Continuous patient monitoring

Abstract

A device for monitoring a physiological variable determines a starting value for a self-adjusting alarm limit based on an abnormal state of the physiological variable. The device determines a new value for the self-adjusting alarm limit from physiological data values received during a time window. The device resets the self-adjusting alarm limit to the new value when the new value of the self-adjusting alarm limit moves in a target direction.

Description

BACKGROUND

[0001] During continuous patient monitoring, alarms are typically set with a pair of upper and lower alarm limits. An alarm is triggered when a patient's monitored vital sign is below the lower alarm limit or the patient's vital sign is above the upper alarm limit.

[0002] When a patient's vital sign is improving or worsening, the alarm is typically manually reset based on a newly established baseline for the patient. This requires additional action by the clinician, which can be labor intensive and time consuming. When the alarm is not properly reset, the alarm is often repeatedly triggered, which can lead to alarm fatigue.

[0003] Additionally, the clinician is often unable to determine whether the alarm was triggered due to a worsening condition of the patient or due to a medication, treatment, and noise-like artifact. This can lead to confusion regarding the need for a response to the alarm and further contribute to alarm fatigue. SUMMARY

[0004] Generally, the present disclosure relates to vital sign alarms and visualization. In one possible configuration, a monitoring device provides self-adjusting upper and lower alarm limits that can more accurately monitor a patient's measured vital sign and reduce alarm fatigue. The monitoring device can further provide enhanced visualization of the measured vital sign that can increase confidence in its accuracy and assist the clinician in making decisions, such as whether to intervene or adjust one or more alarm settings. According to embodiments of the present disclosure, various vital signs can be monitored. For example, at least one of heart rate, blood pressure, blood oxygen saturation, respiratory rate, electrocardiogram, and end-tidal carbon dioxide (etC02) can be monitored. Various aspects are described in the present disclosure, including but not limited to the following aspects.

[0005] In one aspect, a device for monitoring a physiological variable includes at least one processing device and a storage device storing instructions that, 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 reset the self-adjusting alarm limit to the new value when the new value for the self-adjusting alarm limit moves in a target direction.

[0006] In another aspect, a method of continuous physiological monitoring includes determining a starting value for a self-adjusting alarm limit based on an abnormal state of a 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 to the new value when the new value for the self-adjusting alarm limit moves in a target direction, and triggering an alarm when the new value for the self-adjusting alarm limit moves in a direction opposite the target direction.

[0007] In another aspect, an apparatus for monitoring a physiological variable includes at least one processing device; and a storage device storing instructions that, when executed by the at least one processing device, cause the apparatus to: receive a physiological data value from a physiological sensor; receive artifact data including an audio signal captured from an audio sensor; process the audio signal to determine one or more artifacts; and display the physiological data value to distinguish values affected by the one or more artifacts from values not affected by the one or more artifacts.

[0008] In another aspect, an apparatus for monitoring a physiological variable includes at least one processing device; and a storage device storing instructions that, when executed by the at least one processing device, cause the apparatus to: receive a physiological data value from a physiological sensor; receive a therapeutic event; determine an expected effect of the therapeutic event on the physiological data value, the expected effect being a target effect or a side effect; display the therapeutic event overlaid on the physiological data value; display a normal range overlaid on the physiological data value, the normal range having a first set of upper and lower limits; and display a modified range overlaid on the physiological data value, the modified range having a second set of upper and lower limits based on the expected effect of the therapeutic event. BRIEF DESCRIPTION OF DRAWINGS

[0009] The following drawings, which are a part of this application, are included to illustrate certain aspects of the technology described, but are not meant to limit the scope of the disclosure in any way.

[0010] Figure 1 An example of a monitoring system for monitoring vital signs of a patient shown lying on a patient support system is illustrated.

[0011] Figure 2 An example of an audio sensor of the monitoring system of Figure 1 is shown positioned proximate to the patient.

[0012] Figure 3 An example of a monitoring system of Figure 1 is schematically illustrated, the monitoring system including a monitoring apparatus, a motion sensor, a physiological sensor, and an audio sensor.

[0013] Figure 4 An example of an alarm application installed on the monitoring apparatus of Figure 3 is schematically illustrated.

[0014] Figure 5 An example of a crisis alert mode in the alarm application of Figure 3 applied to a graph displayed on the monitoring apparatus is illustrated. Figure 4

[0015] Figure 6 An example of a crisis alert mode in the alarm application of Figure 4 ​An example of how an alert application executes a crisis alert mode.

[0016] Figure 7 Explains the application Figure 3 The charts displayed on the monitoring device Figure 4 An example of an alarm application.

[0017] Figure 8 Explains the application Figure 3 The charts displayed on the monitoring device Figure 4 Another example of an alert application.

[0018] Figure 9 Explained the application Figure 3 The charts displayed on the monitoring device Figure 4 Another example of an alert application.

[0019] Figure 10 Explained the application Figure 3 The charts displayed on the monitoring device Figure 4 Another example of an alert application.

[0020] Figure 11 This explains the installation by [the company / organization]. Figure 3 An example of a method for continuous physiological monitoring performed by a visualization application on a monitoring device.

[0021] Figure 12 Explained the application Figure 3 An example of a visualization application that displays charts on a monitoring device.

[0022] Figure 13 Explained the application Figure 3 Another example of a visualization application that displays charts on a monitoring device.

[0023] Figure 14 This explains the installation by [the company / organization]. Figure 3 Another example of a method for continuous physiological monitoring performed by a visualization application on a monitoring device.

[0024] Figure 15 Explained the application Figure 3 Another example of a visualization application that displays charts on a monitoring device. Detailed Implementation

[0025] Figure 1An example of a monitoring system 100 for monitoring vital signs of a patient P shown lying on a patient support system 102 is illustrated. The monitoring system 100 includes the patient support system 102, and a monitoring device 104, a motion sensor 106, and a physiological sensor 108, all shown within a region 10. In some examples, the region 10 is a hospital room, a pre- or post-operative waiting 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 a similar type of facility.

[0026] The patient P is a person, such as a patient, being clinically treated by one or more clinicians in the region 10. Examples of clinicians include primary medical providers (e.g., physicians, nurse practitioners, and physician assistants), nursing providers (e.g., nurses), specialized medical providers (e.g., specialists of various specialties), and health care professionals who provide preventive, therapeutic, rehabilitative, and palliative health services.

[0027] In Figure 1 In the illustrated example, the patient support system 102 is a hospital bed. In other examples, the patient support system 102 is another type of bed, a lift, a chair, a wheelchair, a stretcher, an operating table, or the like that can support the patient P in the region 10.

[0028] The monitoring device 104 is connected to the physiological sensor 108 and includes a display device 114 for displaying physiological data acquired from the physiological sensor 108. The physiological sensor 108 communicates with the monitoring device 104 wirelessly or via a wired connection. The monitoring device 104 can also communicate with one or more additional sensing devices in the region 10, including the patient support system 102 and the motion sensor 106.

[0029] The monitoring device 104 can be any suitable type of monitoring device. Figure 1 The monitoring device 104 is illustrated as a multi-parameter device that displays multiple parameters on the display device 114. The multiple parameters are detected from the physiological sensor 108 and from other sensing devices within the region 10. In alternative examples, the monitoring device 104 can be a single-parameter device, such as an ECG monitor.

[0030] Examples of the physiological sensor 108 include an electrocardiogram (ECG) sensor, a blood oxygen saturation / pulse oximeter (Sp02) sensor, a blood pressure sensor, a heart rate sensor, a respiratory rate sensor, an end-tidal carbon dioxide (etC02) sensor, or the like. The physiological sensor 108 can also combine two or more sensors in a single sensor device.

[0031] As Figure 1As shown, the monitoring device 104 communicates with a server 200 via the communication network 110. The server 200 operates to manage the medical history and information of the patient P. The server 200 can be operated by a healthcare service provider, such as a hospital or medical clinic. The monitoring device 104 sends physiological data acquired from the physiological sensor 108 to the server 200 via connection with the communication network 110. In at least some examples, the server 200 is a cloud server or similar type of server.

