Patent Publication Number: US-2022219000-A1

Title: Systems and methods for pacing assistance and automation

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the benefit of U.S. Provisional Application No. 63/199,563, titled “SYSTEMS AND METHODS FOR PACING ASSISTANCE AND AUTOMATION” and filed on Jan. 8, 2021, and which is incorporated by reference herein in its entirety. 
    
    
     BACKGROUND 
     Pacing is a technique by which electrical stimulation is delivered to a heart of a patient to control and/or modify a rate at which the heart beats. In some cases, pacing may be administered to a patient experiencing bradycardia, or slow heart beats, via electrodes applied to an external surface of the patient, where the electrodes are connected to an external pacing device. In some examples, the external pacing device also functions as a defibrillator. An objective of pacing is to achieve capture of the heart of the patient. Capture is achieved when the electrical stimulation delivered during pacing causes depolarization of the ventricles of the heart (electrical capture) and/or contraction of the myocardium of the heart (mechanical capture). In conventional systems, a healthcare provider may operate the pacing device to place the electrodes on the skin of the patient, administer pacing, and determine whether capture has been achieved. Administering pacing and determining whether capture has been achieved presents challenges for healthcare providers, especially in stressful situations where a patient&#39;s life may be at risk. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates an example pacing device configured to provide pacing assistance and automation according to the techniques described herein. 
         FIG. 2  illustrates an example pacing device displaying an example user interface indicating a time at which an electrical stimulation was administered across multiple biological parameters, according to the techniques described herein. 
         FIG. 3  illustrates an example pacing device displaying an example user interface including a notification to display an additional biological parameter, according to the techniques described herein. 
         FIG. 4  is an example method for providing electrical stimulation based on a likelihood of capture determined from multiple biological parameters, according to the techniques described herein. 
         FIG. 5  is an example method for providing electrical stimulation based on sensor data collected at different times, according to the techniques described herein. 
         FIG. 6  is an example method for displaying a representation of a biological parameter based on a determination that pacing is being administered, according to the techniques described herein. 
         FIG. 7  illustrates an example of an external defibrillator configured to perform various functions described herein. 
     
    
    
     DETAILED DESCRIPTION 
     Various implementations described herein relate to providing pacing assistance and automation. For example, a pacing device, such as an external defibrillator, provides electrical stimulations to an external surface of a patient based on a determination as to whether capture has been achieved. As used herein, an “electrical stimulation” is an electrical signal output by the pacing device at a current between, for example, 0 and 200 milliamperes (mA), delivered at a frequency such as 60 paces per minute (PPM). In some examples, the pacing device provides electrical stimulation at an initial current of 60 mA, and pacing capture is achieved at or near 70 mA. 
     The pacing device determines whether capture has been achieved using one or multiple types of sensor data (e.g., electrocardiogram (ECG), oxygen saturation (SpO 2 ), non-invasive blood pressure (NIBP), invasive blood pressure, end-tidal CO 2  (ETCO 2 ), regional cerebral oxygen saturation (rSO 2 ), and/or ventilation), and/or historical sensor data, for instance. These techniques effect a particular treatment (e.g., pacing using an external pacing system) for a medical condition (e.g., bradycardia). In some examples, the pacing device provides notifications to assist with pacing to a healthcare provider that is administering pacing to a patient. Examples of notifications include an indication that a representation corresponding to a biological parameter of a patient may assist with pacing, that the patient has an internal pacemaker, and so forth. These techniques improve the functioning of the pacing device by displaying an application summary of un-launched representations that would assist the healthcare provider with pacing, where conventional systems would require the healthcare provider to navigate through multiple menus to locate the un-launched representations while the patient&#39;s health rapidly deteriorates. 
       FIG. 1  illustrates an example pacing device  100  configured to provide pacing assistance and automation according to the techniques described herein. In some examples, the pacing device  100  is also an external defibrillator having functionality similar to the external defibrillator  700  described in relation to  FIG. 7 . The pacing device  100  is configured to administer pacing in the form of electrical stimulation at intervals to electrodes attached to a patient via electrode leads (not pictured), such as to treat bradycardia. The pacing device  100  is also configured to receive data associated with biological parameters, such as ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , ventilation, and so on from various biological sensors that collect the data associated with the respective biological parameters. As described in more detail below, the pacing device  100  includes various components to perform the functionality described herein. The components described herein in relation to the pacing device  100  correspond to software (digital) circuits, and/or analog circuits configured to perform the described functionality. 
     The pacing device  100  includes a sensor analysis component  102  that is configured to analyze data received from various types of sensors, such as biological sensors. For example, the sensor analysis component  102  receives data associated with biological parameters configured to sense the biological parameters, as described above. In examples, the sensor analysis component  102  analyzes the data associated with the biological parameters to detect characteristics of the biological parameters. For instance, in response to receiving ECG data, the sensor analysis component  102  detects the presence (or absence) of a T-wave, which is a shape of an ECG waveform that is indicative of repolarization of the ventricles of a heart of a patient. Alternatively or additionally, in response to receiving ECG data, the sensor analysis component  102  detects the presence (or absence) of a QRS complex, which is a representation of electrical impulse as it spreads through the ventricles of the heart and indicates ventricular depolarization. In some cases, the sensor analysis component  102  foregoes detection of specific complexes, waves, or other indicators in ECG data, and instead compares how similar the ECG data is between electrical stimulations during pacing. 
     In response to receiving SpO 2  data, the sensor analysis component  102  detects the presence (or absence) of a plethysmography signal (e.g., a waveform), which is a representation of the absorption of light by tissue, including blood, between an emitter and a sensor. The sensor analysis component  102  derives an oxygen saturation for the plethysmography signal from one or more light absorption curves. In response to receiving NIBP data, the sensor analysis component  102  detects the presence (or absence) of a non-invasive blood pressure signal (e.g., a waveform). In some cases, the NIBP data includes a signal corresponding to how full a bladder of a blood pressure cuff is (e.g., based on an amount of pressure within the blood pressure cuff). In response to receiving invasive blood pressure data, the sensor analysis component  102  detects the presence (or absence) of an invasive blood pressure signal (e.g., a waveform). In response to receiving ventilation data, the sensor analysis component  102  detects the presence (or absence) of a capnography signal (e.g., a waveform). In some instances, the sensor analysis component  102  receives sensor data from non-biological sensors as well, such as from a therapy board of the pacing device  100  that provides data indicating locations of impulses generated by the pacing device  100 , thereby providing the pacing device  100  with information about when to expect an artifact from electrical stimulations. Other examples of characteristics that the sensor analysis component  102  may detect from sensor data are also considered. 
     The pacing device  100  also includes a pacing component  104  configured to cause a discharge circuit (not pictured) of the pacing device  100  to deliver an electrical stimulation to electrodes (also referred to as “ECG electrodes”) via electrode leads (also referred to as “ECG leads”) attached to the pacing device  100 . The pacing component  104  controls a current and/or a voltage of the electrical stimulation delivered to the electrodes. In some examples, the pacing component  104  delivers pulses of electrical stimulation at regular (or irregular) intervals to the electrodes in response to a pacing setting of the pacing device  100  being activated. The pacing component  104  may control any of the voltage, the current, or the interval at which the electrical stimulations are delivered based on data received by the sensor analysis component  102 , and/or characteristics detected by the sensor analysis component  102  from the data. This may include the pacing component  104  automatically modifying (e.g., without user intervention) any of the voltage, the current, or the interval at which the electrical stimulations are delivered based on data received by the sensor analysis component  102 , and/or characteristics detected by the sensor analysis component  102  from the data. 
     In some examples, the sensor analysis component  102  includes a capture component  106  configured to determine, based on the sensor data, a likelihood that capture has been achieved during pacing. As used herein, “capture” may refer to electrical capture and/or mechanical capture. The capture component  106  may determine the likelihood that capture has been achieved based on data associated with one biological parameter received by the sensor component  102  from a biological sensor, or multiple biological parameters received by the sensor component  102  from different ones of the biological sensors. By using multiple different biological parameters to determine a likelihood that capture has been achieved, the capture component  106  improves accuracy of a capture determination over systems that may rely on a single biological parameter. However, examples are also considered in which the capture component  106  utilizes a single biological parameter (e.g., ECG) to determine a likelihood that capture has been achieved, such as if a second biological sensor is malfunctioning or unavailable. 
