Personalized Vital Signs Monitor

Abstract

Systems, methods, and devices are directed to monitoring biological conditions (e.g., vital signs) using patient-specific ranges. An exemplary method includes receiving a first measurement of an individual's vital sign automatically determined from a sensor over a first time period, and determining a baseline for the vital sign based on the first measurement by averaging the first measurement. The threshold for the vital sign can be a predetermined percentage of the baseline. A second measurement of the vital sign can be received from the sensor. In response to determining that at least one of the second measurements is outside the range, an alarm can be triggered.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application No. 62 / 900,179, filed on September 13, 2019, which is incorporated herein by reference in its entirety. Technical Field

[0003] The present disclosure relates to vital signs monitors, and more particularly to vital signs monitors configured to provide an alarm or other indication when a patient's vital signs fall outside of a personalized range. Background Art

[0004] In an inpatient clinical setting outside of an intensive care unit (ICU), a single caregiver may be responsible for monitoring multiple patients. In some cases, a caregiver can proactively measure a patient's vital signs and compare them to a predetermined range consistent with healthy people. When a patient's vital signs are outside of that patient's personalized range, the caregiver can initiate additional medical treatment for that patient. For example, vital signs may indicate that a patient requires intensive care, and the caregiver may transfer the patient to the ICU. In the ICU, patients can be continuously monitored by a dedicated caregiver.

[0005] However, as the number of patients for which a caregiver is responsible increases, the caregiver may measure vital signs less frequently. In non-emergency situations, in some cases, a caregiver may measure a patient's vital signs every 8 hours. While measuring a patient's vital signs at this frequency allows the caregiver to monitor other patients as well, a patient's condition may deteriorate rapidly during the 8-hour sampling period. As a result, the caregiver is less likely to detect early signs of a patient's deteriorating condition, and the caregiver may not be able to initiate early intervention measures for a deteriorating patient.

[0006] Automatic sensors configured to automatically determine a patient's vital signs (without user intervention) can assist caregivers in handling a high volume of patient cases. Unlike manually measuring vital signs, automatic sensors can measure a patient's vital signs without the need for a caregiver to be present or intervene. However, the fidelity of vital sign determinations made by automatic sensors may be significantly lower than the quality of vital sign measurements made directly by a caregiver. For example, in the case of measuring heart rate measurements, an automatic sensor may measure a patient's heart rate regardless of the patient's body position or the position of the sensor. In contrast, a caregiver would ensure that the patient is in a relaxed body position and that the position of the sensor is ideal before measuring the patient's heart rate. Therefore, some measurements measured by automatic sensors are more likely to be inaccurate than measurements measured directly by a caregiver.

[0007] In some cases, automated sensors may measure vital signs semi-continuously, such as once every minute. However, many of these measurements may be inaccurate. When caregivers are informed of every measurement that deviates from a certain threshold, noise in the measurements may increase the risk that caregivers will be called to a patient’s bedside when the patient is not in distress. Noise may also increase the risk that caregivers will not be notified when a patient is in distress. These risks are further exacerbated by natural vital sign variation among healthy patients and the relatively low-fidelity measurement performance of automated sensors. Summary of the invention

[0008] Various implementations of the present disclosure relate to a vital sign monitor that is triggered in response to a vital sign being outside a patient-specific range. Baseline vital signs can be identified for an individual, and a personalized range associated with the baseline vital sign can be further identified. A system that continuously (or semi-continuously) monitors an individual's vital signs can alert a caregiver when the individual's vital signs are outside a personalized range. Therefore, if an individual's baseline is abnormal (e.g., greater than or less than the overall mean), when the individual's vital signs are relatively close to the individual's baseline, the vital sign monitor may not trigger a false alarm even if the vital signs are outside a healthy range defined for the overall population. In addition, when an individual's vital signs are relatively far from the individual's baseline, the vital sign monitor may also trigger an alarm even if the vital signs are within a healthy range defined for the overall population. Therefore, according to different implementations, the sensitivity and specificity of the vital sign monitor can be enhanced.

[0009] Baseline vital signs can be identified using a variety of different methods. In some cases, baseline vital signs are determined by averaging various vital sign measurements of an individual over a period of time when the individual's vital signs are relatively stable. In some cases, baseline vital signs are the median of vital sign measurements. In some cases, vital signs are considered stable when the variance of vital sign measurements over the period is less than a threshold variance. The threshold variance can be, for example, a fixed amount or percentage of the average vital sign of an individual over this period of time. As used herein, the term "average" may refer to the arithmetic mean. In some cases, baseline vital signs are determined based on previous measurements of vital signs during previous hospitalizations, admission procedures, primary care visits, and the like. According to various implementations, when an individual is medically stable, baseline vital signs can be determined based on one or more measurements of an individual's vital signs.

[0010] In some cases, when other features indicate that the individual's vital signs are stable, baseline vital signs can be selectively identified. For example, baseline vital signs can be determined based on measurements taken when the individual is in a fixed position (such as a supine position). In some cases, baseline vital signs can be determined based on measurements taken when the individual moves less than a threshold amount. The position and / or movement of the individual can be identified using at least one of an accelerometer attached to the individual's body, a gyroscope attached to the individual's body, a pressure sensor on the individual's bed, etc. In various implementations, the individual may be given a drug or other treatment that makes its vital sign measurements unstable. In some examples, the baseline can be determined based on measurements over a specific amount of time (e.g., one or more hours, depending on the pharmacokinetics, dosage and dosage form of the drug, and / or the measured bioavailability of the drug) after administration or other treatment.

[0011] The personalized range can be defined according to the upper and lower thresholds. In some cases, at least one of the upper threshold or the lower threshold can be determined according to the baseline vital signs. For example, the lower threshold can be a fixed amount less than the baseline vital signs, a predetermined percentage of the baseline vital signs (e.g., less than 100%), a predetermined percentage between the baseline vital signs and the minimum value of the vital signs (e.g., 50%), or a combination of the two. In some examples, the upper threshold can be a fixed amount greater than the baseline vital signs, a predetermined percentage of the baseline vital signs (e.g., greater than 100%), a predetermined percentage between the baseline vital signs and the maximum value of the baseline vital signs (e.g., 50%), or a combination of the two. In various implementations, both the lower threshold and the upper threshold can be identified based on the baseline vital signs. In some cases, one of the lower threshold and the upper threshold is determined based on the overall value rather than the individual's baseline. For example, the lower threshold and / or the upper threshold can be the same for all individuals in the overall population.

[0012] In various implementations, sensors can measure vital signs of an individual. The monitoring system can compare the measured vital signs to a personalized range for the individual. If the system determines that the individual's vital signs are outside the personalized range, the system can trigger an alarm. In some cases, the system may only trigger an alarm if the individual's vital signs are outside the personalized range for a predetermined amount of time or a predetermined number of measurements, which can prevent false alarms.

[0013] In various examples, the system can also monitor the rate of change of the vital sign measurements and trigger an alarm based on the rate of change. In some cases, the rate of change can be an average rate of change based on multiple vital sign measurements. In some implementations, the system can compare the rate of change with a range and trigger an alarm when the rate of change is outside the range. In various examples, when the system identifies that the measured vital signs of an individual may be outside the vital sign range and the rate of change is outside the rate of change range, the system can selectively trigger an alarm. The range can be pre-set by a caregiver, automatically set according to historical trends of the monitored individual, automatically set according to previous analysis (e.g., according to previous studies indicating rates of change that may be associated with dangerous situations (such as heart attacks), etc. In some cases, when the measured vital signs may be below the vital sign range and the rate of change may be below a first threshold, or when the measured vital signs may be above the vital sign range and the rate of change may be above a second threshold, the system can selectively trigger an alarm. Therefore, the system can trigger an alarm based on the trend of changes in the measured vital signs over time.

[0014] When the alarm is triggered, the electronic device may output a warning and / or alarm to at least one caregiver (e.g., a nurse, a doctor, etc.). In some cases, the warning and / or alarm may indicate the location and / or identity of the individual.

[0015] According to the implementation of the present disclosure, various vital signs may be monitored, for example, at least one of heart rate, blood pressure, blood oxygen saturation percentage, respiratory rate, core temperature or peripheral temperature may be monitored. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The following drawings, which constitute a part of this disclosure, are illustrative of the described technology and are not meant to limit the scope of the claims in any way.

[0017] Figure 1 An example environment for continuously monitoring vital signs of multiple patients is shown.

[0018] Figure 2 An example of a visualization interface output by a clinical device is shown.

[0019] Figure 3A and Figure 3B An example of vital sign measurements taken semi-continuously over a period of time is shown.

[0020] Figure 4A and Figure 4B Examples of individual vital sign measurements and rates of change are shown.

[0021] Figure 5 An example process for identifying a personalized range of biological condition measurements that may be used to monitor an individual is shown.

[0022] Figure 6 An example process for triggering an alarm based on a measurement of a biological condition is shown.

[0023] Figure 7 An example system including at least one device is shown. In some implementations, Figure 7 The system shown can perform any of the functions described herein.

[0024] Specific implementation method

[0025] Various implementations of the present disclosure will be described in detail with reference to the accompanying drawings, wherein the same reference numerals present the same parts and components in multiple views. In addition, any examples listed in this specification are not intended to be limiting, but merely to list many possible implementations.

