NUM> mmHg.

In one embodiment, a percentile is calculated from the physiological data values (e.g., blood pressure) acquired from the physiological sensor <NUM> during a first sliding window between time T-<NUM> and T<NUM>, and the self-adjusting lower alarm limit <NUM> is initially set to the calculated percentile starting at the time of treatment T<NUM>. A percentile is a physiological data value below which a given percentage of physiological data values within the first sliding window falls (exclusive definition), or at or below which a given percentage of physiological data values within the first sliding window falls (inclusive definition). The percentile can be set at any given percentage such as a 99th percentile, a 95th percentile, and the like.

In another embodiment, an average is calculated from the physiological data values (e.g., blood pressure) acquired from the physiological sensor <NUM> during the first sliding window between time T-<NUM> and T<NUM>, and the self-adjusting lower alarm limit <NUM> is initially set a standard deviation away from the average of the physiological data values at the time of treatment T<NUM>. A standard deviation is a measure of the amount of variation or dispersion of the physiological data values during the first sliding window. Additional algorithms for determining the starting value and subsequent self-adjustments of the self-adjusting lower alarm limit <NUM> are contemplated.

The blood pressure is monitored during a continuum of sliding windows until one or more of the exit criteria <NUM> are satisfied. During each sliding window, physiological data values are acquired from the physiological sensor <NUM>, and at the end of the sliding window, an adjustment of the self-adjusting lower alarm limit <NUM> is determined.

As shown in the example provided in <FIG>, a second sliding window between time T-<NUM> and T+<NUM> triggers an automatic adjustment of the self-adjusting lower alarm limit <NUM> from the starting value X<NUM> to a new value X<NUM>. Similarly, a third sliding window between time T-<NUM> and T+<NUM> triggers an automatic adjustment of the self-adjusting lower alarm limit <NUM> from the previous value X<NUM> to a new value X<NUM>, a fourth sliding window between time T<NUM> and T+<NUM> triggers an automatic adjustment of the self-adjusting lower alarm limit <NUM> from the previous value X<NUM> to a new value X<NUM>, and so on until one or more of the exit criteria <NUM> are satisfied.

Advantageously, the sliding windows at least partially overlap one another to provide a level of smoothing for updating the self-adjusting lower alarm limit <NUM>. For example, the second sliding window overlaps the first sliding window between time T-<NUM> and T<NUM>. Similarly, the third sliding window overlaps the second sliding window between time T-<NUM> and T+<NUM>, the fourth sliding window overlaps the third sliding window between time T<NUM> and T+<NUM>, and so on.

In the example shown in <FIG>, the blood pressure is improving such that the self-adjusting lower alarm limit <NUM> is adjusted at the end of each sliding window in the targeted direction <NUM> toward the normal resting value <NUM>. Alternatively, when the blood pressure is not improving such that the self-adjusting lower alarm limit <NUM> is adjusted at the end of any sliding window away from the normal resting value <NUM>, an alarm is triggered and the alarm application <NUM> exits the crisis alarm mode <NUM> to return to the normal alarm mode <NUM>.

The alarm triggered in the crisis alarm mode <NUM> can include a local alarm on the monitor device <NUM> such as a visual alarm (e.g., blinking red light) and/or an audible alarm (e.g., beeping noise), and/or may also include notifications sent to mobile devices carried by clinicians (e.g., smartphones), and/or notifications sent to a nurses' station. When the alarm is triggered in the crisis alarm mode <NUM>, the alarm application <NUM> returns to the normal alarm mode <NUM>.

The self-adjusting lower alarm limit <NUM> continues to self-adjust until either the alarm is triggered, or the exit criteria <NUM> are satisfied. As an illustrative example, the exit criteria <NUM> can include the target value <NUM> set at the lower alarm limit <NUM> (e.g., <NUM>/<NUM> mmHg). When the self-adjusting lower alarm limit <NUM> is adjusted above the lower alarm limit <NUM> (e.g., above <NUM>/<NUM> mmHg) such as at the end of a sliding window between time T+<NUM> and T+<NUM>, the crisis alarm mode <NUM> ends and the alarm application <NUM> returns to the normal alarm mode <NUM>.

In some examples, the crisis alarm mode <NUM> ends when the target value <NUM> is satisfied (e.g., <NUM>/<NUM> mmHg) or the time limit <NUM> is satisfied, whichever occurs first. Alternatively, the crisis alarm mode <NUM> ends only when both the target value <NUM> (e.g., <NUM>/<NUM> mmHg) and the time limit <NUM> are satisfied. In some further examples, the crisis alarm mode <NUM> ends when the target value <NUM> (e.g., <NUM>/<NUM> mmHg) is reached within the time limit <NUM>. Additional scenarios for ending the crisis alarm mode are possible.