     Alternatively or additionally, the capture component  106  may determine the likelihood that capture has been achieved based on historical data associated with one or multiple biological parameters. In conventional systems, a healthcare provider who is administering pacing is provided with a limited duration (e.g., 10 seconds, 30 seconds, etc.) of sensor data on a monitor associated with a pacing device which is updated continuously as time progresses, and/or may generate a printout of historical sensor data. The healthcare provider in such conventional systems must then interpret the sensor data as it passes along on the display and/or interpret the separate printout, if used, along with continuing to administer pacing to the patient. In some cases, when pacing is being administered, it can be helpful to determine the likelihood that capture has been achieved by analyzing biological parameters prior to a time at which pacing administration began. However, these conventional systems cause difficulty and frustration for healthcare providers during pacing administration, by either not displaying a long enough duration of the biological parameter to view prior to and/or during administration of pacing, or by manually searching through a printout of the historical sensor data to locate a relevant time span. Accordingly, the capture component  106  compares historical sensor data (e.g., prior to pacing administration, at a previously administered current level, etc.) to recent sensor data (e.g., within the last 30 seconds, a time period during which a present current level has been administered, etc.) to determine a likelihood that capture has been achieved. 
     In some cases, the capture component  106  may employ a rules-based system to determine the likelihood that capture has been achieved. Such a rules-based system includes thresholds associated with different biological parameters (e.g., in a database or look-up table). The capture component  106  receives data associated with biological parameters before, during, and/or after pacing is administered to a patient, and compares values included in the data to the thresholds to determine a likelihood that capture has been achieved. 
     In an illustrative example, the sensor analysis component  102  may receive data associated with an ECG and sensor data associated with SpO 2 . The sensor component  102  provides the data (and/or characteristics determined from the sensor data, such as signals that may include waveforms) to the capture component  106 . The capture component  106  compares values in the ECG data, such as changes in values of the ECG data between electrical stimulations. Alternatively or additionally, the capture component  106  determines a presence (or absence) of a T-wave (or a QRS-like fluctuation) in a fixed time period (e.g., 300 milliseconds), and/or compares an amplitude of a T-wave to a threshold amplitude of a T-wave associated with successful capture (e.g., 4 mm, 5 mm, etc.). 
     Additionally, the capture component  106  compares values in the SpO 2  data or plethismograph, such as changes in the plethismographic waveform data between electrical stimulations, while accounting for delay for an electrical stimulation to induce cardiac electrical activity that will lead to a mechanical pulse generated by the heart, and for the mechanical pulse to travel to a sensor location of the SpO 2  sensor (e.g., at a fingertip). In the illustrative example, the capture component  106  determines that capture has been achieved if the changes in values of the ECG data between electrical stimulations received from the sensor analysis component  102  is greater than a threshold difference (e.g., greater than 10% difference), and if the changes in values of the SpO 2  data between electrical stimulations is greater than a threshold difference (e.g., greater than 10% difference). If the changes in values of the ECG data between electrical stimulations received from the sensor analysis component  102  is less than the threshold difference, and the changes in values of the SpO 2  data between electrical stimulations is less than the threshold difference, the capture component  106  determines that capture has not been achieved. 
     Alternatively or in addition to the rules-based system just described, the capture component  106  may employ machine-learned model(s)  108  to determine the likelihood that capture has been achieved. The machine-learned models  108  also utilize thresholds associated with different biological and/or device generated parameters, but in some cases the parameters of the machine-learned models  108  are modified to improve accuracy of capture likelihood determinations. For instance, the capture component  106  receives data associated with biological parameters and inputs at least a portion of this data into the machine-learned models  108 . 
     In some examples, the machine-learned models  108  comprise one or more supervised models (e.g., classification, regression, similarity, or other type of model), unsupervised models (e.g., clustering, neural network, or other type of model), and/or semi-supervised models configured to determine a likelihood that capture has been achieved. For instance, the machine-learned model  108  may be a logistic regression model that outputs a likelihood that capture has been achieved based on the sensor data associated with the biological parameter(s). An example likelihood may include a value between 0 and 1, where the value corresponds to the likelihood that capture has been achieved and, when combined with a value representing the likelihood that capture has not been achieved, is equal to 1. In some cases, the sensor analysis component  102  converts the value between 0 and 1 representing the likelihood that capture has been achieved to a percentage value (e.g., 70% likelihood that capture has been achieved). 
     As discussed above, the sensor analysis component  102  may also leverage historical data of the patient to determine a likelihood of capture. For instance, the sensor analysis component  102  may receive data associated with biological parameter(s) of the patient prior to administration of pacing, at a previous electrical current level of electrical stimulation, and so forth. The pacing component  104  may also, in some examples, provide historical data including voltage, current, timing, and/or interval information to the sensor analysis component  102  regarding electrical stimulations that have been administered to the patient. The sensor analysis component  102  inputs the historical data into the machine-learned model  108  to provide information to the machine-learned model for determining whether capture has been achieved. The sensor analysis component  102  may continue to input data associated with one or multiple biological parameters over time, such that the machine-learned model  108  can provide a likelihood as to whether capture has been achieved. Additionally, the sensor analysis component  102  also inputs electrical stimulation data into the machine-learned model  108  over time, such that the machine-learned model  108  can refine the likelihood that capture has been achieved. In some examples, if the pacing device  100  did not administer pacing (e.g., in the form of electrical stimulation to electrodes attached to a patient via electrode leads), yet the sensor analysis component  102  detects the presence of a QRS complex, the sensor analysis component  102  may receive (or select) historical data associated with the heartbeat (e.g., intrinsic heartbeats) of the patient, and the sensor analysis component  102  may determine the likelihood of capture based on such historical data. 
     In examples, the pacing component  104  controls an electrical current level of an electrical stimulation administered to a patient via the electrodes based on a likelihood that capture has been achieved. The pacing component  104  compares the likelihood that capture has been achieved to at least one threshold likelihood of capture to determine whether an electrical current level of the electrical stimulation being delivered to the patient should change or remain the same for the upcoming electrical stimulation pulse. In an illustrative example, the pacing component  104  may utilize a single threshold (e.g., 70%, 80%, 90%, etc.) likelihood that capture has been achieved. In this example, the pacing component  104  compares a likelihood of capture of a particular patient received from the sensor analysis component  102  to the single threshold, and if the likelihood of capture is greater than or equal to the threshold, the pacing component  104  keeps the electrical current level the same for an upcoming electrical stimulation. However, if the likelihood of capture is less than the threshold, the pacing component  104  increases the electrical current level for an upcoming electrical stimulation (e.g., by 10 milliamps). In this way, the pacing device  100  controls the electrical current level of electrical stimulation administered to the patient based on a likelihood that capture has been achieved. 
     In another illustrative example, the pacing component  104  may utilize multiple threshold likelihoods that capture has been achieved. For instance, the pacing component  104  may employ a first threshold associated with capture being achieved, a second threshold associated with capture improving, and a third threshold associated with capture failure. In this example, the pacing component  104  compares a likelihood of capture of a particular patient received from the sensor analysis component  102  to the different thresholds. If the likelihood of capture is greater than or equal to the first threshold, the pacing component  104  keeps the electrical current level the same for an upcoming electrical stimulation. If the likelihood of capture is less than the first threshold and greater than or equal to the second threshold, the pacing component  104  increases the electrical current level for an upcoming electrical stimulation by a first amount (e.g., 10 milliamps). If the likelihood of capture is less than the second threshold, the pacing component  104  increases the electrical current level for an upcoming electrical stimulation by a second amount that is greater than the first amount (e.g., 15 milliamps). In this way, the pacing device  100  controls the electrical current level of electrical stimulation administered to the patient based on a likelihood that capture has been achieved, and how far the patient is from capture. 
     Although the examples above generally relate to modifying a current level of electrical stimulation based on a likelihood of capture, examples are also considered in which the pacing component  104  modifies a timing of electrical stimulations delivered to the patient as well. For instance, the pacing component  104  compares a likelihood of capture of a particular patient received from the sensor analysis component  102  to a threshold, as described above. If the likelihood of capture is greater than or equal to the threshold, the pacing component  104  keeps an interval between electrical stimulations the same for an upcoming electrical stimulation. However, if the likelihood of capture is less than the threshold, the pacing component  104  modifies the interval between electrical stimulations for an upcoming electrical stimulation (e.g., by decreasing a time between electrical stimulations by 50 milliseconds, by 500 milliseconds, etc.). 