[0026] Figure 1 An example environment 100 for continuously monitoring the vital signs of multiple patients is shown. In some cases, the example environment 100 may be associated with a medical institution. Figure 1 As shown, the first to nth individuals 102-1 to 102-n can be monitored by the first to nth sensor devices 104-1 to 104-n, where n is a positive integer. As used herein, the terms "individual", "patient" and their equivalents may refer to people who may be actively monitored by a medical institution. In some implementations, individuals 102-1 to 102-n may refer to individuals who are at least temporarily hospitalized in a medical institution. For example, the first individual 102-1 may be an individual monitored after a surgical operation. In some implementations, individuals 102-1 to 102-n can be monitored inside the ICU, outside the ICU, or in other environments where continuous care and supervision are provided by a medical provider. For example, individuals 102-1 to 102-n can be monitored in one or more medical wards.

[0027] Sensor devices 104-1 to 104-n may include sensors that measure, sense, detect, and / or otherwise determine various conditions of individuals 102-1 to 102-n. As used herein, the terms "sensor," "biosensor," "vital sign sensor," and their equivalents may refer to sensors configured to measure, sense, detect, and / or otherwise determine a biological condition of an individual. As used herein, the terms "biological condition," "condition," and their equivalents may refer to a physical parameter of an individual's body or a measure based on a physical measurement of an individual's body. In some examples, a biological condition may be a vital sign (e.g., blood pressure, heart rate, body temperature, respiratory rate, blood oxygen saturation, etc.).

[0028] In some cases, the sensor may further report the measured biological condition to one or more external devices. Some examples of sensors include pressure sensors (e.g., pressure sensors mounted on a hospital bed to sense the position of an individual lying on the bed), blood pressure sensors (e.g., blood pressure sensors including blood pressure cuffs, sensors that measure blood pressure based on pulse wave velocity, etc.), heart rate sensors (e.g., smart watch sensors), body temperature sensors (e.g., infrared thermometers), respiratory rate sensors (e.g., respiratory rate monitors), end-tidal carbon dioxide sensors, blood oxygen saturation sensors (e.g., pulse oximeters and / or other sensors that measure peripheral blood oxygen saturation (SpO2) in arterial blood), chemical sensors (e.g., glucose sensors), electrical sensors (e.g., electrocardiogram (ECG) sensors, electroencephalogram (EEG) sensors, etc.), consciousness sensors (e.g., devices that prompt individuals to perform interactive psychological exercises), etc. Some sensors in the sensor devices 104-1 to 104-n may include movement sensors (e.g., gyroscopes, accelerometers, etc.), position sensors (e.g., pressure sensors on the beds of individuals 102-1 to 102-n), etc.

[0029] According to some implementations, sensor devices 104-1 to 104-n may measure the patient condition multiple times within a time interval. In some cases, sensor devices 104-1 to 104-n may sample the condition semi-continuously or periodically. As used herein, the term "semi-continuously" may refer to measurements performed at a sampling rate that meets or exceeds a minimum sampling rate defined according to the Nyquist theorem. In some examples, any one of sensor devices 104-1 to 104-n may have a sampling rate of approximately 1-100 samples per minute, approximately 1-100 samples per hour, approximately 1-100 samples per day, and the like.

[0030] The sensor devices 104-1 to 104-n may send data indicating the measured values ​​to the monitoring system 108 via the first network 106. In some cases, the sensor devices 104-1 to 104-n may measure various parameters (e.g., pressure, temperature, pulse frequency, electrical signals, etc.) associated with the individuals 102-1 to 102-n, generate signals indicating the measured values ​​based on these parameters, and send the signals to the monitoring system 108. In some cases, the measured values ​​may be derived based on the parameters by the sensor devices 104-1 to 104-n and / or the monitoring system 108. As used herein, the term "network" and its equivalents may refer to any suitable communication network through which multiple nodes can exchange data. Examples of networks include wide area networks (WANs), such as the Internet; personal area networks (PANs); local area networks (LANs), metropolitan area networks (MANs), etc. The network may be wireless, so that the nodes may communicate with each other via one or more wireless protocols (e.g., WLAN, Wi-Fi, Bluetooth, etc.). In some cases, the nodes may exchange data in the form of one or more data packets. For example, the sensor devices 104 - 1 to 104 - n may generate data packets by packaging data indicating measurement values ​​into the data packets and transmit the data packets to the monitoring system 108 through the first network 106 .

[0031] The monitoring system 108 may be configured to analyze the measurements and selectively report an indication of the measurements. According to various implementations, the monitoring system 108 may time-average the measurements and report the average. In other words, the monitoring system 108 may report the average of the previous a measurements taken during the time interval, where a is a positive integer. For example, the monitoring system 108 may report the arithmetic mean of the measurements taken within the previous hour. In some examples, the monitoring system 108 may not report every measurement. For example, the monitoring system 108 may identify multiple measurements of the blood pressure of the first individual 102-1 measured over a time period (e.g., one hour), determine the average of the blood pressure of the first individual 102-1 over the time period, and report the average without reporting every measurement.

[0032] The monitoring system 108 can determine the personalized baseline associated with the individuals 102-1 to 102-n based on the measurements made by the sensor devices 104-1 to 104-n. For example, the baseline associated with the first individual 102-1 can be determined based on the measurements made by the first sensor device 104-1. In some cases, each baseline can be identified based on multiple measurements made within a time period (e.g., 1 hour to 6 hours, etc.). For example, the baseline associated with the first individual 102-1 can be the average or median of multiple measurements made by the first sensor device 104-1 within the time period. In some cases, if the measured values ​​have a symmetrical distribution, the baseline can be defined as the average; if the measured values ​​have an asymmetrical distribution, the baseline can be defined as the median. As used herein, the terms "symmetrical distribution", "Gaussian distribution", "normal distribution", etc. can refer to a sample set with a sample skewness whose absolute value is less than a predetermined threshold (e.g., 0.25). As used herein, the terms "asymmetrical distribution", "skewed distribution", etc. can refer to a sample set with a sample skewness whose absolute value is greater than or equal to a predetermined threshold (e.g., 0.25).

[0033] In some examples, the monitoring system 108 may confirm that the plurality of measurements during the time period are stable. For example, the monitoring system 108 may identify that the variance of the plurality of measurements may be below a certain level (e.g., 5-10% of the average of the plurality of measurements, etc.). If the measurements are not stable (e.g., if the variance is above a certain level), the monitoring system 108 may not calculate a baseline.

[0034] In some cases, the monitoring system 108 may determine that the individual has not moved during the time period, or has only moved a minimum amount. For example, when the individual is determined to have moved less than a threshold distance (e.g., less than 6 inches), less than a threshold speed or velocity (e.g., less than 1 meter / second), less than a threshold acceleration (e.g., less than 1 meter / second squared), etc., the individual may be moving a "minimum amount." The sensor devices 104-1 to 104-n may include one or more movement sensors attached to the individuals 102-1 to 102-n. For example, the sensor devices 104-1 to 104-n may include at least one accelerometer and / or at least one pressure sensor on at least one bed of the individuals 102-1 to 102-n. The movement sensor may measure the movement of the individuals 102-1 to 102-n and report the measurement of the movement to the monitoring system 108 via the first network 106. Since movement can affect the measurement of various biological conditions, the monitoring system 108 may not set a baseline for the biological conditions measured during the time frame in which the individuals 102-1 to 102-n move a non-minimum amount. The monitoring system 108 can compare the measurement of movement to a threshold value (e.g., a threshold distance, a threshold velocity, a threshold speed, a threshold acceleration, etc.) and identify a baseline based only on the measurements during a time period when the movement measurement is below the threshold value. In various implementations, a movement threshold associated with a biological condition can be determined by monitoring the movement of at least one individual and the biological condition measurement. The movement threshold can be a maximum movement measurement associated with an accurate biological condition measurement. Thus, the movement threshold can be a maximum amount of movement that does not reduce the accuracy of the biological condition measurement.

[0035] In some examples, the monitoring system 108 can determine that the individual maintained a certain position during the time period. The sensor devices 104-1 to 104-n may include one or more position sensors associated with the individuals 102-1 to 102-n. For example, the sensor devices 104-1 to 104-n may include at least one gyroscope, at least one pressure sensor, and / or at least one accelerometer on at least one bed of the individuals 102-1 to 102-n, wherein the measurements from the gyroscope, pressure sensor, and / or accelerometer can be used to identify the posture and / or position of the individuals 102-1 to 102-n. The position sensor can measure the position of the individuals 102-1 to 102-n in real time and report the position measurements to the monitoring system 108. The monitoring system 108 can selectively establish a baseline based on biological condition measurements taken when the individuals 102-1 to 102-n are in a stable position. For example, the monitoring system 108 may use the position measurements to confirm that the first individual 102-1 has not changed position for a particular time period, and may identify a baseline biological condition based on measurements taken during the particular time period. In some cases, the monitoring system 108 may selectively establish a baseline based on biological condition measurements taken when the individuals 102-1 to 102-n are in a predetermined position (e.g., the position that the individuals 102-1 to 102-n will be in during a subsequent monitoring period). For example, the monitoring system 108 may use the position measurements to confirm that the first individual 102-1 is in a supine position for a particular time period, and may identify a baseline biological condition based on measurements of the first individual 102-1 for the particular time period.