Each sliding window is defined by a fixed time interval. As an illustrative example, the sliding windows are defined by a time interval of <NUM> minutes. The size of the sliding windows can be adjusted to adjust the sensitivity level <NUM> of the self-adjusting lower alarm limit <NUM>. For example, decreasing the size of the sliding windows will increase the sensitivity level <NUM>, while increasing the size of the sliding windows will decrease the sensitivity level <NUM>.

Additionally, adjusting the amount of overlap between the sliding windows may also be used to adjust the sensitivity level <NUM> of the self-adjusting lower alarm limit <NUM>. For example, decreasing the amount of overlap will increase the sensitivity level <NUM>, while increasing the amount of overlap will decrease the sensitivity level <NUM>.

<FIG> shows the crisis alarm mode <NUM> applying a self-adjusting lower alarm limit that self-adjusts in an increasing targeted direction toward the lower alarm limit <NUM>. In other examples, such as when the patient is experiencing an abnormally high blood pressure due to hypertension, the crisis alarm mode <NUM> can apply a self-adjusting upper alarm limit that self-adjusts in a decreasing targeted direction toward the upper alarm limit <NUM>. In yet further examples, the crisis alarm mode <NUM> can apply both a self-adjusting lower alarm limit and a self-adjusting upper alarm limit that tighten or converge toward the normal resting value <NUM>.

In alternative embodiments where a physiological variable is not continuously monitored, but is rather monitored in intervals, the crisis alarm mode <NUM> can trigger additional readings after an interval reading is detected as not being in the targeted direction <NUM>. For example, when the targeted direction <NUM> is for blood pressure to trend down, and an interval reading is received that the blood pressure has not trended down, or the decrease in the blood pressure is too small, the crisis alarm mode <NUM> can trigger another reading before the next scheduled interval reading to confirm the trend. When a movement in a direction that is not the targeted direction <NUM> is confirmed, the alarm application <NUM> triggers an alarm and exits the crisis alarm mode <NUM>. When a movement in the direction of the targeted direction <NUM> is confirmed, the alarm application <NUM> continues to operate under the crisis alarm mode <NUM>.

<FIG> illustrates an example of a method <NUM> of performing the crisis alarm mode <NUM> by the alarm application <NUM> installed on the monitor device <NUM>. The method <NUM> includes an operation <NUM> of initiating the crisis alarm mode <NUM>. In some examples, the crisis alarm mode <NUM> is initiated upon a manual selection of the crisis alarm mode <NUM> from a clinician operating the monitor device <NUM> when the clinician intervenes to return one or more patient vital signs from an abnormal state to a normal state. In other examples, the crisis alarm mode <NUM> is automatically initiated by the alarm application <NUM> upon a determination that the clinician has intervened to return one or more patient vital signs from an abnormal state to a normal state.

Next, the method <NUM> includes an operation <NUM> of setting a starting value for a self-adjusting upper or lower alarm limit. In some examples, the starting value is the abnormal state of the vital sign captured by the physiological sensor <NUM> before a medical intervention.

Next, the method <NUM> includes an operation <NUM> of determining the targeted direction <NUM> and exit criteria <NUM> for the self-adjusting upper or lower alarm limit. The targeted direction <NUM> is determined by the alarm application <NUM> based on the abnormal state of the vital sign, and the normal range for the vital sign. For example, when the abnormal state is below the normal range, the targeted direction <NUM> is in the increasing targeted direction <NUM>. When the abnormal state is above the normal range, the targeted direction <NUM> is in the decreasing targeted direction <NUM>. The exit criteria <NUM> is based on the normal range for the vital sign such as an upper or lower limit for the normal range. When the upper or lower limit is reached, the alarm application <NUM> exits the crisis alarm mode <NUM> and returns to operating under the normal alarm mode <NUM>.

Once the starting value and targeted direction for the self-adjusting upper or lower alarm limit is set, the method <NUM> proceeds to operation <NUM> of receiving a plurality of physiological data values from the physiological sensor <NUM> during a sliding window.

Next, the method <NUM> includes an operation <NUM> of determining a new value for the self-adjusting upper or lower alarm limit at the end of the sliding window. As described above, the new value can be based on a percentile that is calculated from the physiological data values acquired from the physiological sensor <NUM> during the sliding window. Alternatively, the new value can be based on a standard deviation from an average of the physiological data values.

Next, the method <NUM> includes an operation <NUM> of determining whether the new value for the self-adjusting upper or lower alarm limit is in the targeted direction <NUM>. For example, when the abnormal state of the vital sign is low blood pressure such that the targeted direction <NUM> is increasing toward a normal resting blood pressure value, operation <NUM> determines whether a new value for a self-adjusting lower alarm limit has increased. Alternatively, when the abnormal state of the vital sign is high blood pressure such that the targeted direction <NUM> is decreasing toward a normal resting blood pressure value, operation <NUM> determines whether a new value for a self-adjusting upper alarm limit has decreased.