     The sensor analysis component  102  continues to receive data from biological sensors associated with one or multiple biological parameters following administration of a particular electrical stimulation during pacing. In some cases, the sensor analysis component  102  determines a difference between a value associated with a biological parameter (e.g., an ECG wave amplitude) prior to and after the electrical stimulation was administered. After administration of an electrical stimulation during pacing, the capture component  106  again evaluates a likelihood that capture has been achieved using the previously administered electrical current level, using the techniques described herein. In examples, the capture component  106  uses the difference between values associated with the biological parameter prior to and after the electrical stimulation to determine the likelihood of capture. For instance, the capture component  106  inputs the difference into the machine-learned model  108  to use in determining the likelihood that the electrical stimulation caused capture. The pacing component  104  administers another electrical stimulation based on the likelihood that capture has been achieved by the previous electrical stimulation, which may include maintaining the same electrical current level, increasing the electrical current level, or decreasing electrical current level. 
     In addition to using data prior to and after a particular pacing pulse, the sensor analysis component  102  may analyze whether pacing is improving a condition of the patient over a longer time period. In some examples, the sensor analysis component  102  determines a difference between sensor data (e.g., an ECG signal) generated by the various sensors that detect biological conditions as described above after an electrical stimulation was administered and historical sensor data collected prior to administration of electrical stimulation during pacing. If the difference between the sensor data after the electrical stimulation was administered and historical sensor data collected prior to administration of electrical stimulation during pacing is greater than or equal to a threshold difference (e.g., 50%, 20%, 10% difference, etc.), the capture component  106  determines that the electrical stimulation has likely caused capture. Similar to the discussion above, the capture component  106  may input the difference into the machine-learned model  108 , and receive the likelihood from the machine-learned model based on the difference. The pacing component  104  then causes the same electrical stimulation to be administered to the patient, as the electrical stimulation is likely causing capture and improving the heartbeat of the patient. If the difference between the sensor data after the electrical stimulation was administered and historical sensor data collected prior to administration of electrical stimulation during pacing is less than the threshold difference, the capture component  106  determines that the electrical stimulation has likely failed to cause capture. The pacing component  104  then causes the electrical stimulation being administered to the patient to increase, as the electrical stimulation is likely insufficient to improve the magnitude of the patient&#39;s heartbeat. 
     In some cases, data associated with different biological parameters is collected at different sampling rates, and different biological parameters have periodic cycles that have different time periods. For instance, a patient may have a heart rate of 70 beats per minute where a heartrate sensor samples the heart rate 120 times per minute, and a ventilation rate of 15 breaths per minute where a ventilation sensor samples the ventilation rate 20 times per minute. When using data associated with multiple different biological parameters, the sensor analysis component  102  determines the likelihood that capture has been achieved using data received at such different time periods. In an illustrative example, the sensor analysis component  102  may receive data associated with a first T-wave of an ECG at a first time, and data associated with a second T-wave of an ECG at a second time that is 0.8 seconds after the first time. The sensor analysis component  102  may then receive data associated with capnography signal that includes a waveform of a breath at a third time that is 0.5 seconds after the second time. The capture component  106  determines a likelihood that capture has been achieved using the data received at different times, such as by determining a first likelihood using the data associated with the first and second T-waves, then refining the likelihood once the data associated with the capnography signal is received. In some examples, the capture component  106  inputs the data associated with the different biological parameters received at different times into the machine-learned model  108 , which returns the likelihood that capture has been achieved during pacing. 
     In some examples, the capture component  106  accounts for electrical stimulations administered to the patient that appear in the data received from the biological sensors. For instance, in ECG measurements, electrical stimulations often cause a “blank” in the data generated by the ECG sensor when the electrical stimulation is administered, because the electrical stimulation is significantly more intense than the electrical output of the heart and thus more powerful than the ECG sensor can record. Therefore, the capture component  106  determines a magnitude of a response of the patient to the electrical stimulation as indicated in the data received from the biological sensor. Continuing with the ECG example, the magnitude of the response corresponds to a difference in the electrical stimulation that was administered and the amplitude of the ECG signal at the time that the electrical stimulation was administered. The capture component  106  removes the magnitude of the response from the data associated with the biological parameter prior to determining the likelihood that capture was achieved as a result of the electrical stimulation. In this way, impact of the electrical stimulation itself on sensor data is reduced, and the accuracy of the sensor data associated with the biological parameter is increased. 
     The user interface (UI) component  110  may display a variety of information in association with biological parameters and/or pacing administration on a user interface  112  of the pacing device  100 , and/or a remote computing device (not pictured). For example, the UI component  110  displays values associated with blood pressure, pulse rate, ETCO 2 , ventilation rate, and the like, along with signals that may include waveforms representative of ECG, blood pressure, ETCO 2 , and so on overtime. In examples, the UI component  110  displays an indication of the likelihood that capture has been achieved during pacing, based on data associated with multiple biological parameters and/or a comparison of recent sensor data to historical sensor data as described above. The indication of the likelihood may assist a healthcare provider in cases where the healthcare provider is administering pacing and controlling the current level manually by combining information associated with multiple biological parameters into a single indicator of whether capture has been achieved, and if not, how to increase the likelihood of achieving capture. The UI component  110  can display the indication of the likelihood that capture has been achieved during pacing as a percentage likelihood (e.g., 25% likelihood, 50% likelihood, 75% likelihood, etc.), as a binary indication of capture (e.g., “Capture Achieved” or “Capture Not Achieved”), as a gauge indicator, as a bar indicator, and so forth. In some cases, the UI component also displays a recommendation of how to modify a current of the electrical stimulation being delivered to the patient during pacing, and/or an interval between electrical stimulations, based on a determination by the capture component  106  that modifying the electrical stimulation will increase the likelihood of capture. 
     In some examples, the UI component  110  allows different configurations of representations of various biological parameters on the user interface  112 . For instance, the UI component  110  is configured to display more representations of biological parameters than those illustrated in the user interface  112 , fewer representations of biological parameters than those illustrated in the user interface  112 , representations of biological parameters in different locations on the user interface  112  than illustrated, and so on. In an illustrative example, a healthcare provider may choose to display a single representation of a biological parameter in the user interface  112 , such as the ECG waveform. As noted above, however, having information associated with multiple biological parameters displayed simultaneously during pacing may assist a healthcare provider with determining whether capture has been achieved, and/or whether to modify the electrical stimulations that are delivered during pacing. 
     Accordingly, in examples, the UI component  110  determines that pacing is being administered and that fewer and/or different representations of biological parameters are currently being displayed than a predefined set of biological parameter representations that are helpful to identify capture. For instance, the predefined set of biological parameter representations may include ECG, SpO 2 , and ETCO 2 , although other examples are also considered (and are not limited to three representations). In response, the UI component  110  causes additional representation(s) of biological parameter(s) to be displayed on the user interface  112  that were previously absent from the user interface  112 . Referencing the illustrative example above, the UI component  110  may cause an SpO 2  (plethysmography) waveform and an ETCO 2  trendline or capnography waveform to be displayed on the user interface  112  after pacing administration begins. In some examples, the UI component  110  displays a notification that additional representation(s) are absent from being displayed in the user interface  112  after determining that pacing is being administered, and prior to displaying the additional representation(s). The notification may include a selectable control that, when selected, causes the additional representation(s) to be displayed in the user interface  112 . The notification may also include an additional selectable control that, when selected, causes the additional representation(s) to not be displayed in the user interface  112 , which may be desirable to healthcare providers who have representations of the other biological parameters displayed elsewhere. In some cases, the UI component  110  outputs visual feedback, audio feedback, and/or haptic feedback with the notification, to draw the attention of the healthcare provider that additional information is available to be displayed on the user interface  112  during pacing. 
     The UI component  110  may include other information in the notification (or in a different notification) as well. For example, in response to the sensor analysis component  102  determining that the patient has an internal pacemaker, the UI component  110  outputs a notification on the user interface  112  indicating that the patient has an internal pacemaker. Such a notification may also include recommendations on whether and/or how to administer pacing differently to a patient with an internal pacemaker than to a patient without an internal pacemaker. 