[0036] In some cases, the monitoring system 108 can confirm that the individual 102-1 to 102-n has not been administered a drug (e.g., drug, medicine, biologic, pharmaceutical, etc.) that actively changes the individual's biological condition during the time period. For example, when albuterol is administered to an individual, the individual's heart rate increases. In some examples, the monitoring system 108 can confirm that the individual has not been administered the drug during the time period. If there is a delay between administration and the drug's effect on the biological condition, the monitoring system 108 can confirm that the drug's effect on the biological condition did not occur during the time period. For example, some forms of albuterol take effect within 15 minutes of administration, reach peak effect 60-90 minutes after administration, and are effective within 5 hours after administration.

[0037] In some exemplary implementations, the monitoring system 108 may determine that the first individual 102-1 has been administered a specific medication (e.g., active ingredient, dosage, dosage form, etc.) and the time (i.e., administration time) at which the first individual 102-1 has been administered the specific medication. The monitoring system 108 may identify the medication and administration time in a variety of ways. For example, the monitoring system 108 may communicate with an electronic medical record (EMR) system 110 via a second network 112. The EMR system 110 may store various health record information of the individuals 102-1 to 102-n, and selectively send data indicating the health record information to the monitoring system 108. In various examples, the monitoring system 108 may access the EMR system 110 to identify the medication and / or administration time of the first individual 102-1.

[0038] The monitoring system 108 can predict when the drug will be active for the first individual 102-1. For example, the monitoring system 108 can predict the time interval at which the drug is bioavailable to the first individual 102-1. In some cases, the monitoring system 108 can access a local database that indicates the time interval between the administration and the onset and / or duration of various drugs (including the drug administered to the first individual 102-1). Based on the administration time of the drug, the time interval between the administration and the onset of the drug, and / or the duration of the drug, the monitoring system 108 can confirm that the drug administered to the first individual 102-1 is not active during the time interval of the measurement of the biological condition. Therefore, the monitoring system 108 can identify the baseline of the biological condition of the first individual 102-1 based on these measurements. In some cases, the monitoring system 108 will not set the baseline of the biological condition based on the measurement of the biological condition performed during the time period when the drug may be active and / or affect the biological condition.

[0039] As used herein, the term "confounding factor" may refer to at least one of medical treatment, surgical treatment, administered medication, biologically active drug, individual movement, individual location, etc. that may affect the measured value of the biological condition of the individual. In some examples, the monitoring system 108 may confirm that there are no confounding factors associated with the first individual 102-1 during a specific time period, and may identify a baseline of the biological condition of the first individual 102-1 based on the measured value of the biological condition during the specific time period.

[0040] In some implementations, the monitoring system 108 may selectively set a baseline for the individuals 102-1 to 102-n based on measurements taken when the individuals 102-1 to 102-n are in a state consistent with future monitoring. For example, if it is expected that the first individual 102-1 will be treated with an opioid during future monitoring, the monitoring system 108 may identify a baseline respiratory rate for the first individual 102-1 based on respiratory rate measurements taken when the first individual 102-1 is administering opioids. In some cases, the monitoring system 108 does not set a baseline respiratory rate for the first individual 102-1 when the first individual 102-1 is not administering opioids. Thus, the monitoring system 108 may identify a baseline based on the condition that the individuals 102-1 to 102-n will be in during monitoring.

[0041] In various examples, the monitoring system 108 can use previous measurements of the biological condition of the individuals 102-1 to 102-n to determine the baseline. For example, the monitoring system 108 can further analyze the measurements taken by the sensor devices 104-1 to 104-n based on the health record information. For example, the monitoring system can access the EMR system 110 to identify measurements of the biological condition 108 during the individual's hospital admission process, measurements of the biological condition during a previous hospitalization of the individual, measurements of the biological condition of the individual during a previous primary care visit, and so on.

[0042] In various implementations, the monitoring system 108 may further identify a range of the biological condition based on the baseline. In various implementations, a "primary range," "baseline range," "personalized range," etc. for an individual may be a range of biological condition measurements that is defined at least in part by a threshold associated with the baseline. A range may be defined by an upper threshold and a lower threshold. In various implementations, the monitoring system 108 may identify at least one of the upper threshold or the lower threshold based on the baseline.

[0043] In some cases, at least one threshold value can be determined by subtracting or adding an offset to the baseline. The offset can be a predetermined percentage of the baseline. For example, the offset can be 20%, 10%, 5% or other percentages of the baseline. In some cases, the offset can be a fixed value. In some examples, the offset can be 40, 30, 20, 10, 5 or other values ​​of the baseline measurement unit. For example, if the baseline is a baseline blood pressure value in mmHg or kPa, the offset can be 30, 20, 10, 5 or other values ​​in mmHg or kPa. In some cases, the offset can be determined based on the maximum or minimum value of the biological condition and the baseline. For example, the offset can be equal to a fixed percentage of the absolute value of the difference between the minimum or maximum value and the baseline. In some cases, the fixed percentage can be 10%, 20%, 30%, 40%, 50%, 60%, 70% or other percentages. For example, if the baseline heart rate is 40 beats per minute and the minimum heart rate is 0 beats per minute, the offset may be 25% of the difference between 40 beats per minute and 0 beats per minute, or 10 beats per minute.

[0044] In some cases, the range can be determined based on a confidence interval associated with the measurement value. For example, the range can be defined as a 90% confidence interval, a 95% confidence interval, a 99% confidence interval, etc. calculated based on a stable biological condition measurement value.

[0045] In various examples, the monitoring system 108 can define at least one of the upper boundary or the lower boundary independently of the baseline. In some cases, a biological condition may be associated with a boundary that indicates that the individual may be unstable regardless of the individual's baseline. For example, a heart rate of 40 beats per minute may be the lowest lower boundary, while a heart rate of 200 beats per minute may be the highest upper boundary, regardless of the individual's baseline heart rate. Thus, in some cases, the monitoring system 108 can define the boundaries of the range based on predetermined levels associated with unhealthy biological conditions for any individual in the general population.

[0046] Monitoring system 108 may monitor additional measurements of the biological condition from sensor devices 104 associated with individual 102 based on the baseline and / or static or dynamic range of the biological condition. In some cases, monitoring system 108 may trigger an alarm in response to identifying that at least one measurement of the biological condition of the individual may be outside the range. For example, monitoring system 108 may average the measurements of the biological condition over a particular time (e.g., one hour) and may trigger an alarm in response to identifying that the average may be outside the range. In some cases, monitoring system 108 may trigger an alarm in response to identifying that a predetermined number (e.g., 5) of the measurements of the biological condition are outside the range within a particular time period (e.g., 1 hour).

[0047] In some examples, monitoring system 108 may identify a dynamic range of measurements for monitoring a biological condition of at least one of individuals 102-1 to 102-n. In various cases, there may be a predetermined trend between the medical characteristics of individual 102 and the biological condition. For example, albuterol may increase the individual's heart rate after administration. In some examples, analgesics (such as opioids) may reduce the individual's blood pressure after administration. In some cases, surgery may increase the patient's heart rate for a longer period of time. As used herein, an individual's "medical characteristics" may refer to medical treatments administered to the individual, surgical treatments administered to the individual, drugs administered to the individual, drug dosages administered to the individual, biological conditions (e.g., vital signs) of the individual, allergies (e.g., allergies to specific drugs) of the individual, genetic predispositions of the individual (e.g., genotypes and / or transcriptomes of the individual), and the like.

[0048] In various implementations of the present disclosure, the monitoring system 108 may identify trends between one or more medical features and a biological condition. In some examples, the monitoring system 108 may receive various health profile information for various previous patients from the EMR system 110. The monitoring system 108 may train a neural network to identify trends between medical features and biological conditions using the health profile information for previous patients. After training the neural network, the monitoring system 108 may use the trained neural network to identify a mathematical relationship between one or more specific medical features and a specific biological condition. In some cases, the mathematical relationship may be predetermined and stored in the monitoring system 108. For example, a mathematical relationship between a biological condition and the administration of a specific drug may be identified based on a predetermined pharmacokinetic model of the bioavailability of the specific drug.

[0049] Monitoring system 108 may receive an indication of one or more medical characteristics of individual 102. In some cases where the one or more medical characteristics include at least one other biological condition, measurements of the other biological condition may be received from sensor device 104. In some examples, the indication of the one or more medical characteristics may be received from EMR system 110. For example, monitoring system 108 may access EMR system 110 to determine that a particular medication was administered at a particular time.

[0050] Using the mathematical relationship between one or more medical characteristics and the biological condition, the monitoring system 108 can adjust the primary range of the biological condition (e.g., adjust the upper threshold and / or lower threshold) based on the indication of the one or more medical characteristics. For example, the mathematical relationship between the albuterol dose and the time after administration can be used to increase the lower threshold and / or upper threshold of the heart rate range of the individual 102 within 1 hour after the administration of albuterol to the individual.

[0051] In some cases, the monitoring system 108 may expand or reduce the range, or adjust the offset of the range based on one or more medical characteristics. Medical characteristics may be associated with an increased risk of a particular pathological outcome. For example, individuals taking opioids may have an increased risk of irregular breathing. In one example, individuals with Marfan syndrome may have an increased risk of heart damage due to high blood pressure. According to various implementations, the monitoring system 108 may store various rules that associate medical characteristics with offsets, and may adjust the primary range based on those rules. For example, the monitoring system 108 may automatically increase the lower threshold of the respiratory rate range of the individual 102 in response to identifying that opioids have been administered to the individual 102 within the past 4 hours.