When the new value for the self-adjusting upper or lower alarm limit is not in the targeted direction <NUM> (i.e., "No" at operation <NUM>), the method <NUM> proceeds to an operation <NUM> of triggering an alarm because the abnormal state of the vital sign is not improving, but is rather deteriorating. After the alarm is triggered, the alarm application <NUM> exits the crisis alarm mode <NUM> at operation <NUM> where it returns to operating under the normal alarm mode <NUM> where the upper and lower alarm limits for monitoring the vital sign are fixed values.

When the new value for the self-adjusting upper or lower alarm limit is in the targeted direction <NUM> (i.e., "Yes" at operation <NUM>), the method <NUM> proceeds to operation <NUM>, which includes resetting the self-adjusting upper or lower alarm limit to the new value. As discussed above, the new value for the self-adjusting upper or lower alarm limit can be based on a percentile that is calculated from the physiological data values acquired from the physiological sensor <NUM> during the sliding window. Alternatively, the new value can be based on a standard deviation from an average of the physiological data values during the sliding window.

The method <NUM> includes an operation <NUM> of determining whether the exit criteria <NUM> are satisfied. The exit criteria <NUM> can include a target value <NUM> and/or a time limit <NUM>. When the exit criteria <NUM> are satisfied (i.e., "Yes" at operation <NUM>), the alarm application <NUM> exits the crisis alarm mode <NUM> at operation <NUM>. When the exit criteria <NUM> are not satisfied (i.e., "No" at operation <NUM>), the alarm application <NUM> repeats the operations <NUM>-<NUM>.

<FIG> illustrates an example of the alarm application <NUM> applied to a chart <NUM> for monitoring a vital sign. The chart <NUM> is displayed on the display device <NUM> of the monitor device <NUM>. In <FIG>, the monitored vital sign is heart rate, and the chart <NUM> includes an upper alarm limit <NUM> set at <NUM> beats per minute (BPM). The upper alarm limit <NUM> can be a default upper alarm limit, or can be based on the patient's stable baseline before the onset of a health crisis that causes the patient's heart rate to reach an abnormal state.

In some examples, the patient's stable baseline is captured while the vital sign (e.g., heart rate) was stationary at any time before it changed to the abnormal state. In certain examples, an Augmented Dickey-Fuller (ADF) test is performed to test for stationarity at admission (and periodically afterwards) to determine the patient's stable baseline. In some examples, a clinician decides whether to accept or reject the captured stable baseline.

In <FIG>, the heart rate is monitored under the normal alarm mode <NUM> before an intervention by a clinician occurs at <NUM>:<NUM>. While under the normal alarm mode <NUM>, physiological data values <NUM> (e.g., heart rate measurements acquired from the physiological sensor <NUM>) experience a sudden increase after <NUM>:<NUM> and begin to exceed the upper alarm limit <NUM> such that the alarm is triggered under the normal alarm mode <NUM>.

After the intervention by the clinician at <NUM>:<NUM>, the heart rate is monitored under the crisis alarm mode <NUM> which establishes a self-adjusting upper alarm limit 708a based on the abnormally high heart rate measured at the time of the intervention. The self-adjusting upper alarm limit 708a is higher than the upper alarm limit <NUM> set at <NUM> BPM.

The self-adjusting upper alarm limit 708a continuously decreases in the targeted direction <NUM> until it reaches the upper alarm limit <NUM>, at which point the alarm application <NUM> exits the crisis alarm mode <NUM> and continues to monitor the heart rate under the normal alarm mode <NUM>. In this example, the alarm application <NUM> exits the crisis alarm mode <NUM> because the target value <NUM> (e.g., <NUM> BPM) of the exit criteria <NUM> is satisfied. While under the crisis alarm mode <NUM>, the alarm is suppressed, thereby reducing alarm fatigue.

In the example of <FIG>, there is a second health crisis at about <NUM>:<NUM> that causes the patient's heart rate to increase beyond the upper alarm limit <NUM> while the heart rate is being monitored under the normal alarm mode <NUM>. The clinician intervenes such that the heart rate is monitored under the crisis alarm mode <NUM> for a second time which establishes a self-adjusting upper alarm limit 708b based on the abnormally high heart rate measured at the time of the second intervention. While under the crisis alarm mode <NUM>, the alarm is suppressed, thereby reducing alarm fatigue. The self-adjusting upper alarm limit 708b decreases in the targeted direction <NUM> until it reaches the upper alarm limit <NUM>, at which point the alarm application <NUM> exits the crisis alarm mode <NUM> because the target value <NUM> is reached, and the alarm application <NUM> monitors the heart rate under the normal alarm mode <NUM>.

<FIG> illustrates another example of the alarm application <NUM> applied to a chart <NUM> for monitoring a vital sign. As shown in <FIG>, the chart <NUM> is displayed on the display device <NUM> of the monitor device <NUM>. Like in the examples described above, the monitored vital sign is heart rate, and the chart <NUM> includes an upper alarm limit <NUM> set at <NUM> BPM. In this example, the heart rate is monitored under the normal alarm mode <NUM> until an intervention by a clinician occurs at about <NUM>:<NUM>. After the intervention by the clinician, the heart rate is monitored under the crisis alarm mode <NUM> which establishes a self-adjusting upper alarm limit 808a based on the abnormally high heart rate measured at the time of the intervention.