     In some examples, the UI component  110  controls which representations of biological parameters to display based on a quality of the sensor data received from the various sensors. For instance, if a sensor is placed incorrectly or is malfunctioning, the data may inaccurately represent the biological parameter and thus cause confusion on behalf of the healthcare provider during pacing. Therefore, the UI component  110  applies quality thresholds to the sensor data, such as whether a sensor is providing data, whether the sensor data is greater than or less than a threshold for a particular biological parameter (e.g., ECG data with an average frequency greater than 150 Hz), whether there is an artifact detected in the sensor data (e.g., excessive electromagnetic, muscle, or motion artifact), and the like. If the UI component  110  determines that the sensor data does not meet the quality threshold, the UI component withholds the notification to display a representation associated with the sensor data of the particular biological parameter. Alternatively or additionally, the UI component  110  removes the representation associated with the sensor data of the particular biological parameter if previously displayed on the user interface  112  to avoid confusion by the healthcare provider, and/or displays a notification that the representation associated with the sensor data of the particular biological parameter is poor quality, such as with a recommendation to remove the particular biological parameter from the display. If the UI component  110  determines that the sensor data does meet the quality threshold, the UI component provides the notification to display a representation associated with the sensor data of the particular biological parameter, or in some cases displays the representation of the biological parameter automatically without first displaying a notification. 
     In many cases, the pacing device  100  includes a printing device  114  that enables a healthcare provider to print historical data associated with biological parameter(s). Because the user interface  112  displays a limited time period of the various representations of biological parameters and continues to update over time, printing the historical data provides the healthcare provider with more information about the biological parameters, such as a status of the biological parameters prior to administration of pacing, a status of the biological parameters in response to previous electrical stimulations during pacing, and so forth. Accordingly, in response to receiving a user input to print historical data associated with the biological parameter(s), the UI component  110  causes the printing device  114  to print a representation of the historical data. For example, the printing device  114  prints a representation of ECG data prior to pacing initiation, and prints a representation of the ECG data during pacing, and/or when one or more parameters (e.g., a current) of an electrical stimulation is adjusted. In some examples, the UI component  110  includes additional information in the printed representation, such as indications of intervals between heartbeats of the patient (and/or breaths of the patient), indications of when a pulse associated with pacing occurred, and so forth. In this way, the UI component  110  provides additional information to the healthcare provider that is easily interpreted to assist the healthcare provider in determining whether a condition of the patient is improving during pacing. Additional details regarding functionality of the UI component  110  are discussed in relation to  FIG. 2  and  FIG. 3 . 
     For example,  FIG. 2  illustrates a pacing device  200  displaying a user interface  202  indicating a time at which an electrical stimulation was administered across multiple biological parameters, according to the techniques described herein. The pacing device  200  may correspond to the pacing device  100  described in relation to  FIG. 1 . Accordingly, reference is made in the description of the pacing device  200  to various components described in relation to  FIG. 1 . 
     The user interface  202  includes various example representations of different biological parameters. A representation  204  illustrates ECG sensor data, and includes multiple T-waves corresponding to heartbeats of a patient. A representation  206  illustrates SpO 2  sensor data, and includes multiple plethysmography waves also corresponding to heartbeats of the patient. A representation  208  illustrates CO 2  sensor data, and includes capnography waveforms associated with changes in cardiac output of the patient. The user interface  202  also includes indicators  210  that overlay the representation  204 , the representation  206 , and the representation  208 , where the indicators  210  correspond to times at which electrical stimulation was provided to the patient during pacing. In some examples, the UI component  110  displays the representation  204 , the representation  206 , the representation  208  (collectively, “representations  204 ,  206 , and  208 ”), and the indicators  210  by accounting for delays in receiving the respective signals from the biological sensors providing the ECG sensor data, the SpO 2  sensor data, and the CO 2  sensor data. In an illustrative example, the UI component  110  may determine that the ECG sensor data is received at a 50 millisecond delay, and the SpO 2  sensor data is received at a 200 millisecond delay, such as based on responses detected by the sensor analysis component  102  to administration of the electrical stimulation pulses during pacing. Accordingly, the UI component  110  displays the indicators  210  at locations relative to the representations  204 ,  206 , and  208  such that the indicators  210  appear at a same time in each of the representations  204 ,  206 , and  208 . This may include the UI component delaying display of a representation of biological parameter(s), such as by delaying output of the ECG sensor data by 150 milliseconds to account for the delay in the illustrative example above. 
       FIG. 3  illustrates a pacing device  300  displaying a user interface  302  including a notification to display a representation of an additional biological parameter, according to the techniques described herein. The pacing device  300  may correspond to the pacing device  100  described in relation to  FIG. 1 . Accordingly, reference is made in the description of the pacing device  300  to various components described in relation to  FIG. 1 . 
     The user interface  302  includes a representation  304  of a single biological parameter, in this case an ECG waveform. As discussed above, the UI component  110  detects that pacing is being administered, and determines which biological parameter(s) are present in the user interface  302 . The UI component  110  determines that additional biological parameters are absent from the user interface  302  that are included in a predefined set of biological parameter representations that are helpful to identify capture. In response, the UI component  110  displays a notification  306  in the user interface  302  that pacing has been initiated by the pacing device  100 , and includes a suggestion of an additional biological parameter (e.g., SpO 2 ) that can be displayed in the user interface  302  to assist the healthcare provider with identifying capture. The notification  306  includes a “Yes” selectable control that, when selected, causes a representation of the additional biological parameter(s) to be displayed in the user interface  302  with the representation  304 . The notification  306  also includes a “No” selectable control that, when selected, causes the representation of the additional biological parameter to continue to be omitted from the user interface  302 , while the representation  304  remains displayed in the user interface  302 . 
     In addition to the notification  306 , in some cases, the pacing device  300  may provide additional feedback to draw attention of the healthcare provider that other representations are available for display, such as visual feedback other than the notification  306  (e.g., a flashing LED light), audio feedback, haptic feedback, and so forth. Additionally, examples are considered in which the UI component  110  displays the additional biological parameters in the user interface  302  without first presenting a notification, as described above in relation to  FIG. 1 . 
     Example Methods 
     Various methods are described with reference to the example pacing device of  FIG. 1  for convenience and ease of understanding. However, the methods described are not limited to being performed using the system of  FIG. 1  and may be implemented using systems and devices other than those described herein. 
     The methods described herein represent sequences of operations that can be implemented in hardware, software, or a combination thereof. In the context of software, the blocks represent computer-executable instructions stored on one or more computer-readable storage media that, when executed by one or more processors, perform the recited operations. Generally, computer-executable instructions include routines, programs, objects, components, data structures, and the like that perform particular functions or implement particular 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 described operations can be combined in any order and/or in parallel to implement the processes. In some examples, one or more operations of the method may be omitted entirely. Moreover, the methods described herein can be combined in whole or in part with each other or with other methods. 
       FIG. 4  is an example method  400  for providing electrical stimulation based on a likelihood of capture determined from multiple biological parameters, according to the techniques described herein. 
     At operation  402 , the pacing device  100  provides an electrical stimulation to a patient. In examples, the electrical stimulation is one of multiple pulses provided during pacing, such as to attain capture of the heart of a patient experiencing bradycardia. For instance, the pacing component  104  causes a discharge circuit to deliver the electrical stimulation to electrodes attached to the patient via electrode leads connected to the pacing device  100 . The pacing component  104  controls a current and/or a voltage of the electrical stimulation delivered to the electrodes, along with an interval at which the electrical stimulation is administered. In some cases, the electrical stimulation includes a train of stimuli, and/or a period of time (e.g., one heartbeat cycle length, one minute, etc.) during which electrical stimulation occurred. 
     At operation  404 , the pacing device  100  receives data associated with a first biological parameter and data associated with a second biological parameter. The first biological parameter may correspond to ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , or ventilation, to name some examples. The second biological parameter may correspond to a different one of ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , or ventilation than the first biological parameter. The data associated with the first biological parameter and the data associated with the second biological parameter may be received at different times and/or intervals, such as for biological parameters that occur at different cycle rates (e.g., heartbeat and ventilation). 