[0052] In various implementations, the monitoring system 108 may further monitor the rate of change of the additional measurements. For example, the monitoring system 108 may calculate a sliding average of the rate of change of the additional measurements over a given time period (e.g., one hour). The monitoring system 108 may identify a range of rates of change that represent normal conditions. For example, the range of the rate of change may be identified as an amount of change greater than ±1%, ±5%, ±10%, ±20%, ±30%, or some other percentage range of the baseline over the course of one minute, one hour, etc. In some cases, the range of the rate of change may be defined as 90%, 95%, 99%, or other percentages of a confidence interval of a previously determined rate of change associated with a previously sent individual measurement.

[0053] If the monitoring system 108 identifies that at least one rate of change of the measurements of the biological condition may be outside the range, the monitoring system 108 may trigger an alarm. For example, the monitoring system 108 may trigger an alarm in response to identifying that the average rate of change is outside the range. As used herein, an alarm may be "triggered" when the monitoring system 108 causes the output of a signal associated with the alarm. For example, the monitoring system 108 may output an indication of the alarm on a monitor (or some other output device associated with the monitoring system 108), the monitoring system 108 may generate a signal indicating the alarm and send it to an external device that outputs an alarm indication, etc. In some cases, the monitoring system 108 may trigger an alarm in response to identifying that a predetermined number (e.g., 5) of the measurements of the biological condition have a rate of change that remains outside the range for a specific period of time (e.g., 1 hour).

[0054] In some cases, the monitoring system 108 can trigger an alarm when one of the biological condition measurements or the rate of change is outside of its respective range and / or when both the biological condition measurements and the rate of change are outside of their respective ranges. For example, the monitoring system 108 can selectively trigger an alarm when the biological condition is measured outside of a first range and / or the rate of change is measured outside of a second range. In some cases, the monitoring system 108 can trigger an alarm when one of the biological conditions is outside of a first range and the rate of change is outside of a second range. In some cases, the monitoring system 108 can selectively trigger an alarm when multiple biological conditions (and / or associated rates of change) are outside of their respective ranges.

[0055] In some examples, if the monitoring system 108 identifies that one or more confounding factors are present during the time period in which the biological condition measurements are measured, the monitoring system 108 may not trigger an alarm. Thus, the monitoring system 108 may not trigger an alarm when the abnormal biological condition measurements and / or rate of change may be caused by at least one confounding factor.

[0056] The monitoring system 108 may communicate with the 1st to mth clinical devices 114-1 to 114-m via the third network 116, where m is a positive integer. In various implementations, the monitoring system 108 may selectively report information about the individuals 102-1 to 102-n to the clinical devices 114-1 to 114-m. The information may be indicated in data sent from the monitoring system 108 to the clinical devices 114-1 to 114-m. In some cases, the monitoring system 108 may control, or otherwise cause at least one user interface associated with the clinical devices 114-1 to 114-m.

[0057] The monitoring system 108 may trigger an alarm by sending a message (e.g., a signal) to the first to mth clinical devices 114-1 to 114-m. In some cases, the message may indicate an individual (e.g., the first individual 102-1) whose biological condition may be outside the range. For example, the message may indicate the identity of the individual (e.g., name, patient identifier, etc.) or the location of the individual (e.g., bed identifier, room identifier, etc.). In some examples, the message may indicate a biological condition whose measurement value and / or rate of change is outside the applicable range.

[0058] According to some examples, the monitoring system 108 may cause at least one of the clinical devices 114-1 to 114-m to output a warning or alarm in response to determining that at least one biological condition of the individual is changing (e.g., at least one biological condition measurement and / or rate of change is outside of a primary range, below a lower threshold, above an upper threshold, etc.). As used herein, the term "warning" may refer to a signal that can be output from an electronic device that indicates that the individual may be deteriorating, but the individual may not require immediate (e.g., bedside) assistance. As used herein, the term "alarm" may refer to a signal that can be output from an electronic device that indicates that the individual may be in medical distress and requires immediate assistance. In some cases, the monitoring system 108 may only cause the clinical devices 114-1 to 114-m to output an alarm or alert in response to determining that multiple biological conditions are changing. For example, when the heart rate and blood pressure of the first individual 102-1 are determined to be outside the primary range of the first individual 102-1, the monitoring system 108 may instruct the first clinical device 114-1 to output an alarm associated with the first individual 102-1, but when the heart rate of the first individual 102-1 is outside the primary range and the blood pressure of the first individual 102-1 is within the primary range, the monitoring system 108 does not instruct the first clinical device 114-1 to output an alarm. In some examples, when the heart rate and body temperature of the first individual 102-1 are determined to be outside the primary range (e.g., indicating that the first individual 102-1 is sepsis), the monitoring system 108 may instruct the first clinical device 114-1 to output an alarm associated with the first individual 102-1, but when only one of the heart rate or body temperature is outside its respective primary range, the monitoring system 108 does not instruct the first clinical device 114-1 to output an alarm. In some cases, the monitoring system 108 may indicate other levels associated with various patient states to the clinical devices 114-1 to 114-m.

[0059] Clinical devices 114-1 to 114-m can output warnings and / or alarms in various ways. In some cases, clinical devices 114-1 to 114-m can output warnings and / or alarms as auditory signals, which can be heard by at least one caregiver. For example, clinical devices 114-1 to 114-m can be pagers, which indicate that a caregiver should call another caregiver or should directly care for an individual by outputting an audible ring. In some implementations, clinical devices 114-1 to 114-m can output warnings and / or alarms as tactile signals, which can be felt by at least one caregiver. For example, clinical devices 114-1 to 114-m can vibrate. According to various implementations, clinical devices can output warnings and / or alarms as visual signals. In some examples, clinical devices 114-1 to 114-m can display pop-up windows, flashing icons, colors, and various user interface elements that depict alarms. Alarms and warnings can be provided on various user interfaces of clinical devices 114-1 to 114-m.

[0060] Warnings and / or alarms output by clinical devices 114-1 to 114-m may prompt a caregiver to monitor individuals 102-1 to 102-n associated with the warnings and / or alarms. In some cases, at least one caregiver may disable the warnings and / or alarms through the user interface. For example, an alarm indicating that the first individual 102-1 requires additional attention may be disabled in response to the caregiver acknowledging the alarm and / or arriving at the bedside of the first individual 102-1.

[0061] Figure 2 An example of a visual interface 200 output by a clinical device 202 is shown. In some cases, Figure 2 The clinical device 202 shown may be the Figure 1 Any of the described first through mth clinical devices 114 - 1 through 114 - m .

[0062] In various implementations, the visual interface 200 can display the status of various individuals being monitored in a clinical environment (e.g., a hospital). In some examples where the clinical device 202 can be associated with a particular caregiver (e.g., assigned to, carried by, etc.), the visual interface 200 can display the status of multiple (e.g., all) individuals whose care is managed by the particular caregiver. For example, a nurse can be responsible for managing the care of 3-10 patients in a medical ward environment or 1-2 people in an ICU environment.

[0063] Visual interface 200 may display a table having a plurality of entries corresponding to a plurality of individuals being monitored, respectively. Each entry may include four fields: patient identifier 204, vital sign 206, rate of change 208, and status 210. In a given entry, patient identifier 204 may indicate a unique identifier of the individual being monitored. In some cases, patient identifier 204 may include at least one of the name of the individual, the location of the individual in a medical facility (e.g., a room identifier, a bed identifier, etc.), an identifier assigned to the individual at the time of admission (e.g., a unique string assigned to the individual), etc.

[0064] In a given entry, vital signs 206 may indicate a measurement of a biological condition of the individual and / or a running average of the measurement. In some cases, vital signs 206 may be updated in real time as the biological condition is measured. Figure 2 In the illustrated implementation, vital sign 206 represents a measurement of the individual's heart rate (e.g., in beats per minute). In some examples, vital sign 206 may additionally or alternatively represent a measurement and / or a sliding average of the measurements of at least one of the individual's blood pressure, oxygen saturation percentage, respiratory rate, core body temperature, or peripheral temperature. Rate of change 208 may represent the rate of change of vital sign 206 over a given time interval. In some cases, rate of change 208 may represent the rate of change between a current measurement (or average) displayed as vital sign 206 and a previous measurement (or average) of vital sign 206 divided by the time interval between obtaining the current measurement (or average) and obtaining the previous measurement (or average) (or the difference between the time intervals over which the measurements were averaged). In various implementations, rate of change 208 may be a sliding average of the rate of change between measurements and / or averages. For example, rate of change 208 may correspond to the average rate of change of measurements taken during the previous hour, two hours, three hours, etc. In Figure 2 In the example shown, the rate of change can be the rate of change of heart rate (e.g., in units of beats per square minute, beats per minute*hour, etc.).