[0032] The server 200 can include an electronic medical record (EMR) system 300 (or electronic health record (EHR)). Advantageously, the server 200 can automatically store physiological data acquired from the monitoring device 104 in an electronic medical record 302 or electronic health record of the patient P located in the EMR system 300 via connection with the monitoring device 104 over the communication network 110.

[0033] The server 200 can also include an electronic medication administration record (EMAR) system 400. The monitoring device 104 can communicate with the EMAR system 400 via connection with the communication network 110 to obtain access to a medication history 402 of the patient P, which includes medications and timestamps of when the medications were administered to the patient P.

[0034] In Figure 1 In the example shown, the motion sensor 106 is a motion sensor located beneath, within, or on top of the mattress 112 of the patient support system 102. The motion sensor 106 can include a piezoelectric sensor, a load cell, or a combination thereof that detects motion of the patient P when the patient P is supported on the patient support system 102.

[0035] In alternative examples, the motion sensor 106 can be an accelerometer attached to the patient P, or incorporated into the physiological sensor 108 and / or incorporated into one or more other sensing devices attached to the patient P. In such examples, the physiological sensing functionality and the motion detection functionality are combined in one device. Multiple such devices can be used on the patient P. For example, a combined ECG / motion detection device and / or a combined pulse oximeter / motion detection device can be used on the patient P simultaneously.

[0036] The motion sensor 106 detects motion of the patient P, which can affect or alter the heart rate, blood pressure, and respiration rate data sensed by the physiological sensor 108. The motion sensor 106 senses motion of the patient P (e.g., by using piezoelectric or load sensors located under, within, or on top of the mattress 112 or an accelerometer attached to the patient P) and transmits the sensed motion data to the monitoring device 104 while the physiological sensor 108 senses physiological data of the patient P, such as heart rate, blood pressure, or respiration rate, and transmits the physiological data to the monitoring device 104.

[0037] The monitoring device 104 processes the data from the motion sensor 106 to identify when the patient P moves. The monitoring device 104 can then flag the physiological data measured when the patient P moves. For example, the monitoring device 104 can display the physiological data acquired when the patient P moves differently than when the patient P does not move to help a clinician evaluate the patient P.

[0038] The communication network 110 communicates data between one or more devices, such as between the monitoring device 104 and the server 200. In some examples, the communication network 110 can also be used to communicate data between one or more devices within the area 10, such as between the patient support system 102, the monitoring device 104, the motion sensor 106, the physiological sensor 108, and other sensor devices within the area 10.

[0039] The communication network 110 can include any type of wired or wireless connection, or any combination thereof. Examples of wireless connections include broadband cellular network connections, such as 4G or 5G. In some examples, wireless connections can also be implemented using Wi-Fi, Ultra-Wideband (UWB), Bluetooth, Radio Frequency Identification (RFID), and similar types of wireless connections.

[0040] Figure 2 An example of an audio sensor 116 that can also be part of the monitoring system 100 is illustrated. In the illustrated example, the audio sensor 116 is attached to a device 118 connected to the patient P. The device 118 can be a nasal cannula, endotracheal tube, face mask, capnography monitor, or similar device such that the audio sensor 116 is located near the mouth or chest of the patient P. Alternatively, the audio sensor 116 can be attached directly to the patient P, or to another object near the patient P. Figure 2

[0041] In the illustrated example, the physiological sensor 108 is also attached to the device 118. In this example, the physiological sensor 108 is a capnography sensor that can be used to measure the etC02and respiration rate of the patient P. Figure 2

[0042] ​​The audio sensor 116 captures audio sounds that can be used to detect when the patient P is coughing, speaking, and eating, which affects or changes the respiration rate and etC02 data sensed by the physiological sensor 108. The audio sensor 116 captures audio data of the patient P and transmits the audio data to the monitoring device 104. Additionally, the physiological sensor 108 obtains etC02 and respiration rate data of the patient P and transmits the etC02 and respiration rate data to the monitoring device 104.

[0043] The monitoring device 104 processes the data from the audio sensor 116 to identify when the patient P is coughing, speaking, and eating. The monitoring device 104 can then flag the etC02 and respiration rate data measured when the patient P is coughing, speaking, and eating. For example, the monitoring device 104 can display the etC02 and respiration rate data obtained when the patient P is coughing, speaking, and eating differently than when the patient P is not coughing, speaking, and eating to assist the clinician in evaluating the patient P.

[0044] Figure 3 An example of the monitoring system 100 is schematically illustrated. The monitoring device 104 includes a computing device 120 having at least one processing device 122 and a storage device 124. The at least one processing device 122 is an example of a processing unit, such as a central processing unit (CPU). The at least one processing device 122 can include one or more CPUs. The at least one processing device 122 can include one or more digital signal processors, field programmable gate arrays, or other electronic circuits.

[0045] The storage device 124 operates to store data and instructions for execution by the at least one processing device 122, which includes an alert application 126 and a visualization application 128, both of which will be described in greater detail below. The storage device 124 includes a computer-readable medium, which can include any medium accessible by the monitoring device 104. By way of example, computer-readable media include computer-readable storage media and computer-readable communication media.

[0046] Computer-readable storage media include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer-readable storage media include, but are 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 is used to store information that is accessible by the monitoring device 104. Computer-readable storage media are non-transitory.

[0047] Computer-readable communication media embody computer-readable instructions, data structures, program modules, or other data in modulated data signals (such as carrier waves or other transmission mechanisms), and include any information transmission medium. The term "modulated data signal" refers to a signal whose characteristics are set or altered in a manner that encodes information within it. For example, computer-readable communication media include wired media (such as wired networks or direct wired connections) and wireless media (such as acoustic, radio frequency, infrared, and other wireless media). Any combination of these falls within the scope of computer-readable media.

[0048] The monitoring device 104 also includes a sensor interface 130, which operates to communicate with various sensors of the monitoring system 100. The sensor interface 130 may include both wired and wireless interfaces. The motion sensor 106, physiological sensor 108, and audio sensor 116 can be wirelessly connected to the sensor interface 130 via Wi-Fi, ultra-wideband (UWB), Bluetooth, and similar wireless connections. Alternatively, the motion sensor 106, physiological sensor 108, and audio sensor 116 can be connected to the monitoring device 104 using a wired connection inserted into the sensor interface 130.

[0049] like Figure 3 As shown, the monitoring device 104 includes a display device 114 that operates to display a user interface 132. In some examples, the display device 114 is a touchscreen, such that the user interface 132 operates to receive input from a clinician. In such examples, the display device 114 operates as both a display device and a user input device. The monitoring device 104 may also support physical buttons on the device housing that operate to receive input from a clinician to control the operation of the monitoring device and input data.

[0050] Figure 4 An example of an alarm application 126 installed on monitoring device 104 is illustrated. Alarm application 126 includes a normal alarm mode 140 and a crisis alarm mode 142. A clinician can select normal alarm mode 140 or crisis alarm mode 142 while operating monitoring device 104. When display device 114 is a touchscreen, the clinician can select normal alarm mode 140 or crisis alarm mode 142 on display device 114. Alternatively, the clinician can select normal alarm mode 140 or crisis alarm mode 142 by selecting one or more user input buttons on monitoring device 104.

[0051] Normal alarm mode 140 is an operating mode in which fixed upper and lower alarm limits are set for the physiological data sensed from physiological sensors 108. In normal alarm mode 140, an alarm is triggered when the physiological data is above the upper alarm limit or below the lower alarm limit. Illustrative examples of alarms include a local alarm on monitoring device 104, such as a visual alarm (e.g., a flashing red light) and / or an audible alarm (e.g., a beeping sound), and / or can also include a notification sent to a mobile device (e.g., a smartphone) carried by a clinician, and / or a notification sent to a nurses’ station.