The self-adjusting upper alarm limit 808a is higher than the upper alarm limit <NUM> set at <NUM> BPM. The self-adjusting upper alarm limit 808a decreases in the targeted direction <NUM> until about <NUM>:<NUM>, at which point the physiological data values <NUM> acquired from the physiological sensor <NUM> exceed the self-adjusting upper alarm limit 808a. The alarm is triggered and the alarm application <NUM> exits the crisis alarm mode <NUM> to return to the normal alarm mode <NUM>. In this example, the target value <NUM> (e.g., <NUM> BPM) is not reached and the self-adjusting upper alarm limit 808a increased away from the targeted direction <NUM>. Advantageously, the crisis alarm mode <NUM> in this example notifies the clinician that the patient did not respond to the intervention as expected, such that an additional intervention is needed.

In the example of <FIG>, there is a second intervention at about <NUM>:<NUM> such that the heart rate is monitored under the crisis alarm mode <NUM> for a second time which establishes a self-adjusting upper alarm limit 808b based on the abnormally high heart rate measured at the time of the second intervention. The self-adjusting upper alarm limit 808b decreases in the targeted direction <NUM> until the physiological data values <NUM> exceed the self-adjusting upper alarm limit 808b, at which point the alarm is triggered and the alarm application <NUM> exits the crisis alarm mode <NUM> to return to monitoring heart rate under the normal alarm mode <NUM>.

<FIG> and <FIG> illustrate examples of the alarm application <NUM> applied to charts <NUM>, <NUM> having the same physiological data values for monitoring a vital sign such as heart rate. <FIG> and <FIG> illustrate an example where the size of the sliding window (see <FIG>) is adjusted, to control the sensitivity level <NUM> of the crisis alarm mode <NUM>.

In <FIG>, the sliding window is smaller such that the sensitivity level <NUM> of the crisis alarm mode <NUM> is more sensitive. In <FIG>, the sliding window is larger such that the sensitivity level <NUM> of the crisis alarm mode <NUM> is less sensitive.

In <FIG>, there is a first intervention at about <NUM>:<NUM> such that the heart rate is monitored under the crisis alarm mode <NUM> which establishes a self-adjusting upper alarm limit 908a based on the abnormally high heart rate measured at the time of the first intervention. The self-adjusting upper alarm limit 908a is higher than the upper alarm limit <NUM> set at <NUM> BPM. The self-adjusting upper alarm limit 908a begins to decrease in the targeted direction <NUM>, until the physiological data values acquired from the physiological sensor <NUM> exceed the self-adjusting upper alarm limit 908a such that the alarm is triggered and the alarm application <NUM> exits the crisis alarm mode <NUM> and returns to the normal alarm mode <NUM>.

As further shown in <FIG>, there is a second intervention at about <NUM>:<NUM> such that the heart rate is monitored under the crisis alarm mode <NUM> which establishes a self-adjusting upper alarm limit 908b based on the abnormally high heart rate measured at the time of the second intervention. The self-adjusting upper alarm limit 908b is higher than the upper alarm limit <NUM>, and decreases in the targeted direction <NUM> until the physiological data values exceed the self-adjusting upper alarm limit 908b such that the alarm is triggered again and the alarm application <NUM> exits the crisis alarm mode <NUM> and returns to the normal alarm mode <NUM>.

In <FIG>, the sliding window is larger such that the sensitivity level <NUM> of the crisis alarm mode <NUM> is less sensitive. Thus, after the intervention at about <NUM>:<NUM>, the crisis alarm mode <NUM> establishes a self-adjusting upper alarm limit 1008a which decrease in the targeted direction <NUM> until it reaches the upper alarm limit <NUM>, such that the target value <NUM> is satisfied. At this point, the alarm application <NUM> exits the crisis alarm mode <NUM> and returns to the normal alarm mode <NUM> for monitoring the physiological data values. Thus, unlike in <FIG>, the alarm in <FIG> is not triggered during the crisis alarm mode <NUM> due to the lower level of sensitivity that results from having a larger sliding window.

<FIG> illustrates an example of a method <NUM> of continuous physiological monitoring performed by the visualization application <NUM> installed on the monitor device <NUM>. The method <NUM> is performed to provide additional context and information regarding physiological data captured from the physiological sensor <NUM> to boost confidence in the data and aid decision making by a clinician. The method <NUM> can be performed to improve the fidelity of the self-adjusting alarm limits, and/or to alter the display of the physiological data on the display device <NUM>, which can help the clinician to decide whether to adjust an alarm setting, determine whether a medical intervention is needed, or initiate the crisis alarm mode <NUM>.