[0065] The status 210 of a given entry may indicate whether the individual requires assistance. Based on the individual's vital signs 206 and / or rate of change 208, the monitoring system may identify whether the individual requires assistance and cause the clinical device 202 to output the status 210 based on the identification result. Figure 2In the example shown, the state 210 can have one of three levels: an alarm level, a warning level, and a normal level. In various implementations, the state 210 can have one of any number of levels representing varying degrees of patient status, assistance required, severity of a medical condition experienced by the monitored individual, etc. When the state 210 is at the alarm level, the individual may require immediate or emergency assistance. When the state 210 is at the warning level, the individual may be deteriorating but may not require immediate assistance. When the state 210 is at the normal level, the individual may be stable and may not require immediate assistance.

[0066] exist Figure 2 In the example shown, the visual interface 200 can display the status of the first to nth individuals. In the entry corresponding to the first individual, the vital sign 206 can be displayed as "47" (e.g., heart beats per minute), and the rate of change 208 can be displayed as "-5" (e.g., heart beats per square minute). In some examples, the first individual may have a lower threshold of 50 for the biological condition indicated by the vital sign 206, and a lower threshold of -4 for the rate of change 208. Because both the vital sign 206 and the rate of change 208 are below their respective lower thresholds, the first individual may need immediate assistance. Therefore, the state 210 can correspond to "ALERT". In some cases, the color of the entry indicating "ALERT" may be different from other entries corresponding to other states (e.g., "Warning" or "Normal").

[0067] In the entry corresponding to the second individual, vital sign 206 may be displayed as "49" (e.g., beats per minute) and rate of change 208 may be displayed as "1" (e.g., beats per square minute). In some cases, the second individual may have a lower threshold of 50 for the biological condition indicated by vital sign 206 and may have a lower threshold of -4 for rate of change 208. Since the second individual's vital sign 206 may be below its threshold, but the rate of change 208 may be above its threshold, the second individual may be deteriorating but does not require immediate assistance. Therefore, status 210 may be displayed as "Warning".

[0068] In the entry corresponding to the nth individual, vital sign 206 may be displayed as "60" (beats per minute) and rate of change 208 may be displayed as "1" (beats per square minute). In some examples, the nth individual may have a lower threshold of 50 for the biological condition indicated by vital sign 206 and a lower threshold of -4 for rate of change 208. Because the nth individual's vital sign 206 is below its threshold, but the rate of change 208 is above its threshold, the nth individual may not be deteriorating or in need of immediate assistance. Therefore, status 210 may be displayed as "Normal".

[0069] In various implementations, the visual interface 200 can display the order of the entries based on the status 210 of the individuals corresponding to the entries. For example, the monitoring system and / or clinical device 202 can prioritize the individuals based on the status, and the visual interface 200 can display the order of the entries based on the priority of the corresponding individuals. Figure 2 In the example shown, the first individual can have the highest priority because the first individual may be the only individual with an "ALERT" status. Therefore, the entry corresponding to the first individual can be displayed at the top of the list of entries in the visual interface 200. In addition, the second individual can have a higher priority than the nth individual because the second individual has a "Warning" status and the nth individual has a "Normal" status. Therefore, the entry corresponding to the second individual can be displayed above the entry corresponding to the nth individual.

[0070] Figure 3A and Figure 3B An example of a vital sign measurement obtained semi-continuously over a period of time is provided. For example, the vital sign measurement may be expressed as heart rate in beats per minute. Figure 3A An example of relatively stable vital sign measurements obtained semi-continuously over a period of approximately 42 hours is shown. Figure 3B An example of relatively unstable vital sign measurements obtained semi-continuously over a period of approximately 42 hours is shown.

[0071] In various implementations, a monitoring system (e.g., monitoring system 108) may receive and / or track measurements of vital signs during the time period. For example, a monitoring system may receive measurements from a sensor device (e.g., sensor device 104) that measures vital signs of an individual (e.g., individual 102). The sampling period of the sensor device may be significantly shorter than the time period over which the measurements are taken. For example, during Figure 3A and Figure 3B In the example shown, measurements are taken within a sampling period of 0.1 hours. The term "sampling period" may refer to the time period between measurements.

[0072] Measurements may change over time for a variety of reasons. For example, a sensor device may be associated with a sensor noise level. Sensor noise may be attributed to physical limitations of the sensor within the sensor device, limitations of signal processing performed at the sensor device or monitoring system, electronic noise introduced as a signal representing the measurement through the sensor device, the monitoring system, or the communication interface between the sensor device and the monitoring system, etc. In some cases, measurements may change over time due to patient deterioration and / or medical instability. Random changes in vital sign measurements (e.g., due to noise) may have an insignificant effect on the average of the measurements. However, changes due to trends in vital sign measurements (e.g., due to medical instability) may significantly affect the average of the measurements.

[0073] The monitoring system may determine whether a baseline should be calculated based on the measurements. In some cases, the monitoring system may determine the baseline after determining that the measurements are stable. For example, the monitoring system may identify the variance of the measurements. If the variance of the measurements is less than a certain threshold (e.g., a certain percentage of the mean of the measurements), the monitoring system may determine that the measurements are stable and may establish a baseline based on the measurements.

[0074] In some implementations, the monitoring system may identify any measurement with a variance less than 10% of its mean as stable, and may determine a baseline based on these stable measurements. Figure 3A In the example shown, the mean of the measurements is 52.5 and the variance based on the population is 2.1. Therefore, the monitoring system can be based on Figure 3A The baseline is identified by the measured values ​​shown. In some cases, the baseline can be the mean itself (i.e., 52.5). Figure 3B In the example shown, the mean of the measured values ​​is 46.4 and the variance is 15.3. Therefore, the monitoring system can be based on Figure 3B The measurements shown are used to identify the baseline.

[0075] In some cases, although Figure 3A The variance of the measurements depicted in the figure is very low, but the monitoring system may not calculate a baseline from these measurements. For example, additional sensor data (not shown in the figure) may indicate that the individual moved during the time period in which the measurement was taken. In some cases, the additional sensor data may indicate that the individual is in a position (e.g., a standing position) other than a predetermined position (e.g., a supine position), so that the measurement is not applicable to the position in which the individual is expected to be monitored (e.g., a supine position). In some examples, the monitoring system may determine (e.g., based on medical records associated with the individual) that the individual has taken medication that affects the vital signs being measured. In some cases, if any of these characteristics are determined to be applicable to the individual being measured, the monitoring system may not calculate a baseline based on the measurement results.

[0076] Figure 4A and Figure 4B Individual vital sign measurements and rates of change are illustrated. For example, a vital sign measurement may be a heart rate measurement in beats per minute. The rate of change may be defined in hours. For example, if the vital sign measurement is a heart rate measurement, the rate of change may be determined as the number of heart beats per minute per hour (beats / (minutes*hours)). In various implementations, a monitoring system may use the vital sign measurements and the rate of change to determine whether to trigger an alarm indicating that the individual may need assistance. Figure 4A Vital sign measurements of an individual over a period of approximately 42 hours are shown. Figure 4B Shown in Figure 4A The rate of change of the vital sign measurements shown in Figure 4A Same 42 hour sliding average shown in .

[0077] like Figure 4A As shown, the vital sign measurements may be centered around a baseline 402 and vary within a range defined by an upper threshold 404 and a lower threshold 406 for the first approximately 23 hours depicted. However, the vital sign measurements may trend downward between hours 23 and 33, and may then trend upward from hours 33 to approximately hours 42. During the downward trend, the vital sign measurements may drop below the lower threshold 406. During the upward trend, the vital sign measurements may rise above the upper threshold 404.

[0078] like Figure 4B As shown, the hourly rate of change may generally remain between the upper threshold 410 and the lower threshold 412. However, at some point in time, the hourly rate of change may rise above the upper threshold 410 and fall below the lower threshold 412.

[0079] In various implementations, the monitoring system may determine whether to trigger an alarm based on the vital sign measurement and / or hourly rate of change. In some cases, the monitoring system may trigger an alarm whenever the vital sign measurement and / or hourly rate of change are outside of their respective ranges. In some cases, the monitoring system may trigger an alarm whenever the vital sign measurement drops below its lower threshold and the corresponding rate of change drops below its lower threshold, or whenever the vital sign measurement rises above its upper threshold and the corresponding rate of change rises above its upper threshold. According to some implementations, an alarm may be triggered if the vital sign measurement is low and trending downward, or high and trending upward.

[0080] refer to Figure 4A and Figure 4B, in some cases, the vital sign measurement may drop below the lower threshold 406 around the 24 hour mark, but the corresponding rate of change at the 24 hour mark is not below the lower threshold 412. Therefore, in some cases, the monitoring system does not trigger an alarm at the 24 hour mark. However, around the 26 hour mark, the vital sign measurement drops below the lower threshold 405, and the corresponding rate of change drops below the lower threshold 412. Therefore, in some examples, the monitoring system may trigger an alarm at the 26 hour mark.

[0081] In various examples, the monitoring system may recognize that a confounding factor has occurred at the 26-hour mark, such as the individual may be moving, changing location, or taking a medication with significant bioavailability at the 26-hour mark. The low vital sign measurements at the 26-hour mark and their downward trend may be attributed to this. Therefore, in some of these examples, the monitoring system will not trigger an alarm at the 26-hour mark.