[0052] In normal alarm mode 140, the upper and lower alarm limits are based on normal values or default values. As an illustrative example, normal resting blood pressure for an adult is approximately 120 / 80 mmHg, and hypertension for an adult is considered to be 140 / 90 mmHg or higher, and hypotension for an adult is considered to be 90 / 60 mmHg or lower. When monitoring patient P’s blood pressure in normal alarm mode 140, the upper alarm limit can be set to 140 / 90 mmHg, and the lower alarm limit can be set to 90 / 60 mmHg. An alarm is triggered when patient P’s blood pressure is above 140 / 90 mmHg. In addition, an alarm is triggered when patient P’s blood pressure is below 90 / 60 mmHg.

[0053] In some examples, alarm application 126 automatically sets the upper and lower alarm limits based on patient P’s demographic data, including patient P’s age and gender, by obtaining the demographic data from electronic medical record 302 of EMR system 300 via communication network 110. Alternatively, a clinician can manually set the upper and lower alarm limits based on patient P’s demographic data.

[0054] In some examples, the upper and lower alarm limits of normal alarm mode 140 are set by alarm application 126 or a clinician according to patient P’s personalized baseline. For example, when patient P is known to have a prior history of hypotension, the lower alarm limit for blood pressure can be set lower than 90 / 60 mmHg. Similarly, when patient P is known to have a prior history of hypertension, the upper alarm limit for blood pressure can be set higher than 140 / 90 mmHg.

[0055] In some cases, it may be desirable to monitor patient P's physiological data based on patient P's progress during treatment. As an illustrative example, sepsis can cause patient P to have low blood pressure. In response to a sepsis diagnosis, a clinician may intervene by administering vasopressors to raise patient P's blood pressure. The clinician will then closely monitor patient P to ensure their blood pressure is rising. As long as patient P's blood pressure is rising, there is no reason for an alarm to sound. However, in this scenario, fixed alarm upper and lower limits can lead to alarm fatigue because the lower alarm limit is repeatedly triggered until patient P's blood pressure stabilizes. In some cases, the clinician may decide to shut down undesirable alarms. Alternatively, the clinician could manually reset the lower alarm limit as patient P's condition improves; however, this is labor-intensive and can lead to clinician burnout. Therefore, fixed alarm upper and lower limits may be undesirable in this situation.

[0056] Crisis Alarm Mode 142 automatically adjusts the upper or lower alarm limit on the target direction 144 until exit criterion 150 is met. Clinicians can select Crisis Alarm Mode 142 when patient P is receiving treatment that causes a change in data from physiological sensors 108 on the target direction 144. When exit criterion 150 is met, Crisis Alarm Mode 142 terminates and the alarm application 126 returns to normal alarm mode 140.

[0057] like Figure 4 As shown, target direction 144 may include increasing target direction 146 or decreasing target direction 148. As an illustrative example, when administering a vasopressor to raise the blood pressure of patient P, increasing target direction 146 is selected. As another illustrative example, when providing a drug or treatment to decrease the heart rate of patient P, decreasing target direction 148 is selected.

[0058] An alarm is triggered in crisis alarm mode 142 when physiological data values ​​from physiological sensor 108 move in the opposite direction to target direction 144. For example, an alarm is triggered when increasing target direction 146 is selected and physiological data values ​​are decreasing. Similarly, an alarm is triggered when decreasing target direction 148 is selected and physiological data values ​​are increasing.

[0059] Other types of target directions may include recovery trend lines, curves, etc. In such an example, an alarm is triggered in crisis alarm mode 142 when a predetermined distance from the selected recovery trend line or curve is detected.

[0060] The target direction 144 can be automatically selected by the alarm application 126, such as through an algorithm that determines the target direction 144 based on a status or condition of the patient P (e.g., the patient P has sepsis) and medications and / or treatments provided to the patient P (e.g., a vasopressor medication administered to the patient). This information can be obtained by the alarm application 126 from the electronic medical record 302 of the patient P of the EMR system 300 via the communication network 110.

[0061] Alternatively, the target direction 144 can be selected by a clinician. For example, in embodiments where the display device 114 is a touchscreen, the clinician can use the display device 114 to select the target direction 144. Alternatively, the clinician can select one or more user input buttons on the monitoring device 104 to select the target direction 144.

[0062] The exit criteria 150 can include a target value 152 and a time limit 154. In some examples, only the target value 152 is selected to determine when the crisis alarm mode 142 ends. In alternative examples, both the target value 152 and the time limit 154 are selected.

[0063] The target value 152 is a physiologic measurement value that is within a normal range, such as a measurement value based on the demographics of the patient P (e.g., blood pressure is between 140 / 90 mmHg and 90 / 60 mmHg for an adult). When the target value 152 is reached, the crisis alarm mode 142 ends and the alarm application 126 returns to the normal alarm mode 140.

[0064] The time limit 154 is a predetermined time based on the condition, medication, or treatment setting of the patient P. For example, the time limit 154 can be set to 1 hour after a medication has been administered. In some examples, the crisis alarm mode 142 ends when either the target value 152 is met or the time limit 154 is met, whichever occurs first. Alternatively, the crisis alarm mode 142 ends when both the target value 152 and the time limit 154 are met. In some examples, the exit criteria 150 is selected such that the target value 152 must be reached within the time limit 154 for the crisis alarm mode 142 to end.

[0065] The exit criteria 150 can be automatically set by the alarm application 126 based on demographic data, health conditions, diagnoses, medications, and / or treatments applied to the patient P. The alarm application 126 can obtain this information by accessing the EMR system 300 from the electronic medical record 302 of the patient P via the communication network 110. Alternatively, the exit criteria 150 can be manually set by a clinician using the display device 114 or one or more user input buttons on the monitoring device 104.

[0066] As Figure 4As shown, the crisis alarm mode 142 also includes a sensitivity level 156, which is adjustable to automatically adjust the upper or lower alarm limit on the target direction 144. For example, the sensitivity level 156 can be selected between high, medium, and low sensitivity levels. The sensitivity level 156 can be automatically set by the alarm application 126 based on the patient P's demographics, health status, diagnosis, medications, and / or treatments. Alternatively, the sensitivity level 156 can be manually set by a clinician using one or more user input buttons on the display device 114 or monitoring device 104.

[0067] Figure 5 This illustrates an example of how Crisis Alert Mode 142 is applied to Chart 500 to monitor vital signs. Figure 5 In the example shown, the monitored vital sign is blood pressure, and graph 500 includes a normal resting value of 120 / 80 mmHg (502), an upper alarm limit of 140 / 90 mmHg (504), and a lower alarm limit of 90 / 60 mmHg (506). The patient's blood pressure is represented by a trend line (508). In this example, the patient is experiencing abnormally low blood pressure (e.g., due to sepsis), and treatment (e.g., vasopressors) is administered at treatment time T0 to raise their blood pressure to a target value between the upper alarm limit (504) and the lower alarm limit (506).

[0068] like Figure 5 As shown, based on the abnormal blood pressure state before treatment time T0, the self-adjusting alarm lower limit 510 is initially set to the initial value X1. In this example, the initial value X1 is based on the blood pressure abnormality state defined as T... -3 Blood pressure measurements are collected during a sliding window of time interval between T0 and T0. At time T0, the self-adjusting alarm lower limit 510 is set to an alarm lower limit 506 for values ​​below 90 / 60 mmHg.

[0069] In one embodiment, based on time T -3 Percentiles are calculated for physiological data values ​​(e.g., blood pressure) acquired from physiological sensor 108 during the first sliding window between treatment time T0 and T0, and the self-adjusting alarm lower limit 510 is initially set to the percentile calculated from treatment time T0. A percentile is a physiological data value for which a given percentage of physiological data values ​​within the first sliding window is below (exclusion definition), or where a given percentage of physiological data values ​​within the first sliding window is equal to or lower than the value (inclusive definition). Percentiles can be set to any given percentage, such as 99%, 95%, etc.