The alarm application <NUM> and visualization application <NUM> can operate together on the monitor device <NUM> such that the method <NUM> can be performed in combination or in parallel with the method <NUM>. For example, the monitor device <NUM> can operate under both the normal and crisis alarm modes while altering the display of the physiological data on the display device <NUM> to provide additional context and information regarding the physiological data to help aid decision making by a clinician such as whether to initiate or exit the crisis alarm mode <NUM>.

The method <NUM> includes an operation <NUM> of receiving physiological data from the physiological sensor <NUM>. The physiological data can include heart rate, respiration rate, blood pressure, blood oxygen saturation (SpO2), end tidal carbon dioxide (etCO2), and the like.

The method <NUM> includes an operation <NUM> of receiving artifact data that may affect or influence the physiological data received from the physiological sensor <NUM>. For example, the artifact data may cause the physiological data to be inaccurate, erroneous, and/or false. The artifact data can be received simultaneously as the physiological data. In some instances, the artifact data is time stamped and the physiological data is time stamped, and the time stamps of the artifact data and the physiological data are matched together for correspondence.

The artifact data can include audio sounds captured from the audio sensor <NUM>. As described above, the audio sounds captured from the audio sensor <NUM> can be used to detect when the patient P is coughing, talking, and eating, which can affect or influence physiological data such as the respiration rate and etCO2 data sensed by the physiological sensor <NUM>. Additionally, artifact data can include motion data detected by the motion sensor <NUM> such as movements by the patient P while being supported on the patient support system <NUM>, and/or a video feed captured by a camera that detects movements by the patient P inside the area <NUM>. Additional sources of artifact data that can be received in operation <NUM> are contemplated.

Alternatively, or in addition to the audio sounds, the artifact data can include motion data captured by the motion sensor <NUM>, which can affect or influence physiological data such as the heart rate, blood pressure, or respirate rate data sensed by the physiological sensor <NUM>. As described above, the motion data can be captured from piezoelectric sensors, load cells, or combinations thereof that are positioned below, within, or on top of a mattress <NUM> of the patient support system <NUM>, from one or more accelerometers attached to the patient P, or from an accelerometer incorporated into the physiological sensor <NUM>, which is attached to the patient P.

Next, the method <NUM> includes an operation <NUM> of processing the artifact data. In some examples, the artifact data is processed to classy the artifact data as either coughing, talking, or eating, which can affect or influence the respiration rate and etCO2 data, or as motion data that can affect or influence the heart rate, blood pressure, or respirate rate data. Additionally, the artifact data can be processed to quantify and/or classify a strength of the detected artifact data, such as corresponding to an amount of coughing, talking, and eating (e.g., talking vs. shouting), or an amount or type of motion (rolling to one side of the patient support system <NUM> vs. getting up and leaving the patient support system <NUM> to walk around the area <NUM>).

The method <NUM> includes an operation <NUM> of determining whether the artifact data exceeds a predetermined threshold amount, such that the artifact data is strong enough to influence the physiological data. When the artifact data is less than the predetermined threshold amount (i.e., "No" at operation <NUM>), the method <NUM> continues to monitor the physiological data by repeating the operations <NUM>-<NUM>. When the artifact data exceeds the predetermined threshold amount (i.e., "Yes" at operation <NUM>), the method <NUM> proceeds to operation <NUM>, which can include excluding artifact affected physiological data from consideration when adjusting the one or more self-adjusting alarm limits (see the method <NUM>). Additionally, or alternatively, operation <NUM> can include altering the display of the physiological data on the display device <NUM>, which will now be described with reference to <FIG> and <FIG>.

<FIG> illustrates an example of the visualization application <NUM> applied to a chart <NUM> displayed on the display device <NUM> of the monitor device <NUM>, in accordance with operation <NUM> of the method <NUM>. In the example shown in <FIG>, the chart <NUM> is for monitoring respiration rate values. The visualization application <NUM> displays the respiration rate values differently based on when the patient P is detected as talking (e.g., when the artifact data exceeds a predetermined threshold amount) or when the patient P is not talking (e.g., when the artifact data does not exceed the predetermined threshold amount). While the chart <NUM> displays respiration rate values, the visualization application <NUM> can be applied in a similar fashion to charts that display other types of physiological data values such as heart rate, blood pressure, blood oxygen saturation (SpO2), end tidal carbon dioxide (etCO2), and the like.

In <FIG>, the respiration rate values when the patient P is talking are displayed in a color (e.g., red) that is different from a color (e.g., blue) of the respiration rate values when the patient P is not talking such that the respiration rate values are color coded. In other examples, the visualization application <NUM> can apply a different kind of dashed line pattern or other type of visual marker to distinguish between the respiration rate values detected when the patient P is talking from the respiration rate values detected when the patient P is not talking.