[0082] Figure 5 and Figure 6 Example processes according to embodiments of the present disclosure are described. The processes are illustrated in a logic flow diagram, each operation of which represents a sequence of operations that can be implemented in hardware, software, or a combination thereof. In the context of software, the operations represent computer-executable instructions stored on one or more computer-readable storage media, which, when executed by one or more processors, perform the operations. In general, computer-executable instructions include routines, programs, objects, components, data structures, etc. that perform specific functions or implement specific abstract data types. The order in which the operations are described is not intended to be construed as a limitation, and any number of the operations described may be combined in any order and / or in parallel to implement the processes.

[0083] Figure 5 An example process 500 for identifying a personalized range of biological condition measurements that can be used to monitor an individual is shown. According to various implementations, process 500 can be performed by a monitoring system, such as described above with reference to Figure 1 Monitoring system 108 is described. In some examples, at least some steps of process 500 can be performed by at least one processor in the monitoring system.

[0084] At 502, the processor may identify biological condition measurements of an individual measured over a period of time. In various cases, the biological condition may be a vital sign. For example, the biological condition may be at least one of a heart rate, blood pressure, blood oxygen saturation percentage, respiratory rate, core body temperature, or peripheral temperature of the individual.

[0085] In some cases, the processor can receive the measurement from a sensor device that generates the measurement. For example, the processor can be part of a system having at least one transceiver configured to receive a signal indicating the measurement from the sensor device, and the processor can identify the measurement based on the signal. In some cases, the measurement is identified substantially in real time. For example, the sensor device can send a signal in response to generating a corresponding measurement.

[0086] According to various implementations, the processor may identify multiple measurements of the biological condition taken during the time period. For example, the processor may identify 5-100 measurements of the biological condition taken during the time period. The sampling period (e.g., the period between two measurements) may be significantly shorter than the length of the time period in which the measurements are taken. For example, the length of the sampling period may be 5 to 100 times the length of the time period in which the measurements are taken. In some cases, the time period in which the measurements are taken may be between 0.5 and 24 hours. For example, the time period may be between 1 and 6 hours.

[0087] At 504, the processor may determine that the individual is stable during the time period. In various implementations, the processor may determine that the measurement is stable during the time period. In some cases, the processor may receive (e.g., via a transceiver) a signal indicating that the individual is stable from an independent system such as an EMR system (e.g., EMR system 110).

[0088] In various examples, the processor may calculate the variance or standard deviation of the measurements. The variance (or standard deviation) may be weighted or unweighted. In some cases, the processor may compare the variance or standard deviation to a specific threshold. For example, if the variance is about the heart rate measurement, the threshold may be 10 beats per minute. If the variance or standard deviation is below a specific threshold, the processor may determine that the individual is stable.

[0089] In some implementations, the processor may further calculate an average value (e.g., an arithmetic mean) of the measurements and use the average value to determine whether the individual is stable. In various examples, the processor may compare the variance or standard deviation to a specific percentage of the average value. For example, the specific percentage may be 10% of the average value. If the variance or standard deviation is lower than a specific percentage of the average value, the processor may determine that the individual is stable.

[0090] Although not applicable to Figure 5504. The exemplary process 500 shown in FIG. 504 is shown, but in some implementations, the processor can identify individual instability based on signals and / or measurements from an external system. In response to identifying individual instability, the processor can monitor additional measurements of the biological condition until the measurements stabilize. In some examples, the processor can generate a new set of measurements by omitting earlier measurements (e.g., the first one or more measurements in a time period in which the measurements were taken), and repeat 504 based on the new set of measurements.

[0091] At 506, the processor may identify a baseline based on the measured values. According to various implementations (e.g., when the measured values ​​have a symmetrical distribution), the baseline may be an average value (e.g., an arithmetic mean) of the measured values. In some cases where the measured values ​​have an asymmetrical distribution, the baseline may be a median of the measured values. For example, the measured values ​​of the oxygen saturation percentage may have an asymmetrical distribution, and the baseline oxygen saturation percentage may be the median of the measured values.

[0092] At 508, the processor may identify a range of biological conditions based on the baseline. The range may be defined by a lower threshold and an upper threshold. The processor may define at least one of the lower threshold or the upper threshold based on the baseline. In some cases, the processor may identify the lower threshold or the upper threshold independently of the baseline. In various cases, the processor may be configured to define the lower threshold or the upper threshold for a particular biological condition at a particular level. For example, the processor may define the lower threshold of the range of heart rate measurements as 40 beats per minute, regardless of the individual's baseline.

[0093] In some cases, the processor may calculate a threshold value (e.g., a lower threshold value or an upper threshold value) by adding an offset value to the baseline. The offset value may be a positive or negative value. In some cases, the processor applies the same offset value to each range of the same biological condition. For example, the processor may apply an offset value of 10 beats per minute to any range corresponding to heart rate. In some cases, the processor calculates the offset value based on the baseline itself. For example, the processor may calculate a fixed percentage (e.g., 10%) of the baseline as the offset value. In various implementations, the processor uses two different offset values ​​to calculate the two thresholds.

[0094] In some exemplary implementations, the processor may calculate a potential threshold based on a baseline, but may not use the potential threshold if the potential threshold is too extreme. For example, the processor may calculate a potential lower threshold based on a baseline, compare the potential lower threshold to an absolute lower threshold, and use the potential lower threshold only if the potential lower threshold is greater than the absolute lower threshold. In some examples, the processor may calculate a potential upper threshold threshold based on a baseline, compare the potential upper threshold to an absolute upper threshold, and use the potential upper threshold only if the potential upper threshold is less than the absolute upper threshold threshold. An absolute threshold may represent a threshold biological condition measurement that should trigger an alarm for each individual, regardless of the baseline. For example, an absolute lower threshold for a heart rate measurement may be the minimum heart rate required to adequately oxygenate a human body, applicable to all persons, regardless of resting heart rate.

[0095] In some implementations, the processor can compare additional measurements of the biological condition to the range to determine whether the individual's health is likely to deteriorate and / or whether the individual requires urgent assistance from a caregiver.

[0096] Figure 6 An example process 600 for triggering an alarm based on a measurement of a biological condition is shown. According to various implementations, process 600 may be performed by a monitoring system, such as described above with reference to Figure 1 Monitoring system 108 is described. In some examples, at least some steps of process 600 can be performed by at least one processor in the monitoring system.

[0097] At 602, the processor may identify a measurement of a biological condition of an individual measured over a period of time. In various cases, the biological condition may be a vital sign. For example, the biological condition may be at least one of a heart rate, blood pressure, blood oxygen saturation percentage, respiratory rate, core body temperature, or peripheral temperature of the individual.

[0098] In some cases, the processor can receive the measurement from a sensor device that generates the measurement. For example, the processor can be part of a system having at least one transceiver configured to receive a signal indicating the measurement from the sensor device, and the processor can identify the measurement based on the signal. In some cases, the measurement is identified substantially in real time. For example, the sensor device can send a signal in response to generating a corresponding measurement.

[0099] According to various implementations, the processor may identify multiple measurements of the biological condition within the time period. For example, the processor may identify 5-100 measurements of the biological condition measured within the time period. The sampling period (e.g., the period between two measurements) may be significantly shorter than the length of the time period in which the measurements are taken. For example, the length of the sampling period may be 5 to 100 times the length of the time period in which the measurements are taken. In some cases, the time period in which the measurements are taken may be between 0.01 and 24 hours. For example, the time period may be between 0.1 and 1 hour.

[0100] At 604, the processor may determine that one or more of the measured values ​​are outside of a first range associated with the individual. The first range may have been previously defined (e.g., by the processor) based on a baseline of previous measurements of the biological condition of the individual. For example, the processor may have previously determined that one or more of the measured values ​​are outside of a first range associated with the individual. Figure 5 Process 500 is described to identify a range.

[0101] In some cases, the processor determines that at least one threshold number of measurements is outside the first range. The measurements outside the first range can be below the first range, above the first range, or a combination of the two. In an exemplary case, the processor can determine that 2 to 10 consecutive measurements are outside the first range. In some examples, the processor determines that the time period can be longer than a threshold time period (e.g., the threshold can be about 0.1 to about 1 hour), and all measurements taken during the time period are outside the first range. In various examples, 604 includes a processor that determines that one or more averages (e.g., arithmetic means) of the measurements are outside the first range.

[0102] At 606, the processor may determine that the rate of change of the measured value may be outside the second range. The rate of change outside the second range may be lower than the first range or higher than the first range. The processor may calculate the rate of change based on one or more measured values. In some cases, the processor may calculate the average rate of change of at least a subset of the measured values. For example, the processor may calculate the rate of change between each adjacent measured value pair and the average rate of change. In some cases, the processor may calculate the rate of change based on a single pair of measured values. For example, the processor may calculate the rate of change based on the first pair of measured values ​​outside the first range, the last pair of measured values, etc.

[0103] In some cases, the processor may calculate the second range based on the confidence interval of the change rate previously calculated for the individual. For example, the processor may calculate multiple change rates (e.g., sliding average change rates, average values ​​within an hour or some other time interval) based on previous measurements of the biological condition, and calculate the confidence interval based on the change rate. The confidence level associated with the confidence interval may be 90%, 95%, 99%, etc. The processor may then define the second range based on the confidence interval. In some cases, the processor may calculate the second range based on a predetermined level. For example, the second range may be defined as a change in the average value of the measured value within a specific time interval (e.g., 1 hour) within a range of ±5%, ±10%, ±15%, or the like. In some examples, the processor may predetermine the second range based on the biological condition. For example, for heart rate measurements, the processor may always define the second range as ±10 beats / minute per 0.1 hour.