[0070] In another embodiment, based on time T -3The physiological data values ​​(e.g., blood pressure) acquired from the physiological sensor 108 during the first sliding window between treatment time T0 are averaged, and the self-adjusting alarm lower limit 510 is initially set to the standard deviation of the physiological data values ​​from the average value at treatment time T0. The standard deviation is a measure of the amount of change or dispersion of the physiological data values ​​during the first sliding window. Additional algorithms are considered for determining the initial value and subsequent self-adjusting value of the self-adjusting alarm lower limit 510.

[0071] Blood pressure is monitored during consecutive sliding windows until one or more of exit criteria 150 are met. During each sliding window, physiological data values ​​are acquired from physiological sensor 108, and at the end of the sliding window, an adjustment to the self-adjusting alarm lower limit 510 is determined.

[0072] like Figure 5 As shown in the example provided, time T -2 and T +1 The second sliding window between them triggers an automatic adjustment of the alarm lower limit 510 from the initial value X1 to the new value X2. Similarly, time T... -1 and T +2 The third sliding window between the two triggers an automatic adjustment alarm lower limit of 510, which automatically adjusts from the previous value X2 to the new value X3, with time T0 and T... +3 The fourth sliding window between triggers an auto-adjusting alarm lower limit 510, which automatically adjusts from the previous value X3 to the new value X4, and so on, until one or more of the exit criteria 150 are met.

[0073] Advantageously, the sliding windows at least partially overlap each other to provide a smooth level for updating the self-adjusting alarm lower limit 510. For example, the second sliding window at time T -2 The third sliding window overlaps with the first sliding window at time T0. Similarly, the third sliding window overlaps with the first sliding window at time T0. -1 and T +1 The fourth sliding window overlaps with the second sliding window at times T0 and T1. +2 The third sliding window overlaps with the previous one, and so on.

[0074] exist Figure 5 In the example shown, blood pressure is improving, causing the self-adjusting alarm lower limit 510 to adjust in the target direction 144 toward the normal resting value 502 at the end of each sliding window. Alternatively, when blood pressure is not improving, causing the self-adjusting alarm lower limit 510 to adjust away from the normal resting value 502 at the end of any sliding window, an alarm is triggered and the alarm application 126 exits crisis alarm mode 142 to return to normal alarm mode 140.

[0075] Alerts triggered in the crisis alert mode 142 can include local alerts on the monitoring device 104, such as visual alerts (e.g., flashing red lights) and / or audible alerts (e.g., beeping sounds), and / or can also include notifications sent to a mobile device (e.g., a smartphone) carried by a clinician and / or notifications sent to a nurses' station. When an alert is triggered in the crisis alert mode 142, the alert application 126 returns to the normal alert mode 140.

[0076] The self-adjusting alarm lower limit 510 continues to self-adjust until an alert is triggered or an exit criterion 150 is met. As an illustrative example, the exit criterion 150 can include a target value 152 set to the alarm lower limit 506 (e.g., 90 / 60 mmHg). When the self-adjusting alarm lower limit 510 is adjusted above the alarm lower limit 506 (e.g., above 90 / 60 mmHg), as at time T +1 and T +4 The crisis alert mode 142 ends and the alert application 126 returns to the normal alert mode 140 when the self-adjusting alarm lower limit 510 is adjusted to the alarm lower limit 506 (e.g., 90 / 60 mmHg) or when the exit criterion 150 is met, whichever occurs first.

[0077] In some examples, the crisis alert mode 142 ends when the target value 152 (e.g., 90 / 60 mmHg) is met or when the time limit 154 is met, whichever occurs first. Alternatively, the crisis alert mode 142 ends only when both the target value 152 (e.g., 90 / 60 mmHg) and the time limit 154 are met. In some further examples, the crisis alert mode 142 ends when the target value 152 (e.g., 90 / 60 mmHg) is reached within the time limit 154. Other scenarios for ending the crisis alert mode are possible.

[0078] Each sliding window is defined by a fixed time interval. As an illustrative example, the sliding windows are defined by a time interval of 5 minutes. The size of the sliding windows can be adjusted to adjust the sensitivity level 156 of the self-adjusting alarm lower limit 510. For example, decreasing the size of the sliding windows increases the sensitivity level 156, while increasing the size of the sliding windows decreases the sensitivity level 156.

[0079] Additionally, adjusting the amount of overlap between the sliding windows can also be used to adjust the sensitivity level 156 of the self-adjusting alarm lower limit 510. For example, decreasing the amount of overlap increases the sensitivity level 156, while increasing the amount of overlap decreases the sensitivity level 156.

[0080] Figure 5A crisis alert mode 142 is shown that applies a self-adjusting alarm lower limit that self-adjusts in a target direction of increase toward the alarm lower limit 506. In other examples, such as when a patient experiences an abnormally high blood pressure due to hypertension, the crisis alert mode 142 can apply a self-adjusting alarm upper limit that self-adjusts in a target direction of decrease toward the alarm upper limit 504. In still further examples, the crisis alert mode 142 can apply both a self-adjusting alarm lower limit and a self-adjusting alarm upper limit that tighten or converge toward the normal resting value 502.

[0081] In alternative embodiments in which the physiological variable is not continuously monitored but is monitored at intervals, the crisis alert mode 142 can trigger an additional reading after detecting that an interval reading is not in the target direction 144. For example, when the target direction 144 is a blood pressure downward trend, and an interval reading is received that does not have a downward trend, or the blood pressure is decreasing too little, the crisis alert mode 142 can trigger another reading before the next scheduled interval reading to confirm the trend. When the confirmation is not moving in the direction of the target direction 144, the alarm application 126 triggers an alarm and exits the crisis alert mode 142. When the confirmation is moving in the direction of the target direction 144, the alarm application 126 continues to operate in the crisis alert mode 142.

[0082] Figure 6 An example of a method 600 of executing the crisis alert mode 142 by the alarm application 126 installed on the monitoring device 104 is illustrated. The method 600 includes an operation 602 of initiating the crisis alert mode 142. In some examples, the crisis alert mode 142 is initiated by a clinician manually selecting the crisis alert mode 142 upon the clinician operating the monitoring device 104 when the clinician intervenes to restore the vital signs of one or more patients from an abnormal state to a normal state. In other examples, the crisis alert mode 142 is automatically initiated by the alarm application 126 upon determining that a clinician has intervened to restore the vital signs of one or more patients from an abnormal state to a normal state.

[0083] Next, the method 600 includes an operation 604 of setting a starting value for the self-adjusting alarm upper limit or alarm lower limit. In some examples, the starting value is the abnormal state of the vital signs captured by the physiological sensor 108 prior to the medical intervention.

[0084] Next, the method 600 includes an operation 606 to determine a target direction 144 and an exit criterion 150 for the self-adjusting alarm upper or lower limit. The target direction 144 is determined by the alarm application 126 based on the abnormal state of the vital sign and the normal range of the vital sign. For example, when the abnormal state is below the normal range, the target direction 144 is in an increasing target direction 146. When the abnormal state is above the normal range, the target direction 144 is in a decreasing target direction 148. The exit criterion 150 is based on the normal range of the vital sign, such as the upper or lower limit of the normal range. When the upper or lower limit is reached, the alarm application 126 exits the crisis alarm mode 142 and returns to operating in the normal alarm mode 140.

[0085] Once the starting value and the target direction of the self-adjusting alarm upper or lower limit are set, the method 600 proceeds to an operation 608 to receive a plurality of physiological data values from the physiological sensor 108 during a sliding window.

[0086] Next, the method 600 includes an operation 610 to determine a new value of the self-adjusting alarm upper or lower limit at the end of the sliding window. As described above, the new value can be based on a percentile calculated from the physiological data values obtained from the physiological sensor 108 during the sliding window. Alternatively, the new value can be based on a standard deviation from the mean of the physiological data values.

[0087] Next, the method 600 includes an operation 612 to determine whether the new value of the self-adjusting alarm upper or lower limit is in the target direction 144. For example, when the abnormal state of the vital sign is hypotension such that the target direction 144 is to increase towards the normal resting blood pressure value, the operation 612 determines whether the new value for the self-adjusting alarm lower limit has increased. Alternatively, when the abnormal state of the vital sign is hypertension such that the target direction 144 is to decrease towards the normal resting blood pressure value, the operation 612 determines whether the new value for the self-adjusting alarm upper limit has decreased.