In <FIG>, the chart <NUM> includes a legend <NUM> that includes labels identifying visual markers associated with artifacts that can affect or influence the respiration rate values, such as when the patient P is talking (e.g., "Talking"). The visual markers can also be associated with normal behavior (e.g., "Normal") when no artifacts are detected.

The legend can include additional labels for visual markers associated with coughing and eating artifacts when the audio sensor <NUM> detects that the patient P is coughing or eating, and for additional visual markers associated with motion when the motion sensor <NUM> detects the patient P is moving. In some examples, the legend <NUM> classifies the artifacts detected by the audio sensor <NUM> and motion sensor <NUM> together under one label such as "Artifact detected", without distinguishing between talking, coughing, eating, and motion artifacts.

As described above, the alarm application <NUM> and visualization application <NUM> can operate together on the monitor device <NUM>. Thus, the visual markers can be displayed by the visualization application <NUM> to classify the physiological data values when artifacts (e.g., talking, coughing, eating, and motion) are detected by the motion sensor <NUM> and audio sensor <NUM>, while the monitor device <NUM> is operating in the normal alarm mode <NUM> and the crisis alarm mode <NUM> in accordance with the alarm application <NUM>. Advantageously, the visual markers from the visualization application <NUM> can help inform a clinician to decide whether to respond to an alarm or adjust an alarm setting, determine whether a medical intervention is needed, and/or initiate the crisis alarm mode <NUM>. Thus, the visual markers displayed by the visualization application <NUM> improve the operation of the monitor device <NUM>.

<FIG> illustrates another example of the visualization application <NUM> applied to a chart <NUM> displayed on the display device <NUM> of the monitor device <NUM>, in accordance with operation <NUM> of the method <NUM>. <FIG> is similar to the example shown in <FIG>, except the chart <NUM> is for monitoring heart rate values, which are displayed differently based on whether the patient is detected by the motion sensor <NUM> as moving or not moving. For example, the chart <NUM> includes a legend <NUM> that includes "Normal" and "Motion" labels to distinguish heart rate values when the patient is moving from when the patient is not moving.

In alternative examples to those shown in <FIG> and <FIG>, the physiological data values (e.g., heart rate, respiration rate, blood pressure, blood oxygen saturation (SpO2), end tidal carbon dioxide (etCO2), etc.) are excluded from the charts <NUM>, <NUM> when motion artifacts (e.g., talking, coughing, eating, and motion) are detected by the motion sensor <NUM> and audio sensor <NUM>. In such examples, the legends <NUM>, <NUM> can provide explanations for the exclusion of the physiological data values, such as due to the detection of one or more artifacts. Additionally, automatic or semi-automatic baselining can be performed without using the excluded physiological data values to calculate a personalized baseline for the patient.

<FIG> illustrates another example of a method <NUM> of continuous physiological monitoring performed by the visualization application <NUM> installed on the monitor device <NUM>. The method <NUM> is performed to provide additional context and information regarding physiological data captured from the physiological sensor <NUM> to boost confidence in the data and aid decision making by a clinician. The method <NUM> alters the display of the physiological data on the display device <NUM> to help a clinician to decide whether to adjust an alarm setting, determine whether a medical intervention is needed, and/or initiate the crisis alarm mode <NUM>.

As described above, the alarm application <NUM> and visualization application <NUM> can operate together on the monitor device <NUM> such that the method <NUM> can be performed in combination or in parallel with the method <NUM>. For example, the monitor device <NUM> can operate under both the normal and crisis alarm modes while altering the display of the physiological data on the display device <NUM> in accordance with the operations of the method <NUM>.

The method <NUM> includes an operation <NUM> of receiving treatment events that may affect or influence the physiological data received from the physiological sensor <NUM>. Examples of the treatment events include, without limitation, medications, surgical operations, pre-operative and post-operative procedures, diagnoses, co-morbidities, rapid response alarm codes, sepsis risk scores including systemic inflammatory response syndrome (SIRS) scores, sequential organ failure assessment scores (SOFA), and quick SOFA scores (qSOFA), Early Warning Scores (EWS), equipment requests (e.g., requests for nasal cannula, high flow, bilevel positive airway pressure (BiPap) ventilator, and the like for oxygen supply), Glasgow Modified Alcohol Withdrawal Scale (GMAWS) scores for alcohol and/or opioid withdrawal, and other treatments that may affect or influence the physiological data. The treatment events received in operation <NUM> are time stamped to include information such as when they took place and for how long.

The visualization application <NUM> when installed on the monitor device <NUM> can receive the treatment events from the server <NUM> via the communications network <NUM>. For example, the visualization application <NUM> can receive the diagnoses and co-morbidities of a patient from the electronic medical record <NUM> of the patient stored in the EMR system <NUM>. As another example, the visualization application <NUM> can receive administered medications from the medication record <NUM> of the patient stored in the EMAR system <NUM>.