[0104] At 608, the processor may determine whether there are any confounding factors. Confounding factors may affect the individual's biological condition measurements, sometimes in a predictable manner. Some examples of confounding factors include, for example, recent medical treatment, surgical treatment, medication, movement of the individual, change of location of the individual, and the like. In some cases, the processor may access an EMR system (e.g., EMR system 110) to identify whether confounding factors exist within the time period, or within a previously predetermined time period prior to the time period in which the measurement was taken. For example, the biological condition may be heart rate, and the processor may access the EMR system to determine whether the individual was administered albuterol within a time period prior to the time period in which the heart rate measurement was taken.

[0105] Despite Figure 6 Although not specifically described in the description, in some implementations, the processor may adjust the first range and / or the second range in response to identifying the presence of a confounding factor. In some cases, the processor may identify a relationship between the biological condition and the identified factor and adjust the first range accordingly. For example, the biological condition may be heart rate, the processor may identify that the individual has been administered albuterol, and may increase the upper and lower thresholds of the first range in response to identifying that the individual has been administered albuterol.

[0106] At 610, the processor may trigger an alarm. In various implementations, the processor may generate a message indicating the identity of the individual and / or the status of the individual, which may be sent to an electronic device via one or more transceivers. The electronic device may be associated with a caregiver who can provide assistance to the individual. In some cases, the message may cause the electronic device to output an alarm associated with the individual so that the caregiver may be informed that the individual needs immediate assistance.

[0107] Figure 7An example system is shown that includes at least one device 700. In some implementations, Figure 7 The system shown can perform any of the functions described herein. Device 700 can be implemented by at least one of a server computer, dedicated hardware, software running on dedicated hardware, or a virtualized function hosted on an appropriate platform (e.g., a cloud infrastructure). The device can be implemented as a single device or multiple devices, with components and data distributed among the multiple devices.

[0108] As shown, the device 700 includes a memory 702. In various implementations, the memory 702 can be volatile (e.g., random access memory (RAM)), non-volatile (e.g., read-only memory (ROM), flash memory, etc.), or some combination of the two. The various elements stored in the memory 702 can include methods, threads, processes, applications, objects, modules, or any other kind of executable instructions. The elements stored in the memory 702 can be non-temporary. The memory 702 can also store various files, databases, etc.

[0109] The memory 702 may include various instructions 704 that may be used for any of the functions described herein. The memory 702 also includes a baseline determiner 706, a range determiner 708, and an alarm trigger 710. The baseline determiner 706 may include instructions for determining a personalized baseline based on measurements of various biological conditions (e.g., vital signs) of an individual. The range determiner 708 may include instructions for determining a personalized range of the biological condition based on the personalized baseline. The alarm trigger 710 may include instructions for monitoring the measurements of the biological condition and triggering an alarm when the measurements are outside the personalized range.

[0110] Instructions 704, baseline determiner 706, range determiner 708, and / or alarm trigger 710 may be executed by processor 712 to perform operations. In some embodiments, processor 712 includes a central processing unit (CPU), a graphics processing unit (GPU), or both a CPU and a GPU, or other processing units or components known in the art.

[0111] like Figure 7 As shown, the device 700 may also include one or more wired or wireless transceivers 714. For example, the transceiver 714 may include a network interface card (NIC), a network adapter, a local area network (LAN) adapter, or a physical, virtual, or logical address connected to various external devices and / or systems. The transceiver 714 may include any type of wireless transceiver capable of participating in wireless communications (e.g., radio frequency (RF) communications). The transceiver 714 may also include other wireless modems, such as a modem for Wi-Fi, WiMAX, Bluetooth, or infrared communications.

[0112] The device 700 may also include additional data storage components, such as magnetic disks, optical disks, or tapes. These additional data storage components may include removable memory 716 and non-removable memory 718. Tangible computer-readable media may 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.

[0113] Memory 702, removable storage 716, and non-removable storage 718 are all examples of computer-readable storage media. Computer-readable storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other storage technology, CD-ROM, digital versatile disks (DVD), content addressable memory (CAM) or other optical storage, magnetic tape, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by the device 700. Any such tangible computer-readable media can be part of the device 700.

[0114] The device 700 may also include an input device 720 and an output device 722. In some implementations, the input device 720 may include at least one of a keypad, a cursor controller, a touch-sensitive display, a voice input device, a tactile feedback device, etc. The output device 722 may include at least one of a display, a speaker, a tactile output device, a printer, etc. These devices are well known in the art and need not be discussed in detail here.

[0115] The following clauses, alone or in combination, describe one or more exemplary embodiments of the present disclosure.

[0116] 1. A method comprising: receiving a first signal from a sensor, the first signal including information indicating a first measurement value of a vital sign of an individual measured during a first time period; determining a baseline for the vital sign based on the first measurement value; identifying a threshold for the vital sign based on the baseline; receiving a second signal from the sensor, the second signal including information indicating a second measurement value of a vital sign of the individual measured during a second time period; determining that at least one of the second measurement values ​​is outside a range defined by the threshold value; and in response to determining that at least one of the second measurement values ​​is outside the range, sending a third signal indicating an alarm to at least one clinical device.

[0117] 2. A method according to clause 1, wherein determining a baseline of a vital sign comprises: identifying a variance of the first measurement value; determining that the variance is less than a predetermined percentage of an arithmetic mean of the first measurement value, wherein the threshold is identified in response to determining that the variance is less than the predetermined percentage.

[0118] 3. A method according to Article 1 or Article 2, wherein the sensor is a first sensor, the threshold is a first threshold, and the method further includes: receiving a fourth signal from a second sensor, the fourth signal including information indicating a third measurement value of individual movement within a first time period; and determining that the third measurement value is lower than the second threshold, wherein the first threshold is identified in response to determining that the third measurement value is lower than the second threshold.

[0119] 4. A method according to any one of items 1 to 3, wherein the sensor is a first sensor, the threshold is a first threshold, and the method further includes: receiving a fourth signal from the second sensor, the fourth signal including information of a third measurement value indicating the position of the individual during a first time period; and determining that the individual has maintained a supine position during the first time period based on the third measurement value, wherein the first threshold is identified in response to determining that the individual has maintained a supine position.

[0120] 5. The method of any one of clauses 1 to 4, further comprising: determining that a drug administered to the individual is inactive during the first time period, wherein the threshold is identified in response to determining that the drug is inactive during the first time period.

[0121] 6. A method according to any one of Articles 1 to 5, wherein the threshold is a first threshold, the range is a first range, and the method further comprises: determining that the rate of change of the second measurement value is outside a second range defined by the second threshold, wherein triggering an alarm is also in response to determining that the rate of change of the second measurement value is outside the second range.

[0122] 7. A method according to clause 6, wherein: at least one of the second measurement values ​​is determined to be lower than the first range, and the rate of change is determined to be lower than the second range, or at least one of the second measurement values ​​is determined to be higher than the first range, and the rate of change is determined to be higher than the second range.

[0123] 8. A method according to any one of clauses 1 to 7, wherein the vital signs include at least one of the individual's heart rate, the individual's blood pressure, the individual's blood oxygen saturation percentage, the individual's respiratory rate, the individual's core body temperature, or the individual's peripheral temperature.

[0124] 9. A system comprising: at least one processor; and a memory storing instructions, which, when executed by the at least one processor, cause the at least one processor to perform the following operations, including: receiving a first signal from a sensor, the first signal being used to indicate a first measurement value of a vital sign of an individual within a first time period; determining a baseline of the vital sign based on the first measurement value; determining a threshold of the vital sign based on the baseline; receiving a second signal from the sensor, the second signal being used to indicate a second measurement value of the vital sign of the individual within a second time period; determining that at least one of the second measurement values ​​is outside a range defined by the threshold value; and triggering an alarm in response to determining that at least one of the second measurement values ​​is outside the range.

[0125] 10. A system according to Article 9, wherein the sensor is a first sensor, the threshold is a first threshold, and the operation further includes: receiving a third signal from a second sensor, the third signal being used to indicate a third measurement value of the individual's movement within a second time period; and determining that the third measurement value is lower than a second threshold, wherein at least one of the second measurement values ​​is outside the range defined by the threshold in response to determining that the third measurement value is lower than the second threshold.

[0126] 11. A system according to Article 9 or Article 10, wherein the sensor is a first sensor, the threshold is a first threshold, and the operation further includes: receiving a third signal from a second sensor, the third signal being used to indicate a third measurement value of the individual's position during a second time period; and determining that the individual maintained a supine position during the second time period based on the third measurement value, wherein at least one of the second measurement values ​​is outside the range defined by the threshold in response to determining that the individual maintained a supine position during the second time period.

[0127] 12. A system according to any one of clauses 9 to 11, wherein the operation further includes: determining that a drug administered to the individual is inactive during a second time period, wherein at least one of the second measurement values ​​is outside a range defined by a threshold value in response to determining that the drug is inactive during the second time period.

[0128] 13. A system according to any one of Articles 9 to 12, wherein the threshold is a first threshold, the range is a first range, and the operation further includes: determining that the rate of change of the second measurement value is outside a second range defined by the second threshold, wherein triggering the alarm is also in response to determining that the rate of change of the second measurement value is outside the second range.