[0088] When the new value of the self-adjusting alarm upper or lower limit is not in the target direction 144 (i.e., "No" at operation 612), the method 600 proceeds to an operation 614 to trigger an alarm because the abnormal state of the vital sign has not only failed to improve, but has worsened. After the alarm is triggered, the alarm application 126 exits the crisis alarm mode 142 at operation 620 in which the alarm application 126 returns to operating in the normal alarm mode 140 in which the alarm upper and lower limits for the monitored vital sign are fixed values.

[0089] When the new value of the self-adjusting alarm upper or lower limit is in the target direction 144 (i.e., "yes" at operation 612), method 600 proceeds to operation 616, which includes resetting the self-adjusting alarm upper or lower limit to the new value. As described above, the new value of the self-adjusting alarm upper or lower limit may be based on percentiles calculated from physiological data values ​​acquired from physiological sensor 108 during the sliding window. Alternatively, the new value may be based on the standard deviation from the mean of the physiological data values ​​during the sliding window.

[0090] Method 600 includes operation 618 determining whether exit criterion 150 is met. Exit criterion 150 may include a target value 152 and / or a time limit 154. When exit criterion 150 is met (i.e., "yes" at operation 618), alarm application 126 exits crisis alarm mode 142 at operation 620. When exit criterion 150 is not met (i.e., "no" at operation 618), alarm application 126 repeats operation 610-operation 618.

[0091] Figure 7 An example of an alarm application 126 applied to graph 700 to monitor vital signs is illustrated. Graph 700 is displayed on display device 114 of monitoring device 104. Figure 7 In this context, the monitored vital sign is heart rate, and graph 700 includes an alarm limit 704 set at 130 beats per minute (BPM). The alarm limit 704 can be the default alarm limit, or it can be based on the patient's stable baseline prior to a health crisis that would cause the patient's heart rate to reach an abnormal state.

[0092] In some examples, a patient's stable baseline is captured when vital signs (e.g., heart rate) are at rest at any time before becoming abnormal. In some examples, an enhanced Dickie-Fuller (ADF) test is performed to assess stability upon admission (and periodically thereafter) to determine a patient's stable baseline. In some examples, the clinician decides whether to accept or reject the captured stable baseline.

[0093] exist Figure 7 In the normal alarm mode 140, heart rate is monitored before the clinician intervention occurs at 14:30. In the normal alarm mode 140, physiological data value 712 (e.g., heart rate measurement obtained from physiological sensor 108) experiences a sudden increase after 14:20 and begins to exceed the alarm limit 704, thus triggering an alarm in the normal alarm mode 140.

[0094] Following the clinician intervention at 14:30, heart rate was monitored in Crisis Alert Mode 142, which establishes a self-adjusting alarm limit 708a based on the abnormally high heart rate measured at the time of intervention. The self-adjusting alarm limit 708a is higher than the alarm limit 704 set at 130 BPM.

[0095] The self-adjusting alarm upper limit 708a continuously decreases in the target direction 144 until it reaches the alarm upper limit 704. At this point, the alarm application 126 exits the crisis alarm mode 142 and continues to monitor heart rate in the normal alarm mode 140. In this example, the alarm application 126 exits the crisis alarm mode 142 because the target value 152 of the exit criterion 150 (e.g., 130 BPM) is met. In crisis alarm mode 142, alarms are suppressed, thereby reducing alarm fatigue.

[0096] exist Figure 7 In this example, a second health crisis occurs at approximately 14:40, causing the patient's heart rate to exceed the alarm limit 704, while heart rate is monitored in normal alarm mode 140. The clinician intervenes, causing a second monitoring of the heart rate in crisis alarm mode 142, which establishes a self-adjusting alarm limit 708b based on the abnormally high heart rate measured at the time of the second intervention. In crisis alarm mode 142, alarms are suppressed to reduce alarm fatigue. The self-adjusting alarm limit 708b continuously decreases in the target direction 144 until it reaches the alarm limit 704. At this point, because the target value 152 has been reached, alarm application 126 exits crisis alarm mode 142 and continues monitoring the heart rate in normal alarm mode 140.

[0097] Figure 8 This illustrates another example of an alarm application 126 applied to chart 800 to monitor vital signs. (See example...) Figure 8 As shown, graph 800 is displayed on display device 114 of monitoring device 104. As in the example above, the monitored vital sign is heart rate, and graph 800 includes an alarm upper limit 804 set to 130 BPM. In this example, heart rate is monitored in normal alarm mode 140 until clinician intervention at approximately 17:50. After clinician intervention, heart rate is monitored in crisis alarm mode 142, which establishes a self-adjusting alarm upper limit 808a based on the abnormally high heart rate measured at the time of intervention.

[0098] The self-adjusting alarm upper limit 808a is higher than the alarm upper limit 804 set to 130 BPM. The self-adjusting alarm upper limit 808a decreases in the target direction 144 until approximately 18:00, at which point the physiological data value 812 obtained from the physiological sensor 108 exceeds the self-adjusting alarm upper limit 808a. An alarm is triggered, and the alarm application 126 exits the crisis alarm mode 142 to return to the normal alarm mode 140. In this example, the target value 152 (e.g., 130 BPM) is not reached, and the self-adjusting alarm upper limit 808a increases away from the target direction 144. Advantageously, the crisis alarm mode 142 in this example informs the clinician that the patient is not responding to the intervention as expected, thereby requiring additional intervention.

[0099] In Figure 8 this example, a second intervention occurs at approximately 18:20, causing a second monitoring of the heart rate under the crisis alarm mode 142, which establishes a self-adjusting alarm upper limit 808b based on the abnormally high heart rate measured at the second intervention. The self-adjusting alarm upper limit 808b continuously decreases in the target direction 144 until the physiological data value 812 exceeds the self-adjusting alarm upper limit 808b, at which point an alarm is triggered, and the alarm application 126 exits the crisis alarm mode 142 to return to monitoring the heart rate under the normal alarm mode 140.

[0100] Figure 9 and 10 FIGS. 9 and 10 illustrate examples of the alarm application 126 applied to the graphs 900, 1000 having the same physiological data values to monitor a vital sign, such as a heart rate. Figure 9 and 10 FIGS. 11 and 12 illustrate examples of adjusting the size of the sliding window (see Figure 5 ) to control the sensitivity level 156 of the crisis alarm mode 142.

[0101] In Figure 9 the sliding window is smaller, causing the sensitivity level 156 of the crisis alarm mode 142 to be more sensitive. In Figure 10 the sliding window is larger, causing the sensitivity level 156 of the crisis alarm mode 142 to be less sensitive.

[0102] In Figure 9At approximately 12:45, a first intervention occurs, causing the heart rate to be monitored in the crisis alert mode 142, which establishes a self-adjusting alert upper limit 908a based on the abnormally high heart rate measured at the first intervention. The self-adjusting alert upper limit 908a is higher than the alert upper limit 904, which is set to 130 BPM. The self-adjusting alert upper limit 908a begins to decrease in the target direction 144 until the physiological data values obtained from the physiological sensor 108 exceed the self-adjusting alert upper limit 908a, causing an alert to be triggered, and the alert application 126 exits the crisis alert mode 142 and returns to the normal alert mode 140.

[0103] Further as shown Figure 9 At approximately 12:50, a second intervention occurs, causing the heart rate to be monitored in the crisis alert mode 142, which establishes a self-adjusting alert upper limit 908b based on the abnormally high heart rate measured at the second intervention. The self-adjusting alert upper limit 908b is higher than the alert upper limit 904 and decreases in the target direction 904 until the physiological data values exceed the self-adjusting alert upper limit 908b, causing an alert to be triggered again, and the alert application 126 exits the crisis alert mode 142 and returns to the normal alert mode 140.