Alternatively, or in addition to receiving the treatment events from the server <NUM>, the treatment events can be entered manually into the monitor device <NUM> by a clinician. In examples where the display device <NUM> operates to display a user interface <NUM> that receives inputs, the clinician can manually enter the treatment events on the monitor device <NUM> from a drop down menu. In some instances, the drop down menu can include a treatment name or ID that the clinician can select. Alternatively, the clinician can enter the treatment name or ID into a field on the user interface <NUM>. Also, the clinician can scan a bar code of a medication using a bar code scanner connected to the monitor device <NUM> to enter the medication as a treatment event.

The method <NUM> includes an operation <NUM> of processing the treatment events to determine whether they have an effect on one or more of the physiological variables measured by the physiological sensor <NUM> such as heart rate, respiration rate, blood pressure, blood oxygen saturation (SpO2), end tidal carbon dioxide (etCO2), and the like. The treatment event can be processed to determine whether it has a targeted effect (e.g., a vasopressor medication that has a targeted effect to raise blood pressure), or whether it has an unintended side effect on one or more of the physiological variables measured by the physiological sensor <NUM>.

In some instances, the side effect can be classified as mild, medium, or severe. Additionally, the targeted effect or side effect of each treatment event can be classified or quantified as having an effect within a physiological variable range such as an absolute range or a relative range based on patient baseline values, and within a time window range.

Additionally, each treatment event is processed to determine whether it may have an interaction with any other treatment events that may cause an effect on the one or more of the physiological variables measured by the physiological sensor <NUM>. For example, a certain medication may have a side effect based on a co-morbidity of the patient.

Next, the method <NUM> includes an operation <NUM> of altering the display of the physiological data on the display device <NUM> based on the processed treatment events. For example, all medications administered to the patient that are known to affect a physiological variable measured by the physiological sensor <NUM> are displayed on the display device <NUM> along with the measured physiological data values. Each medication can be displayed as a predefined range that is overlayed on the measured physiological data values to show a duration that the medication was administered to the patient (e.g., when administered through an IV drip), or an estimated duration that the medication may affect the measured physiological data values.

Additionally, any side effects that cause the measured physiological data values to fall within a defined range will be displayed with appropriate labels (e.g., listing possible causes for the side effects such as due to co-morbidities, drug interactions, or other causes). In some examples, the display device <NUM> can display one or more recommended actions such as to adjust alarm settings, adjust medications, check patient response, or provide a medical intervention.

<FIG> illustrates another example of the visualization application <NUM> applied to a chart <NUM> displayed on the display device <NUM> of the monitor device <NUM>, in accordance with operation <NUM> of the method <NUM>. In the example shown in <FIG>, the chart <NUM> is for monitoring heart rate values. The visualization application <NUM> displays the heart rate values along with one or treatment events that can affect the heart rate values. While the chart <NUM> displays heart rate values, the visualization application <NUM> can be applied in a similar fashion to charts that display other types of physiological data values such as heart rate, blood pressure, blood oxygen saturation (SpO2), end tidal carbon dioxide (etCO2), and the like.

The chart <NUM> displays a normal range for the heart rate values defined by upper and lower limits <NUM>, <NUM>. In some examples, the upper and lower limits <NUM>, <NUM> of the normal range are based on default values. Alternatively, the upper and lower limits <NUM>, <NUM> of the normal range are based on personalized baselines of the patient. The normal range between the upper and lower limits <NUM>, <NUM> is overlayed on the heart rate values in a first shade of color.

The chart <NUM> also displays a treatment event <NUM> that starts at time T<NUM> and ends at time T<NUM>. In the example shown in <FIG>, the treatment event <NUM> is an albumin infusion, which is used to treat or prevent shock following serious injury, bleeding, surgery, or burns by increasing the volume of blood plasma. The treatment event <NUM> between time T<NUM> and time T<NUM> is displayed as a visual marker overlayed on the heart rate values in a second shade of color.

While the example in <FIG> shows the chart <NUM> as displaying a single treatment event, it is contemplated that the chart <NUM> can display a plurality of treatment events. In such examples, a clinician can view all of the treatment events on a timeline, along with the physiological data values acquired from the physiological sensor <NUM>.

In examples where the display device <NUM> operates to display a user interface <NUM> that receives inputs, the clinician can select the treatment event <NUM> to obtain information on an expected effect or influence of the treatment event <NUM> on the physiological data values acquired from the physiological sensor <NUM>. For example, the clinician can select the treatment event <NUM> with their finger or with a stylus in examples where the display device <NUM> is a touchscreen to obtain information on the expected effect or influence on the physiological data values acquired from the physiological sensor <NUM>. Alternatively, or in addition, the clinician can select the treatment event <NUM> using a mouse cursor or can hover the mouse cursor over the treatment event <NUM> (without actually selecting the treatment event <NUM>) to obtain the information on the expected effect or influence on the physiological data values.