[0129] 14. A system according to clause 13, wherein: at least one of the second measurement values ​​is determined to be below the first range and the rate of change is determined to be below the second range, or at least one of the second measurement values ​​is determined to be above the first range and the rate of change is determined to be above the second range.

[0130] 15. A system according to any one of Articles 9 to 14, wherein the threshold is a first threshold, and determining that at least one of the second measurement values ​​is outside the range defined by the threshold comprises: determining that the second measurement value exceeding the second threshold number is outside the range defined by the first threshold.

[0131] 16. A system comprising: a vital sign sensor configured to measure a vital sign of an individual; a movement sensor configured to measure movement of an individual; an electronic device configured to output an alarm; at least one processor; and a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations including: receiving a first signal from the vital sign sensor, the first signal being used to indicate a first measurement value of a vital sign measured within a first time period; receiving a second signal from the movement sensor, the second signal being used to indicate a second measurement value of movement of the individual measured within the first time period; determining that the second measurement value is below a first threshold; and determining, based on the first measurement value, by calculating an arithmetic value of the first measurement value. an average value to determine a baseline for a vital sign; identifying a second threshold for a vital sign based on the baseline, the second threshold being a predetermined percentage of the baseline; receiving a third signal from the vital sign sensor, the third signal being used to indicate a third measurement of the vital sign measured during a second time period; receiving a fourth signal from the movement sensor, the fourth signal being used to indicate a fourth measurement of movement measured during the second time period; determining that the fourth measurement is below the first threshold; determining that at least one of the third measurements is outside a range defined by the second threshold; and in response to determining that at least one of the third measurements is outside the range, sending a fifth signal to the electronic device, the fifth signal being used to indicate an instruction to output an alarm for identifying an individual.

[0132] 17. A system according to clause 16, wherein the range is a first range, and the operation further comprises: determining an average rate of change of the third measurement value; determining that the average rate of change is outside a second range, wherein the fifth signal is sent in response to determining that the average rate of change is outside the second range.

[0133] 18. A system according to Article 17, wherein determining that the rate of change is outside the second range includes: determining that the average rate of change is greater than the second range, and wherein determining that at least one of the third measurement values ​​is outside the first range includes: determining that at least one of the third measurement values ​​is greater than the second threshold.

[0134] 19. A system according to Article 17, wherein determining that the rate of change is outside the second range includes: determining that the average rate of change is less than the second range, and wherein determining that at least one of the third measurement values ​​is outside the first range includes: determining that at least one of the third measurement values ​​is less than the second threshold.

[0135] 20. The system of any one of clauses 16 to 19, wherein the electronic device outputs an alarm as at least one of a visual alarm, an audible alarm, or a tactile alarm in response to receiving the fifth signal.

[0136] In some cases, one or more components may be referred to herein as "configured to," "configurable to," "operable / operable," "adaptable / adaptable," "capable of," "compliant / compliant with," etc. Those skilled in the art will recognize that these terms (e.g., "configurable to") may generally include active state components and / or inactive state components and / or standby state components unless the context requires otherwise.

[0137] As used herein, the term "based on" may be used synonymously with "based at least in part on" and "based at least in part on."

[0138] As used herein, the terms "comprising" and "including" and their equivalents are used interchangeably. An apparatus, system, or method "comprising A, B, and C" includes A, B, and C, but may also include other components (e.g., D). That is, the apparatus, system, or method is not limited to components A, B, and C.

[0139] Although the subject matter has been described in language specific to structural features and / or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described.

Claims

1. A method executed by a processor, comprising: receiving a first signal from a sensor, the first signal comprising information indicative of a first measurement of a vital sign of an individual measured during a first time period; identifying a variance of the first measurement; Determine whether the first measurement is stable by: determining that a variance of the first measurement is less than a variance threshold, and determining that a drug administered to the individual is inactive during the first time period by determining that the first time period occurs greater than a predetermined amount of time after administration of the drug to the individual; In response to determining that the first measurement is stable, determining a baseline for the vital sign based on the first measurement; identifying a threshold value of the vital sign based on the baseline, the threshold value of the vital sign being greater or less than an offset from the baseline; determining that the drug administered to the individual is effective during the second time period by determining that the second time period occurs within a predetermined amount of time after administration of the drug to the individual; receiving a second signal from the sensor, the second signal comprising information indicative of a second measurement of a vital sign of the individual measured during a second time period; adjusting a threshold value for a vital sign based on an indication of one or more medical characteristics, the one or more medical characteristics comprising: a medical treatment administered to the individual, a surgical treatment administered to the individual, a medication administered to the individual, a dosage of a medication administered to the individual, a biological condition of the individual, an allergy of the individual, or a genetic predisposition of the individual; determining that at least one of the second measurements is outside a range defined by a threshold value for the vital sign; and In response to determining that at least one of the second measurements is outside of the range, a third signal indicative of an alarm is sent to at least one clinical device.

2. The method according to claim 1, wherein: The sensor is a first sensor, and the method further comprises: receiving a fourth signal from the second sensor, the fourth signal including information indicating a third measurement of movement of the individual during the first time period; and The step of determining that the first measurement is stable also includes determining that the third measurement is below a movement threshold.

3. The method according to claim 1, wherein: The method further comprises: receiving a fifth signal from a third sensor, the fifth signal including information indicating a fourth measurement of the location of the individual during the first time period; and The step of determining that the first measurement is stable also includes: determining that the individual maintained a supine position during the first time period based on the fourth measurement.

4. The method according to claim 1, wherein: The range is a first range, and the method further includes: determining that the rate of change of the second measurement value is outside a second range defined by another threshold, Wherein triggering the alarm is also responsive to determining that the rate of change of the second measurement value is outside of the second range.

5. The method according to claim 4, wherein: Determining that at least one of the second measurements is outside of the first range comprises: determining that at least one of the second measurements is below a lower threshold, and Determining that the rate of change of the second measurement value is outside the second range includes: determining that the rate of change is below a second lower threshold; or Determining that at least one of the second measurements is outside of the first range comprises: determining that at least one of the second measurements is above an upper threshold, and Determining that the rate of change of the second measurement value is outside the second range includes: It is determined that the rate of change is above the upper threshold.

6. The method according to any one of claims 1 to 5, wherein: The vital sign includes at least one of the individual's heart rate, the individual's blood pressure, the individual's blood oxygen saturation percentage, the individual's respiratory rate, the individual's core temperature, or the individual's peripheral temperature.

7. A system comprising: at least one processor; as well as A memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform the following operations: The method according to any one of claims 1 to 6.

8. A system comprising: a vital sign sensor configured to measure a vital sign of an individual; a motion sensor configured to measure movement of an individual; an electronic device configured to output an alarm; at least one processor; as well as A memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations including: receiving a first signal from a sensor, the first signal comprising a first measurement indicative of a vital sign of an individual taken over a first time period; determining a variance of the first measurement; Determine whether the first measurement is stable by: determining that a variance of the first measurement is less than a variance threshold, and determining that a drug administered to the individual is inactive during the first time period by determining that the first time period occurs greater than a predetermined amount of time after administration of the drug to the individual; In response to determining that the first measurement is stable, determining a baseline for the vital sign based on the first measurement; identifying a threshold value of the vital sign based on the baseline, the threshold value of the vital sign being greater or less than an offset from the baseline; determining that the drug administered to the individual is effective during the second time period by determining that the second time period occurs within a predetermined amount of time after administration of the drug to the individual; receiving a second signal from the sensor, the second signal comprising a second measurement indicative of a vital sign of the individual taken during the second time period; adjusting a threshold value for a vital sign based on an indication of one or more medical characteristics, the one or more medical characteristics comprising: a medical treatment administered to the individual, a surgical treatment administered to the individual, a medication administered to the individual, a dosage of a medication administered to the individual, a biological condition of the individual, an allergy of the individual, or a genetic predisposition of the individual; determining that at least one of the second measurements is outside a range defined by a threshold value for the vital sign; and In response to determining that at least one of the second measurements is outside of the range, an alarm is triggered.

9. The system according to claim 8, wherein: The sensor is a first sensor, and the operations further include: receiving a fourth signal from the second sensor, the fourth signal comprising a third measurement indicating movement of the individual during the first time period; and Determining that the first measurement is stable also includes determining that the third measurement is below a movement threshold.

10. The system according to claim 8, wherein: The sensor is a first sensor, and the operations further include: receiving a fifth signal from a third sensor, the fifth signal comprising a fourth measurement indicative of a location of the individual taken during the first time period; and Determining that the first measurement is stable also includes determining that the individual maintained a supine position during the first time period based on the fourth measurement.

11. The system according to claim 8, wherein: The range is a first range, and the operation further includes: Determining that the rate of change of the second measurement value is outside a second range defined by another threshold, wherein after determining that the rate of change of the second measurement value is outside the second range, further performing an operation of triggering an alarm; or in: Determining that at least one of the second measurements is outside of the first range comprises: determining that at least one of the second measurements is below a lower threshold, and Determining that the rate of change of the second measurement value is outside the second range includes: determining that the rate of change is below a second lower threshold; or Determining that at least one of the second measurements is outside of the first range comprises: determining that at least one of the second measurements is above an upper threshold, and Determining that the rate of change of the second measurement value is outside the second range includes: It is determined that the rate of change is above the upper threshold.

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