[0104] In Figure 10 the sliding window is larger, causing the sensitivity level 156 of the crisis alert mode 142 to be less sensitive. Thus, after the intervention at approximately 12:45, the crisis alert mode 142 establishes a self-adjusting alert upper limit 1008a that decreases in the target direction 144 until the alert upper limit 1004 is reached, causing the target value 152 to be met. At this point, the alert application 126 exits the crisis alert mode 142 and returns to the normal alert mode 140 to monitor the physiological data values. Thus, unlike Figure 9 the alert in Figure 10 is not triggered during the crisis alert mode 142 due to the lower sensitivity level caused by the larger sliding window.

[0105] Figure 11 An example of a method 1100 of continuous physiological monitoring performed by the visualization application 128 installed on the monitoring device 104 is illustrated. The method 1100 is performed to provide additional context and information about the physiological data captured from the physiological sensor 108 to increase confidence in the data and to assist the clinician in making decisions. The method 1100 can be performed to increase the fidelity of the self-adjusting alert limits and / or to change the display of the physiological data on the display device 114, which can assist the clinician in deciding whether to adjust the alert settings, determine whether medical intervention is needed, or to initiate the crisis alert mode 142.

[0106] The alarm application 126 and the visualization application 128 can operate together on the monitoring device 104 such that the method 1100 can be performed in combination or in parallel with the method 600. For example, the monitoring device 104 can be operated in both the normal alarm mode and the crisis alarm mode, while changing the display of the physiological data on the display device 114 to provide additional context and information about the physiological data to assist the clinician in making decisions, such as whether to initiate or exit the crisis alarm mode 142.

[0107] The method 1100 includes an operation 1102 of receiving physiological data from the physiological sensors 108. The physiological data can include heart rate, respiratory rate, blood pressure, blood oxygen saturation (Sp02), end-tidal carbon dioxide (etC02), and the like.

[0108] The method 1100 includes an operation 1104 of receiving artifact data that can affect or alter the physiological data received from the physiological sensors 108. For example, the artifact data can cause the physiological data to be inaccurate, erroneous, and / or spurious. The artifact data can be received concurrently with the physiological data. In some cases, 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.

[0109] The artifact data can include audio sounds captured from the audio sensor 116. As described above, the audio sounds captured from the audio sensor 116 can be used to detect when the patient P is coughing, speaking, and eating, which can affect or alter the physiological data sensed by the physiological sensors 108, such as respiratory rate and etC02 data. Additionally, the artifact data can include motion data detected by the motion sensor 106, such as the patient P’s motion while supported on the patient support system 102, and / or a video feed captured by a camera that detects the patient P’s motion within the area 10. Additional sources of artifact data are contemplated that can be received in operation 1104.

[0110] Alternatively, or in addition to including audio sounds, the artifact data can include motion data captured by the motion sensor 106, which can affect or alter the physiological data, such as heart rate, blood pressure, or respiratory rate data sensed by the physiological sensors 108. As described above, the motion data can be captured from one or more accelerometers attached to the patient, or from accelerometers incorporated into the physiological sensors 108 attached to the patient P, from piezoelectric sensors, load sensors, or combinations thereof, located beneath, within, or on top of the mattress 112 of the patient support system 102.

[0111] Next, method 1100 includes operations 1106 for processing artifact data. In some examples, the artifact data is processed to classify it as coughing, talking, or eating that can affect or alter respiratory rate and etCO2 data, or as motion data that can affect or alter heart rate, blood pressure, or respiratory rate data. Additionally, the artifact data can be processed to quantify and / or classify the intensity of detected artifact data, such as corresponding to the amount of coughing, talking, and eating (e.g., talking vs. shouting), or the amount or type of motion (rolling to one side of the patient support system 102 vs. getting up and leaving the patient support system 102 to walk around area 10).

[0112] Method 1100 includes an operation 1108 determining whether artifact data exceeds a predetermined threshold amount such that the artifact data is sufficient to affect physiological data. When the artifact data is less than the predetermined threshold amount (i.e., "No" at operation 1108), method 1100 continues to monitor physiological data by repeating operation 1102-operation 1108. When the artifact data exceeds the predetermined threshold amount (i.e., "Yes" at operation 1108), method 1100 proceeds to operation 1110, which may include disregarding the artifact-affected physiological data when adjusting one or more self-adjusting alarm limits (see method 600). Additionally or alternatively, operation 1110 may include changing the display of physiological data on display device 114, now referred to... Figure 12 and 13 Describe it.

[0113] Figure 12 An example of a visualization application 128 is illustrated, which applies operation 1110 of method 1100 to the display device 114 of the monitoring device 104 to display a graph 1200. Figure 12 In the example shown, chart 1200 is used to monitor respiratory rate values. The visualization application 128 displays the respiratory rate values ​​differently based on when patient P is detected speaking (e.g., when artifact data exceeds a predetermined threshold) or when patient P is not speaking (e.g., when artifact data does not exceed a predetermined threshold). While chart 1200 displays respiratory rate values, the visualization application 128 can be applied in a similar manner to charts displaying other types of physiological data values, such as heart rate, blood pressure, oxygen saturation (SpO2), end-tidal carbon dioxide (etCO2), etc.

[0114] exist Figure 12In this case, the respiration rate values when the patient P is speaking are displayed in a different color (e.g., red) than the respiration rate values when the patient P is not speaking (e.g., blue), such that the respiration rate values are color-coded. In other examples, the visualization application 128 can apply different kinds of dashed line patterns or other types of visual markers to distinguish the respiration rate values detected when the patient P is speaking from the respiration rate values detected when the patient P is not speaking.

[0115] In this case, the graph 1200 includes a legend 1202 that includes labels that identify visual markers associated with artifacts that can affect or change the respiration rate values, such as when the patient P is speaking (e.g., “talking”). The visual markers can also be associated with normal behavior (e.g., “normal”) when no artifacts are detected. Figure 12

[0116] The legend can include additional labels for visual markers associated with coughing and eating artifacts when the audio sensor 116 detects that the patient P is coughing or eating, and additional labels for additional visual markers associated with movement when the motion sensor 106 detects that the patient P is moving. In some examples, the legend 1202 categorizes the artifacts detected by the audio sensor 116 and the motion sensor 106 together under one label, such as “detected artifacts,” without distinguishing between talking, coughing, eating, and movement artifacts.

[0117] As described above, the alarm application 126 and the visualization application 128 can operate together on the monitoring device 104. Thus, when the motion sensor 106 and the audio sensor 116 detect artifacts (e.g., talking, coughing, eating, and movement), the visualization application 128 can display visual markers to categorize the physiological data values while the monitoring device 104 operates under the normal alarm mode 140 and the crisis alarm mode 142 according to the alarm application 126. Advantageously, the visual markers from the visualization application 128 can help inform the clinician to decide whether to respond to the alarm or adjust the alarm settings, determine whether medical intervention is needed, and / or initiate the crisis alarm mode 142. Thus, the visual markers displayed by the visualization application 128 improve the operation of the monitoring device 104.

[0118] Figure 13 Another example of the visualization application 128 applying the operation 1110 according to the method 1100 to the graph 1300 displayed on the display device 114 of the monitoring device 104 is illustrated. Figure 13 With Figure 12 ​The illustrated example is similar, except that graph 1300 is used to monitor heart rate values that are displayed differently based on whether the motion sensor 106 detected that the patient is in motion or not in motion. For example, graph 1300 includes a legend 1302 that includes “normal” and “motion” labels to distinguish between heart rate values when the patient is in motion from heart rate values when the patient is not in motion.

[0119] In Figure 12 and 13 In alternative examples to those illustrated, physiological data values (e.g., heart rate, respiratory rate, blood pressure, blood oxygen saturation (Sp02), end-tidal carbon dioxide (etC02), etc.) are excluded from the graphs 1200 and 1300 when the motion sensor 106 and audio sensor 116 detect motion artifacts (e.g., speaking, coughing, eating, and motion). In such examples, the legends 1202, 1302 can provide an explanation for the excluded physiological data values, such as due to detection of one or more artifacts. Additionally, automatic or semi-automatic baselines can be performed without using the excluded physiological data values to calculate a patient’s personalized baseline.