     At operation  406 , the pacing device  100  determines a likelihood of capture from the electrical stimulation based on the data associated with the first biological parameter and the data associated with the second biological parameter. In some cases, the capture component  106  employs a rules-based system to determine the likelihood that capture has been achieved. Such a rules-based system includes thresholds associated with different biological parameters (e.g., in a database or look-up table). The capture component  106  receives data associated with biological parameters before, during, and/or after pacing is administered to a patient, and compares values included in the data to the thresholds to determine a likelihood that capture has been achieved. 
     Alternatively or additionally, the capture component  106  may employ machine-learned model(s)  108  to determine the likelihood that capture has been achieved. The machine-learned models  108  also utilize thresholds associated with different biological parameters, but in some cases the parameters of the machine-learned models  108  are modified to improve accuracy of capture likelihood determinations. For instance, the capture component  106  receives data associated with biological parameters and inputs at least a portion of this data into the machine-learned models  108 . 
     At operation  408 , the pacing device  100  determines whether the likelihood of capture is greater than a threshold likelihood. The pacing component  104  compares the likelihood that capture has been achieved to at least one threshold likelihood of capture to determine whether the electrical current level of the electrical stimulation being delivered to the patient should change or remain the same for the upcoming electrical stimulation pulse. If the pacing device  100  determines that the likelihood is greater than or equal to the threshold likelihood (e.g., “Yes” at operation  408 ), the pacing device  100  provides a same electrical stimulation at operation  410 . In this way, the electrical stimulation will remain at the same electrical current level if capture is achieved and the condition of the patient is improving (or not deteriorating). The method  400  then returns to the operation  404 , at which the pacing device  100  receives additional data associated with the first biological parameter and the second biological parameter. The pacing device  100  continues to evaluate whether the electrical stimulations being administered to the patient are maintaining capture, by comparing a likelihood of capture to the threshold likelihood. 
     If the pacing device  100  determines that the likelihood is less than the threshold likelihood (e.g., “No” at operation  408 ), the pacing device  100  provides a modified electrical stimulation at operation  412 . For example, if the likelihood of capture is less than the threshold, the pacing component  104  increases the electrical current level for an upcoming electrical stimulation (e.g., by 10 milliamps). The method  400  then returns to the operation  404 , at which the pacing device  100  receives additional data associated with the first biological parameter and the second biological parameter. The pacing device  100  continues to evaluate whether the electrical stimulations being administered to the patient are achieving capture, by comparing a likelihood of capture to the threshold likelihood. For example, if capture is not achieved by increasing the electrical stimulation by 10 milliamps, the pacing component  104  increases the electrical current of the electrical stimulation again by another 10 milliamps. 
       FIG. 5  is an example method  500  for providing electrical stimulation based on sensor data collected at different times, according to the techniques described herein. As described above, in some cases, the electrical stimulation includes a train of stimuli, and/or a period of time (e.g., one heartbeat cycle length, one minute, etc.) during which electrical stimulation occurred. 
     At operation  502 , the pacing device  100  receives sensor data prior to an electrical stimulation. The sensor data is associated with at least one biological parameter, such as ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , and/or ventilation, to name some examples. In some examples, the sensor analysis component  102  receives the sensor data prior to administration of pacing, such as while electrodes are being placed on the patient, as vital signs are being collected, and so forth. The pacing device  100  stores the sensor data received prior to the electrical stimulation (also referred to as “historical sensor data”) for later comparison with sensor data received during pacing. In some instances, the historical sensor data is from a past pacing setting, such as a previous electrical stimulation that was administered at a previous, different current amplitude. Alternatively or additionally, the historical sensor data is from data prior to achieving capture, and/or is from after capture has been achieved while monitoring to ensure that capture is maintained over time. 
     At operation  504 , the pacing device  100  provides an electrical stimulation. The pacing component  104  may receive a user input to administer pacing to the patient, and subsequently deliver the electrical stimulation in accordance with pacing protocols. For instance, the pacing component  104  causes a discharge circuit to deliver the electrical stimulation to electrodes attached to the patient via electrode leads connected to the pacing device  100 . The pacing component  104  controls a current and/or a voltage of the electrical stimulation delivered to the electrodes, along with an interval at which the electrical stimulation is administered. 
     At operation  506 , the pacing device receives sensor data after the electrical stimulation. The sensor data received after the electrical stimulation is also associated with at least one biological parameter, such as ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , and/or ventilation, for instance. 
     At operation  508 , the pacing device  100  determines a difference in sensor data values at different times, such as by comparing the sensor data received after the electrical stimulation to the sensor data received prior to the electrical stimulation. For example, the sensor analysis component  102  determines a difference between sensor data (e.g., an ECG pulse) generated after an electrical stimulation was administered and historical sensor data collected prior to administration of electrical stimulation during pacing. 
     At operation  510 , the pacing device  100  determines whether the difference in sensor data values is greater than a threshold difference. If the difference between the sensor data after the electrical stimulation was administered and historical sensor data collected prior to administration of electrical stimulation during pacing is greater than or equal to a threshold difference (e.g., 50%, 20%, 10% difference, etc.), the capture component  106  determines that the electrical stimulation has likely caused capture. However, if the difference between the sensor data after the electrical stimulation was administered and historical sensor data collected prior to administration of electrical stimulation during pacing is less than the threshold difference, the capture component  106  determines that the electrical stimulation has likely failed to cause capture. Similar to the discussion above, the capture component  106  may input the difference into the machine-learned model  108 , and receive a likelihood that the electrical stimulation caused capture from the machine-learned model based on the difference. 
     If the pacing device  100  determines that the difference is greater than or equal to the threshold difference (e.g., “Yes” at operation  510 ), the pacing device  100  provides a same electrical stimulation at operation  512 . For example, the electrical stimulation will remain at the same electrical current level if capture is achieved and the condition of the patient is improving (or not deteriorating). The method  500  then returns to the operation  506 , at which the pacing device  100  receives additional data associated with the biological parameter after the subsequent electrical stimulation. In some cases, the pacing component  104  determines differences between values associated with the biological parameter between pacing intervals in addition to or alternatively from determining the difference from the historical sensor data. Thus, the pacing component  104  tracks how capture is progressing over time with the administration of pacing. 
     If the pacing device  100  determines that the difference is less than the threshold difference (e.g., “No” at operation  510 ), the pacing device  100  provides a modified electrical stimulation at operation  514 . The pacing component  104  then causes the electrical stimulation being administered to the patient to increase, as the electrical stimulation is likely insufficient to improve the magnitude of the patient&#39;s heartbeat. The method  500  then returns to the operation  506 , at which the pacing device  100  receives additional data associated with the biological parameter after the subsequent modified electrical stimulation. In some examples, the pacing component  104  determines differences between values associated with the biological parameter between pacing intervals in addition to or alternatively from determining the difference from the historical sensor data. Thus, the pacing component  104  tracks whether the modification to the electrical current is causing capture to be achieved over time with the administration of pacing. 
       FIG. 6  is an example method  600  for displaying a representation of a biological parameter based on a determination that pacing is being administered, according to the techniques described herein. 
     At operation  602 , the pacing device  100  receives data associated with a biological parameter of a patient over a first time period. Similar to the discussion above, the biological parameter may correspond to ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , or ventilation, to name some examples. In some cases, the pacing device  100  receives data associated with one or more additional biological parameters as well. Additional biological parameter(s) may correspond to a different one of ECG, SpO 2 , NIBP, invasive blood pressure, ETCO 2 , rSO 2 , or ventilation than the first biological parameter. The first time period may correspond to a time period prior to administration of pacing, a time period after pacing began to be administered, or a combination of these. 
     At operation  604 , the pacing device  100  determines that pacing is being administered. At operation  606 , the pacing device determines that a representation of the data associated with the biological parameter is absent from being displayed on a display device over the first time period. For instance, the UI component  110  determines that a user interface being displayed on the display device includes information that is unrelated to the biological parameter, determines that information related to a different biological parameter is being displayed by the display device, or determines that the display is off, to name a few examples. 