The expected effect of the treatment event <NUM> can be overlaid on a trendline of the physiological data values acquired from the physiological sensor <NUM> that are displayed on the chart <NUM>. The expected effect of the treatment event <NUM> can be color coded differently between ranges of desired target effect, side effect, and severe side effect that needs to be intervened immediately. This information can then be used by the clinician to adjust a treatment plan based on the expected effect, adjust alarm settings including adjusting upper and lower alarm limits to an acceptable range based on the expected effect, or intervene and set the crisis alarm mode <NUM>. Also, some treatment events <NUM> can display potential drug interactions with other medications within a configured time window to further inform the clinician.

In <FIG>, the chart <NUM> displays a modified range for the heart rate values defined by upper and lower limits <NUM>, <NUM>. The modified range can be displayed in response to selection of the treatment event <NUM> in accordance with the examples described above. In examples where the chart <NUM> displays a plurality of treatment events, each treatment event is selectable to view a modified range of heart rate values based on the expected effect of the selected treatment event, and its interaction with one or more prior treatment events.

In some examples, the chart <NUM> can display a modified range for the heart rate values without requiring a selection of the treatment event <NUM>. In such examples, the modified range for the heart rate values defined by the upper and lower limits <NUM>, <NUM> is displayed on the chart <NUM> regardless of whether or not a clinician has selected the treatment event <NUM>.

The upper and lower limits <NUM>, <NUM> of the modified range are displayed as curves that show an expected increase in the heart rate values based on the side effect of the of the albumin infusion followed by an expected decrease once the side effect of the albumin infusion begins to wear off. Accordingly, the upper limit <NUM> of the modified range is higher than the upper limit <NUM> of the normal range, and the lower limit <NUM> of the modified range is higher than the lower limit <NUM> of the normal range. The modified range between the upper and lower limits <NUM>, <NUM> is overlayed on the heart rate values in a third shade of color.

As shown in <FIG>, the first, second, and third shades of color when overlayed on the heart rate values are overlapped with one another, and can be used to provide intuitive information that improves the operation of the monitor device <NUM>. As an example, the first shade of color for the normal range is gray and the third shade of color of the modified range is a color (e.g., red, green, blue, yellow, etc.) such that the portion in the chart <NUM> where the modified range is overlapped by the normal range is a darker shade of the color, and the portion in the chart <NUM> where the modified range is not overlapped by the normal range is a lighter or brighter shade of the color. This can help visualize expected targeted effects or side effects of treatment events on the physiological data values measured by the physiological sensor <NUM>. Advantageously, the display of treatment events <NUM> and overlapping normal and modified ranges can help a clinician to decide whether to respond to an alarm or adjust an alarm setting, determine whether a medical intervention is needed, and/or initiate the crisis alarm mode <NUM>.

In some alternative examples, only the modified range defined by the upper and lower limits <NUM>, <NUM> is displayed over the trendline of heart rate values when the treatment event <NUM> is selected, such that the normal range defined the upper and lower limits <NUM>, <NUM> is hidden. Such examples can prevent over-crowding of information displayed on the chart <NUM>.

As described above, the alarm application <NUM> and visualization application <NUM> can operate together on the monitor device <NUM> such that the chart <NUM> can be displayed while the monitor device <NUM> operates under the normal alarm mode <NUM> and the crisis alarm mode <NUM>. In the example shown in <FIG>, the heart rate values are classified as abnormal when they exceed the upper limit <NUM> of the normal range of heart rate values regardless of whether they are below the upper limit <NUM> of the modified range of heart rate values. In such an example, an alarm is triggered by the alarm application <NUM> when the heart rate values exceed the upper limit <NUM> of the normal range, but are below the upper limit <NUM> of the modified range.

In an alternative example, the heart rate values are classified as abnormal only when they exceed the upper limit <NUM> of the modified range. In some instances, an alarm is triggered by the alarm application <NUM> whenever the heart rate values exceed the upper limit <NUM> of the modified range of heart rate values. In other instances, an alarm is triggered when the heart rate values are a predetermined distance beyond the upper limit <NUM> of the modified range.

As another example, the upper and lower limits <NUM>, <NUM> of the normal range of heart rate values can self-adjust when the alarm application <NUM> operates under the crisis alarm mode <NUM>. Also, the upper and lower limits <NUM>, <NUM> of the modified range of heart rate values can self-adjust when the alarm application <NUM> operates under the crisis alarm mode <NUM>.

Claim 1:
A device (<NUM>) for monitoring a physiological variable, comprising:
at least one processing device (<NUM>); and
a memory device (<NUM>) storing instructions which, when executed by the at least one processing device (<NUM>), cause the device (<NUM>) to:
determine (<NUM>) a starting value for a self-adjusting alarm limit based on an abnormal state of the physiological variable;
determine (<NUM>) a new value for the self-adjusting alarm limit from physiological data values received during a time window; and
when the new value for the self-adjusting alarm limit moves in a targeted direction (<NUM>), reset (<NUM>) the self-adjusting alarm limit at the new value.