[0120] Figure 14 Another example of a method 1400 of continuous physiological monitoring performed by the visualization application 128 installed on the monitoring device 104 is illustrated. The method 1400 is performed to provide additional context and information about the physiological data captured from the physiological sensors 108 to increase confidence in the data and to assist the clinician in making decisions. The method 1400 alters the display of the physiological data on the display device 114 to assist the clinician in deciding whether to adjust alarm settings, determine whether medical intervention is needed, and / or initiate a crisis alert mode 142.

[0121] As described above, the alarm application 126 and the visualization application 128 can operate together on the monitoring device 104 such that the method 1400 can be performed in combination or in parallel with the method 600. For example, the monitoring device 104 can be operational in both the normal alarm mode and the crisis alarm mode, while the display of the physiological data on the display device 114 is altered according to the operations of the method 1400.

[0122] The method 1400 includes an operation 1402 of receiving physiological data from the physiological sensors 108. The physiological data can include heart rate, respiratory rate, blood pressure, blood oxygen saturation (Sp02), end-tidal carbon dioxide (etC02), etc.

[0123] The method 1400 includes receiving a treatment event that can affect or alter physiological data received from the physiological sensor 108, operation 1404. Examples of treatment events include, but are not limited to: medications, surgical procedures, pre- and post-operative procedures, diagnoses, secondary pathologies, rapid response alert codes, sepsis risk scores (including the Systemic Inflammatory Response Syndrome (SIRS) score, Sequential Organ Failure Assessment score (SOFA), and quick SOFA score (qSOFA)), Early Warning Score (EWS), equipment requests (e.g., need for nasal cannula, high flow, BiPap ventilator, etc. for oxygenation), Glasgow Modified Alcohol Withdrawal Scale (GMAWS) score for alcohol and / or opioid withdrawal, and other treatments that can affect or alter physiological data. The treatment event received in operation 1404 is time-stamped to include information such as when the treatment event occurred and how long it lasted.

[0124] When the visualization application 128 is installed on the monitoring device 104, the treatment event can be received from the server 200 via the communication network 110. For example, the visualization application 128 can receive a patient’s diagnosis and secondary pathologies from the patient’s electronic medical record 302 stored in the EMR system 300. As another example, the visualization application 128 can receive an administered medication from the patient’s electronic medical record 402 stored in the EMR system 400.

[0125] Alternatively, or in addition to including receiving treatment events from the server 200, treatment events can be manually entered into the monitoring device 104 by a clinician. In an example in which the display device 114 operates to display the user interface 132 that receives input, the clinician can manually enter a treatment event on the monitoring device 104 through a drop-down menu. In some cases, the drop-down menu can include treatment names or IDs that the clinician can select. Alternatively, the clinician can enter a treatment name or ID into a field on the user interface 132. Further, the clinician can scan a barcode of a medication using a barcode scanner connected to the monitoring device 104 to enter the medication as a treatment event.

[0126] The method 1400 includes processing the treatment event to determine whether the treatment event has an effect on one or more physiological variables measured by the physiological sensor 108 (e.g., heart rate, respiratory rate, blood pressure, blood oxygen saturation (Sp02), end-tidal carbon dioxide (etC02), etc.), operation 1406. The treatment event can be processed to determine whether the treatment event has a targeted effect (e.g., a vasopressor medication that has a targeted effect of elevating blood pressure), or whether the treatment event has an unintended side effect on one or more physiological variables measured by the physiological sensor 108.

[0127] In some cases, side effects can be classified as mild, moderate, or severe. Additionally, the target effect or side effect of each treatment event can be classified or quantified as having an effect within a range of a physiological variable (such as an absolute range or a relative range based on a patient’s baseline value) and within a range of a time window.

[0128] Additionally, each treatment event is processed to determine whether each treatment event can have an interaction with any other treatment event that can have an effect on one or more physiological variables measured by the physiological sensor 108. For example, a certain medication can have a side effect that is based on a patient’s underlying condition.

[0129] Next, the method 1400 includes an operation 1408 that changes the display of the physiological data on the display device 114 based on the processed treatment events. For example, all medications administered to the patient that are known to affect the physiological variables measured by the physiological sensor 108 are displayed on the display device 114 along with the measured physiological data values. Each medication can be displayed as a predefined range overlaid on the measured physiological data values to display the duration of time that the medication was administered to the patient (e.g., when administered through an IV drip), or an estimated duration of time that the medication will affect the measured physiological data values.

[0130] Additionally, any side effects that caused the measured physiological data values to fall within a defined range will be displayed with an appropriate label (e.g., listing the possible cause of the side effect, such as due to an underlying condition, a medication interaction, or other cause). In some examples, the display device 114 can display one or more recommended actions, such as adjusting an alarm setting, adjusting a medication, checking the patient’s reaction, or providing a medical intervention.

[0131] Figure 15 Another example of the visualization application 128 applying the operation 1408 of the method 1100 to a graph 1500 displayed on the display device 114 of the monitoring device 104 is illustrated. In this example, the graph 1500 is used to monitor heart rate values. Figure 15 In the illustrated example, the graph 1500 is used to monitor heart rate values. The visualization application 128 displays the heart rate values along with one or more treatment events that can affect the heart rate values. While the graph 1500 displays heart rate values, the visualization application 128 can be applied in a similar manner to graphs displaying other types of physiological data values (such as heart rate, blood pressure, blood oxygen saturation (Sp02), end-tidal carbon dioxide (etC02), etc.).

[0132] The graph 1500 displays a normal range of heart rate values defined by an upper limit 1502 and a lower limit 1504. In some examples, the upper limit 1502 and the lower limit 1504 of the normal range are based on default values. Alternatively, the upper limit 1502 and the lower limit 1504 of the normal range are based on a patient’s individualized baseline. The normal range between the upper limit 1502 and the lower limit 1504 is overlaid on the heart rate values in a first color tint.

[0133] Graph 1500 also shows a treatment event 1510 that begins at time TO and ends at time Tl. In this example, treatment event 1510 is an albumin infusion, which is used to treat or prevent shock after severe injury, hemorrhage, surgery, or burns by increasing plasma volume. Treatment event 1510 between time TO and time Tl is shown as a visual marker overlaid on the heart rate values in a second color tone. Figure 15

[0134] While Figure 15 Examples in this document show graph 1500 as displaying a single treatment event, but it is contemplated that graph 1500 can display multiple treatment events. In such examples, the clinician can view all treatment events on the timeline, as well as the physiological data values acquired from physiological sensor 108.

[0135] In examples where display device 114 operates to display user interface 132 that receives input, the clinician can select treatment event 1510 to obtain information about the expected effect or impact of treatment event 1510 on the physiological data values acquired from physiological sensor 108. For example, in examples where display device 114 is a touchscreen, the clinician can select treatment event 1510 with their finger or with a stylus to obtain information about the expected effect or impact on the physiological data values acquired from physiological sensor 108. Alternatively, or additionally, the clinician can select treatment event 1510 using a mouse cursor, or can hover the mouse cursor over treatment event 1510 (without actually selecting treatment event 1510) to obtain information about the expected effect or impact on the physiological data values.

[0136] The expected effect of treatment event 1510 can be overlaid on the trend line of the physiological data values acquired from physiological sensor 108 displayed on graph 1500. The expected effect of treatment event 1510 can be color-coded differently between a desired target effect, side effects, and severe side effects that require immediate intervention. The clinician can then use this information to adjust the treatment plan based on the expected effect, adjust alarm settings including adjusting the alarm upper limit and alarm lower limit to an acceptable range based on the expected effect, or intervene and set crisis alarm mode 142. In addition, some treatment events 1510 can display potential drug interactions with other medications within a configured time window to further inform the clinician.