     At operation  608 , the pacing device  100  displays the representation of the data associated with the biological parameter substantially continuously over a second time period based on determining that pacing is being administered to the patient and that the representation was absent from being displayed on the display device over the first time period. For example, the second time period occurs after determining that pacing is being administered. In some examples, the UI component  110  determines that one or more different representations of biological parameters are currently being displayed than a predefined set of biological parameter representations that are helpful to identify capture. For instance, the predefined set of biological parameter representations may include ECG, SpO 2 , and ETCO 2 , although other examples are also considered (and are not limited to three representations). The UI component  110  may display a particular representation without input from a healthcare provider in response to the determination that pacing is being administered, to ensure that the healthcare provider is able to view representations of biological parameters that assist in pacing and capture determinations. In some examples, the UI component  110  displays a notification that a particular representation is absent from the user interface  112 , then displays the particular representation in the user interface  112  based on selection of a selectable control to display the particular representation. Accordingly, healthcare providers are presented with one or more biological parameters that can assist with capture and pacing, without having to search through menus on the pacing device to select desired parameters to view. 
     Example External Defibrillator 
       FIG. 7  illustrates an example of an external defibrillator  700  configured to perform various functions described herein. For example, the external defibrillator  700  is the pacing device  100  described above with reference to  FIG. 1 , as evidenced by inclusion of the sensor analysis component  102 , the pacing component  104 , and the UI component  110  in memory  714  of the external defibrillator  700 . In some instances, the external defibrillator  700  detects arrhythmias such as bradycardia using the techniques described herein. 
     The external defibrillator  700  includes an electrocardiogram (ECG) port  702  connected to multiple ECG connectors  704 . In some cases, the ECG connectors  704  are removeable from the ECG port  702 . For instance, the ECG connectors  704  are plugged into the ECG port  702 . The ECG connectors  704  are connected to ECG electrodes  706 , respectively. In various implementations, the ECG electrodes  706  are disposed on different locations on an individual  708 . A detection circuit  710  is configured to detect relative voltages between the ECG electrodes  706 . These voltages are indicative of the electrical activity of the heart of the individual  708 . 
     In various implementations, the ECG electrodes  706  are in contact with the different locations on the skin of the individual  708 . In some examples, a first one of the ECG electrodes  706  is placed on the skin between the heart and right arm of the individual  708 , a second one of the ECG electrodes  706  is placed on the skin between the heart and left arm of the individual  708 , and a third one of the ECG electrodes  706  is placed on the skin between the heart and a leg (either the left leg or the right leg) of the individual  708 . In these examples, the detection circuit  708  is configured to measure the relative voltages between the first, second, and third ECG electrodes  706 . Respective pairings of the ECG electrodes  706  are referred to as “leads,” and the voltages between the pairs of ECG electrodes  706  are known as “lead voltages.” In some examples, more than three ECG electrodes  706  are included, such that 5-lead or 12-lead ECG signals are detected by the detection circuit  710 . 
     The detection circuit  710  includes at least one analog circuit, at least one digital circuit, or a combination thereof. The detection circuit  710  receives the analog electrical signals from the ECG electrodes  706 , via the ECG port  702  and the ECG leads  704 . In some cases, the detection circuit  710  includes one or more analog filters configured to filter noise and/or artifact from the electrical signals. The detection circuit  710  includes an analog-to-digital (ADC) in various examples. The detection circuit  710  generates a digital signal indicative of the analog electrical signals from the ECG electrodes  706 . This digital signal can be referred to as an “ECG signal” or an “ECG.” 
     In some cases, the detection circuit  710  further detects an electrical impedance between at least one pair of the ECG electrodes  706 . For example, the detection circuit  710  includes, or otherwise controls, a power source that applies a known voltage across a pair of the ECG electrodes  706  and detects a resultant current between the pair of the ECG electrodes  706 . The impedance is generated based on the applied voltage and the resultant current. In various cases, the impedance corresponds to respiration of the individual  708 , chest compressions performed on the individual  708 , and other physiological states of the individual  708 . In various examples, the detection circuit  710  includes one or more analog filters configured to filter noise and/or artifact from the resultant current. The detection circuit  710  generates a digital signal indicative of the impedance using an ADC. This digital signal can be referred to as an “impedance signal” or an “impedance.” 
     The detection circuit  710  provides the ECG signal and/or the impedance signal one or more processors  712  in the external defibrillator  700 . In some implementations, the processor(s)  712  includes a central processing unit (CPU), a graphics processing unit (GPU), both CPU and GPU, or other processing unit or component known in the art. 
     The processor(s)  712  is operably connected to memory  714 . In various implementations, the memory  712  is volatile (such as random access memory (RAM)), non-volatile (such as read only memory (ROM), flash memory, etc.) or some combination of the two. The memory  714  stores instructions that, when executed by the processor(s)  712 , causes the processor(s)  712  to perform various operations. In various examples, the memory  714  stores methods, threads, processes, applications, objects, modules, any other sort of executable instruction, or a combination thereof. In some cases, the memory  714  stores files, databases, or a combination thereof. In some examples, the memory  714  includes, but is not limited to, RAM, ROM, electrically erasable programmable read-only memory (EEPROM), flash memory, or any other memory technology. In some examples, the memory  714  includes one or more of CD-ROMs, digital versatile discs (DVDs), content-addressable memory (CAM), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the processor(s)  712  and/or the external defibrillator  700 . In some cases, the memory  714  at least temporarily stores the ECG signal and/or the impedance signal. 
     In various examples, the memory  714  includes a detector  716 , which causes the processor(s)  712  to determine, based on the ECG signal and/or the impedance signal, whether the individual  708  is exhibiting a particular heart rhythm. For instance, the processor(s)  712  determines whether the individual  708  is experiencing a shockable rhythm that is treatable by defibrillation. Examples of shockable rhythms include ventricular fibrillation (VF) and ventricular tachycardia (V-Tach). In some examples, the processor(s)  712  determines whether any of a variety of different rhythms (e.g., asystole, sinus rhythm, atrial fibrillation (AF), etc.) are present in the ECG signal. 
     The processor(s)  712  is operably connected to one or more input devices  718  and one or more output devices  720 . Collectively, the input device(s)  718  and the output device(s)  720  function as an interface between a user and the defibrillator  700 . The input device(s)  718  is configured to receive an input from a user and includes at least one of a keypad, a cursor control, a touch-sensitive display, a voice input device (e.g., a speaker), a haptic feedback device, or any combination thereof. The output device(s)  720  includes at least one of a display, a speaker, a haptic output device, a printer, or any combination thereof. In various examples, the processor(s)  712  causes a display among the input device(s)  718  to visually output a signal which may include a waveform of the ECG signal, and/or the impedance signal. In some implementations, the input device(s)  718  includes one or more touch sensors, the output device(s)  720  includes a display screen, and the touch sensor(s) are integrated with the display screen. Thus, in some cases, the external defibrillator  700  includes a touchscreen configured to receive user input signal(s) and visually output physiological parameters, such as the ECG signal and/or the impedance signal. 
     In some examples, the memory  714  includes an advisor  721 , which, when executed by the processor(s)  712 , causes the processor(s)  712  to generate advice and/or control the output device(s)  720  to output the advice to a user (e.g., a rescuer). In some examples, the processor(s)  712  provides, or causes the output device(s)  720  to provide, an instruction to perform CPR on the individual  708 . In some cases, the processor(s)  712  evaluates, based on the ECG signal, the impedance signal, or other physiological parameters, CPR being performed on the individual  708  and causes the output device(s)  720  to provide feedback about the CPR in the instruction. According to some examples, the processor(s)  712 , upon identifying that a shockable rhythm is present in the ECG signal, causes the output device(s)  720  to output an instruction and/or recommendation to administer a defibrillation shock to the individual  708 . 
     The memory  714  also includes an initiator  723  which, when executed by the processor(s)  712 , causes the processor(s)  712  to control other elements of the external defibrillator  700  in order to administer a defibrillation shock to the individual  708 . In some examples, the processor(s)  712  executing the initiator  723  selectively causes the administration of the defibrillation shock based on determining that the individual  708  is exhibiting the shockable rhythm and/or based on an input from a user (received, e.g., by the input device(s)  718 . In some cases, the processor(s)  712  causes the defibrillation shock to be output at a particular time, which is determined by the processor(s)  712  based on the ECG signal and/or the impedance signal. Alternatively or additionally, the initiator  723  causes the processor(s)  712  to administer electrical stimulations at intervals corresponding to pacing pulses, such as described above in relation to  FIG. 1 . 
     The processor(s)  712  is operably connected to a charging circuit  722  and a discharge circuit  724 . In various implementations, the charging circuit  722  includes a power source  726 , one or more charging switches  728 , and one or more capacitors  730 . The power source  726  includes, for instance, a battery. The processor(s)  712  initiates a defibrillation shock by causing the power source  726  to charge at least one capacitor among the capacitor(s)  730 . For example, the processor(s)  712  activates at least one of the charging switch(es)  728  in the charging circuit  722  to complete a first circuit connecting the power source  726  and the capacitor to be charged. Then, the processor(s)  712  causes the discharge circuit  724  to discharge energy stored in the charged capacitor across a pair of defibrillation electrodes  730 , which are in contact with the individual  708 . For example, the processor(s)  712  deactivates the charging switch(es)  728  completing the first circuit between the capacitor(s)  730  and the power source  726 , and activates one or more discharge switches  732  completing a second circuit connecting the charged capacitor  730  and at least a portion of the individual  708  disposed between defibrillation electrodes  734 . 
     The energy is discharged from the defibrillation electrodes  734  in the form of a defibrillation shock. For example, the defibrillation electrodes  734  are connected to the skin of the individual  708  and located at positions on different sides of the heart of the individual  708 , such that the defibrillation shock is applied across the heart of the individual  708 . The defibrillation shock, in various examples, depolarizes a significant number of heart cells in a short amount of time. The defibrillation shock, for example, interrupts the propagation of the shockable rhythm (e.g., VF or V-Tach) through the heart. In some examples, the defibrillation shock is 200 J or greater with a duration of about 0.015 seconds. In some cases, the defibrillation shock has a multiphasic (e.g., biphasic) waveform. The discharge switch(es)  732  are controlled by the processor(s)  712 , for example. In various implementations, the defibrillation electrodes  734  are connected to defibrillation connectors  736 . The defibrillation connectors  736  are connected to a defibrillation port  738 , in implementations. According to various examples, the defibrillation connectors  736  are removable from the defibrillation port  738 . For example, the defibrillation connectors  736  are plugged into the defibrillation port  738 . 
     In various implementations, the processor(s)  712  is operably connected to one or more transceivers  740  that transmit and/or receive data over one or more communication networks  742 . For example, the transceiver(s)  740  includes a network interface card (NIC), a network adapter, a local area network (LAN) adapter, or a physical, virtual, or logical address to connect to the various external devices and/or systems. In various examples, the transceiver(s)  740  includes any sort of wireless transceivers capable of engaging in wireless communication (e.g., radio frequency (RF) communication). For example, the communication network(s)  742  includes one or more wireless networks that include a 3 rd  Generation Partnership Project (3GPP) network, such as a Long Term Evolution (LTE) radio access network (RAN) (e.g., over one or more LE bands), a New Radio (NR) RAN (e.g., over one or more NR bands), or a combination thereof. In some cases, the transceiver(s)  740  includes other wireless modems, such as a modem for engaging in WI-FI®, WIGIG®, WIMAX®, BLUETOOTH®, or infrared communication over the communication network(s)  742 . 
     The defibrillator  700  is configured to transmit and/or receive data (e.g., ECG data, impedance data, data indicative of one or more detected heart rhythms of the individual  708 , data indicative of one or more defibrillation shocks administered to the individual  708 , etc.) with one or more external devices  744  via the communication network(s)  742 . The external devices  744  include, for instance, mobile devices (e.g., mobile phones, smart watches, etc.), Internet of Things (IoT) devices, medical devices, computers (e.g., laptop devices, servers, etc.), or any other type of computing device configured to communicate over the communication network(s)  742 . In some examples, the external device(s)  744  is located remotely from the defibrillator  700 , such as at a remote clinical environment (e.g., a hospital). According to various implementations, the processor(s)  712  causes the transceiver(s)  740  to transmit data to the external device(s)  744 . In some cases, the transceiver(s)  740  receives data from the external device(s)  744  and the transceiver(s)  740  provide the received data to the processor(s)  712  for further analysis. 
     In various implementations, the external defibrillator  700  also includes a housing  746  that at least partially encloses other elements of the external defibrillator  700 . For example, the housing  746  encloses the detection circuit  710 , the processor(s)  712 , the memory  714 , the charging circuit  722 , the transceiver(s)  740 , or any combination thereof. In some cases, the input device(s)  718  and output device(s)  720  extend from an interior space at least partially surrounded by the housing  746  through a wall of the housing  746 . In various examples, the housing  746  acts as a barrier to moisture, electrical interference, and/or dust, thereby protecting various components in the external defibrillator  700  from damage. 
     In some implementations, the external defibrillator  700  is an automated external defibrillator (AED) operated by an untrained user (e.g., a bystander, layperson, etc.) and can be operated in an automatic mode. In automatic mode, the processor(s)  712  automatically identifies a rhythm in the ECG signal, makes a decision whether to administer a defibrillation shock, charges the capacitor(s)  730 , discharges the capacitor(s)  730 , or any combination thereof. In some cases, the processor(s)  712  controls the output device(s)  720  to output (e.g., display) a simplified user interface to the untrained user. For example, the processor(s)  712  refrains from causing the output device(s)  720  to display a waveform of the ECG signal and/or the impedance signal to the untrained user, in order to simplify operation of the external defibrillator  700 . 
     In some examples, the external defibrillator  700  is a monitor-defibrillator utilized by a trained user (e.g., a clinician, an emergency responder, etc.) and can be operated in a manual mode or the automatic mode. When the external defibrillator  700  operates in manual mode, the processor(s)  712  cause the output device(s)  720  to display a variety of information that may be relevant to the trained user, such as signals that include waveforms indicating the ECG data and/or impedance data, notifications about detected heart rhythms, and the like. 
     Example Clauses 
     A. A method including: providing, via an external pacing device at a first time, a first electrical stimulation at a first current level to an external surface of a patient; receiving, from a first biological sensor at a second time after the first time, first data associated with a first biological parameter of the patient; receiving, from a second biological sensor at the second time, second data associated with a second biological parameter of the patient, the second biological parameter different from the first biological parameter; determining, based on the first data and the second data received at the second time, a likelihood that the first electrical stimulation has caused capture of a heart of the patient; comparing the likelihood to a threshold likelihood; and responsive to determining that the likelihood is less than the threshold likelihood, providing a second electrical stimulation at a second current level via the external pacing device, the second current level being different than the first current level. 
     B. The method of clause A, wherein the first data associated with the first biological parameter includes: a T-wave or QRS complex identified in an electrocardiogram (ECG); a plethysmography signal identified in an oxygen saturation (SpO 2 ) measurement; a non-invasive blood pressure (NIBP) signal identified in an NIBP measurement; a regional cerebral oxygen saturation (rSO 2 ) signal identified in an rSO 2  measurement; an invasive blood pressure signal identified in an invasive blood pressure measurement; an end-tidal CO 2  (ETCO 2 ) signal identified in an ETCO 2  measurement; and a capnography signal identified in a respiratory measurement. 
     C. The method of clause B, wherein the second data associated with the second biological parameter includes a different one of the T-wave or the QRS complex, the plethysmography signal, the NIBP signal, the rSO 2  signal, the invasive blood pressure signal, the ETCO 2  signal, or the capnography signal than the first biological parameter. 
     D. The method of any one of clauses A-C, further including: displaying a first representation of the first biological parameter in a user interface; displaying a second representation of the second biological parameter on the user interface with the first representation of the first biological parameter; and displaying an indicator overlaying the first representation and the second representation at the first time at which the first electrical stimulation was provided. 
     E. The method of clause D, further including: determining a first delay associated with receiving the first data from the first biological sensor; and determining a second delay associated with receiving the second data from the second biological sensor, wherein a location of the indicator relative to the first representation and the second representation is based on the first delay and the second delay. 
     F. The method of any one of clauses A-E, wherein determining the likelihood includes: inputting the first data associated with the first biological parameter and the second data associated with the second biological parameter into a machine-learned model trained to identify heart capture; and receiving, from the machine-learned model, the likelihood that the first electrical stimulation has caused the capture of the heart of the patient. 