[0137] In Figure 15 ​In the example above, chart 1500 displays the range of heart rate values ​​to be modified, defined by an upper limit 1506 and a lower limit 1508. Based on the example above, the range of modifications can be displayed in response to the selection of treatment event 1510. In the example where chart 1500 displays multiple treatment events, each treatment event can be selected to view the range of heart rate value modifications based on the expected effect of the selected treatment event and its interaction with one or more previous treatment events.

[0138] In some examples, chart 1500 can display the range of heart rate values ​​that can be modified without selecting treatment event 1510. In such examples, the range of heart rate values ​​that can be modified, defined by the upper limit 1506 and the lower limit 1508, is displayed on chart 1500, regardless of whether the clinician selects treatment event 1510.

[0139] The upper limit of the modification range (1506) and the lower limit (1508) are shown as curves illustrating the expected increase in heart rate due to the side effects of albumin infusion, followed by an expected decrease once the side effects begin to subside. Therefore, the upper limit of the modification range (1506) is higher than the upper limit of the normal range (1502), and the lower limit of the modification range (1508) is higher than the lower limit of the normal range (1504). The modification range between the upper limit (1502) and the lower limit (1504) is overlaid on the heart rate values ​​with a third-tone color.

[0140] like Figure 15 As shown, when overlaid on heart rate values, the first, second, and third hues overlap each other and can be used to provide visual information for improving the operation of monitoring device 104. For example, the first hue of the normal range is gray, while the third hue of the modified range is a color (e.g., red, green, blue, yellow, etc.), such that the portion of the modified range overlapping the normal range in graph 1500 is a darker hue, while the portion of the modified range not overlapping the normal range in graph 1500 is a lighter or brighter hue. This can help visualize the expected target effect or side effects of a therapeutic event on the physiological data values ​​measured by physiological sensor 108. Advantageously, the display of therapeutic event 1510, along with the overlapping normal and modified ranges, can help clinicians decide whether to respond to an alarm or adjust alarm settings, determine whether medical intervention is needed, and / or activate crisis alarm mode 142.

[0141] In some alternative examples, when selecting treatment event 1510, only the modified range defined by the upper limit 1506 and the lower limit 1508 is displayed on the trend of heart rate values, while the normal range defined by the upper limit 1502 and the lower limit 1504 is hidden. Such examples prevent the information displayed on graph 1500 from becoming overcrowded.

[0142] As described above, the alarm application 126 and the visualization application 128 can operate together on the monitoring device 104 such that the graph 1500 can be displayed when the monitoring device 104 is operating in the normal alarm mode 140 and the crisis alarm mode 142. In the illustrated example, when the heart rate value exceeds the upper limit 1502 of the normal range of heart rate values, the heart rate value is classified as abnormal regardless of whether the heart rate value is below the upper limit 1506 of the modified range of heart rate values. In such an example, when the heart rate value exceeds the upper limit 1502 of the normal range but is below the upper limit 1506 of the modified range, the alarm application 126 triggers an alarm. Figure 15

[0143] In alternative examples, the heart rate value is classified as abnormal only when the heart rate value exceeds the upper limit 1506 of the modified range. In some cases, the alarm application 126 triggers an alarm whenever the heart rate value exceeds the upper limit 1506 of the modified range of heart rate values. In other cases, the alarm is triggered when the heart rate value exceeds the upper limit 1506 of the modified range by a predetermined distance.

[0144] As another example, the upper limit 1502 and the lower limit 1504 of the normal range of heart rate values can be automatically adjusted when the alarm application 126 is operating in the crisis alarm mode 142. Further, the upper limit 1506 and the lower limit 1508 of the modified range of heart rate values can be automatically adjusted when the alarm application 126 is operating in the crisis alarm mode 142.

[0145] The various embodiments described above are provided by way of illustration only and should not be construed as limiting in any way. Various modifications to the embodiments described above can be made without departing from the true spirit and scope of the disclosure.​

Claims

1. A device for monitoring physiological variables, comprising: At least one processing device; as well as A storage device, wherein a storage instruction, when executed by the at least one processing device, causes the device to: Based on the abnormal state of the aforementioned physiological variables, determine the initial value of the self-adjusting alarm limit; A new value for the self-adjusting alarm limit is determined from the physiological data values ​​received during the time window; as well as When the new value of the self-adjusting alarm limit moves in the target direction, the self-adjusting alarm limit is reset to the new value.

2. The apparatus according to claim 1, wherein, The instruction further enables the device to: An alarm is triggered when the new value of the self-adjusting alarm limit moves in the opposite direction to the target direction.

3. The apparatus according to claim 1, wherein, When the self-adjusting alarm limit is the upper alarm limit, the target direction is the decreasing target direction; and when the self-adjusting alarm limit is the lower alarm limit, the target direction is the increasing target direction.

4. The apparatus according to claim 1, wherein, The new value of the self-adjusting alarm limit is based on the percentile calculated from the physiological data values ​​received during the time window.

5. The apparatus according to claim 1, wherein, The new value of the self-adjusting alarm limit is based on the standard deviation of the physiological data values ​​received during the time window.

6. The apparatus according to claim 1, wherein, The instruction further enables the device to: The updated value of the self-adjusting alarm limit is determined from the physiological data values ​​received during the subsequent time window; When the updated value of the self-adjusting alarm limit moves in the target direction, the self-adjusting alarm limit is reset to the updated value; as well as An alarm is triggered when the updated value of the self-adjusting alarm limit moves in the opposite direction to the target direction.

7. The apparatus according to claim 6, wherein, The instruction further enables the device to: Multiple update values ​​are determined to reset the self-adjusting alarm limit during consecutive time windows until one or more exit criteria are met.

8. The apparatus according to claim 7, wherein, The one or more exit criteria include target values ​​within the normal range of the physiological variables.

9. The apparatus according to claim 7, wherein, The one or more exit criteria include a time limit.

10. The apparatus according to claim 1, wherein, The instruction further enables the device to: Receive artifact data; Determine whether the artifact data exceeds a predetermined threshold amount; as well as When the artifact data exceeds the predetermined threshold, the physiological data affected by the artifact data will be excluded when determining the new value of the self-adjusting alarm limit, or the display of the physiological data value on the display device will be changed.

11. The apparatus according to claim 1, wherein, The instruction further enables the device to: Receiving treatment events; Determine the expected effect of the treatment event on the physiological data values; and Based on the expected results, the display of the physiological data values ​​will be changed.

12. The apparatus according to claim 11, wherein, The physiological data values ​​are displayed as including the treatment event and a range of modifications covering the physiological data values, wherein the range of modifications has an upper and a lower limit based on the expected effect.

13. The apparatus according to claim 12, wherein, The upper and lower limits of the modification range are curves that show the expected increase and decrease of the physiological data values.

14. The apparatus according to claim 13, wherein, The modified range is colored differently based on the position where it overlaps with the normal range of the physiological data values.

15. A method for continuous physiological monitoring, comprising: Based on the abnormal state of physiological variables, determine the starting value of the self-adjusting alarm limit; A new value for the self-adjusting alarm limit is determined from the physiological data values ​​received during the time window; When the new value of the self-adjusting alarm limit moves in the target direction, the self-adjusting alarm limit is reset to the new value; as well as An alarm is triggered when the new value of the self-adjusting alarm limit moves in the opposite direction to the target direction.

16. The method of claim 15, further comprising: The updated value of the self-adjusting alarm limit is determined from the physiological data values ​​received during the second time window; When the updated value of the self-adjusting alarm limit moves in the target direction, the self-adjusting alarm limit is reset to the updated value; as well as The alarm is triggered when the updated value of the self-adjusting alarm limit moves in the opposite direction to the target direction.

17. The method of claim 15, further comprising: Receive artifact data; Determine whether the artifact data exceeds a predetermined threshold amount; as well as When the artifact data exceeds the predetermined threshold, the physiological data affected by the artifact data will be excluded when determining the new value of the self-adjusting alarm limit, or the display of the physiological data value will be changed.

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