     G. The method of clause F, wherein the machine-learned model includes a logistic regression model. 
     H. The method of any one of clauses A-G, wherein the capture corresponds to electrical capture or mechanical capture of the heart of the patient. 
     I. The method of any one of clauses A-H, further including: receiving, at a third time prior to the first time at which the patient was provided the electrical stimulation, third data associated with the first biological parameter; and determining a difference between the third data associated with the first biological parameter and first data associated with the biological parameter received at the second time, wherein determining the likelihood is further based on the difference. 
     J. The method of clause I, wherein determining the likelihood includes: inputting the first data associated with the first biological parameter and the difference into a machine-learned model trained to identify heart capture; and receiving, from the machine-learned model, the likelihood that the first electrical stimulation has caused the capture of the heart of the patient. 
     K. The method of any one of clauses A-J, wherein the first data associated with the first biological parameter includes an indication of the electrical stimulation, the method further including: determining a magnitude of a response of the patient to the electrical stimulation from the first data; removing the magnitude of the response from the first data, wherein determining the likelihood is further based on removing the magnitude of the response from the first data. 
     L. An external pacing system, including: electrodes configured to deliver electrical stimulations to a patient via electrode leads; a first biological sensor configured to sense a first biological parameter of the patient; a second biological sensor configured to sense a second biological parameter of the patient, the second biological parameter being different than the first biological parameter; a discharge circuit; a processor; and one or more computer-readable media storing instructions that, when executed by the processor, cause the processor to perform operations including: providing a first electrical stimulation at a current level to an external surface of the patient by the discharge circuit via the electrodes at a first time; receiving, from the first biological sensor at a second time after the first time, first data associated with the first biological parameter; receiving, from the second biological sensor at the second time, second data associated with the second biological parameter; determining, based on the first data and the second data received at the second time, a likelihood that the first electrical stimulation has caused capture of a heart of the patient; comparing the likelihood to a threshold likelihood; and responsive to determining that the likelihood is greater than or equal to the threshold likelihood, providing a second electrical stimulation at the current level by the discharge circuit via the electrodes to the patient. 
     M. The external pacing system of clause L, wherein determining the likelihood includes: inputting the first data associated with the first biological parameter and the second data associated with the second biological parameter into a machine-learned model trained to identify heart capture; and receiving, from the machine-learned model, the likelihood that the first electrical stimulation has caused the capture of the heart of the patient. 
     N. An external pacing system, including: a biological sensor; a processor; a discharge circuit communicatively coupled to the processor; electrodes coupled to the discharge circuit via electrode leads and configured to attach to an external surface of a patient; and one or more computer-readable media storing instructions that, when executed by the processor, cause the processor to perform operations including: causing the discharge circuit to provide a first electrical stimulation to the external surface of the patient via the electrodes at a first time, a first electrical stimulation being at a first current level; receiving, from the biological sensor at a second time after the first time, a first value associated with a biological parameter of the patient; causing the discharge circuit to provide a second electrical stimulation to the external surface of the patient via the electrodes at a third time after the second time, the second electrical stimulation being at the first current level; receiving, from the biological sensor at a fourth time after the third time, a second value associated with the biological parameter of the patient; determining a difference between the first value and the second value; comparing the difference to a threshold difference; and responsive to determining that the difference is greater than or equal to the threshold difference, providing a third electrical stimulation at a second current level via the electrodes, the second current level being different than the first current level. 
     O. The external pacing system of clause N, wherein the biological parameter includes an electrocardiogram (ECG) pulse, the first value corresponds to a first magnitude of the ECG pulse at the second time, and the second value corresponds to a second magnitude of the ECG pulse at the fourth time. 
     P. The external pacing system of clause N or O, the operations further including: inputting the difference into a machine-learned model trained to identify heart capture; receiving, from the machine-learned model, a likelihood that the first electrical stimulation and the second electrical stimulation have caused capture of the heart of the patient, wherein providing the third electrical stimulation is further based on the likelihood. 
     Q. The external pacing system of any one of clauses N-P, wherein the biological parameter is a first biological parameter and the biological sensor is a first biological sensor, the operations further including: receiving, from a second biological sensor at a fifth time after the first time, a third value associated with the second biological parameter of the patient, the fifth time being different than the second time and the fourth time; determining, based on the first value, the second value, and the third value, a likelihood that the first electrical stimulation has caused capture of a heart of the patient; and comparing the likelihood to a threshold likelihood, wherein providing the third electrical stimulation at the second current level is further based on determining that the likelihood is greater than or equal to the threshold likelihood. 
     R. The external pacing system of clause Q, wherein determining the likelihood includes: inputting the first value, the second value, and the third value into a machine-learned model trained to identify heart capture; and receiving, from the machine-learned model, the likelihood that the first electrical stimulation and the second electrical stimulation caused the capture of the heart of the patient. 
     S. A method including: causing a discharge circuit to provide a first electrical stimulation at a current level to an external surface of a patient via electrodes at a first time; receiving, from a biological sensor at a second time after the first time, a first value associated with a biological parameter of the patient; causing the discharge circuit to provide a second electrical stimulation at the current level to the external surface of the patient via the electrodes at a third time after the second time; receiving, from the biological sensor at a fourth time after the third time, a second value associated with the biological parameter of the patient; determining a difference between the first value and the second value; comparing the difference to a threshold difference; and responsive to determining that the difference is less than the threshold difference, providing a third electrical stimulation at the current level via the electrode leads. 
     T. The method of clause S, further including: inputting the difference into a machine-learned model trained to identify heart capture; receiving, from the machine-learned model, a likelihood that the first electrical stimulation and the second electrical stimulation have caused capture of the heart of the patient, wherein providing the third electrical stimulation is further based on the likelihood. 
     U. The method of clause S or T, wherein the biological parameter is a first biological parameter and the biological sensor is a first biological sensor, the method further including: receiving, from a second biological sensor at a fifth time after the first time, a third value associated with the second biological parameter of the patient, the fifth time being different than the second time and the fourth time; determining, based on the first value, the second value, and the third value, a likelihood that the first electrical stimulation has caused capture of a heart of the patient; and comparing the likelihood to a threshold likelihood, wherein providing the fourth electrical stimulation at the first current level is further based on determining that the likelihood is less than the threshold likelihood. 
     V. A method including: receiving data associated with a biological parameter of a patient over a first time period; determining that pacing is being administered to the patient; determining that a representation of the data associated with the biological parameter is absent from being displayed on a display device over the first time period; and displaying, on a display device, the representation of the data associated with the biological parameter substantially continuously over a second time period based on determining that pacing is being administered to the patient and that the representation was absent from being displayed on the display device over the first time period. 
     W. The method of clause V, further including: determining a quality of the data over the first time period; and determining that the quality of the data over the first time period is greater than a threshold quality, wherein displaying the representation on the display over the second time period is further based on the quality of the data being greater than the threshold quality. 
     X. The method of clause V or W, further including: displaying, on the display device, a notification that the representation of the data is absent from being displayed responsive to determining that pacing is being administered to the patient and that the representation was absent from being displayed on the display device over the first time period; and receiving a user input to display the representation of the data, wherein displaying the representation on the display over the second time period is further based on receiving the user input. 
     Y. The method of clause X, further including providing visual feedback, audio feedback, or haptic feedback with the notification. 
     Z. The method of any one of clauses V-Y, further including: receiving a user input to print the data associated with the biological parameter for a third time period, the third time period being at least partially prior to the second time period; and printing, by a printing device, a third representation of the data associated with the biological parameter for the third time period, wherein the third representation includes a first indication of intervals between heartbeats of the patient and a second indication of when a pulse associated with the pacing occurred. 
     AA. The method of any one of clauses V-Z, further including: determining that the patient has an internal pacemaker located in a heart of the patient; and displaying, on the display device, a notification that the patient has the internal pacemaker located in the heart of the patient. 
     AB. A system including: a pacing component implemented at least partially in hardware of an external pacing device and configured to provide, at a first time, a first electrical stimulation at a first current level to an external surface of a patient; a sensor analysis component implemented at least partially in hardware of the external pacing device and configured to receive, from a biological sensor at a second time after the first time, data associated with a biological parameter of the patient; a capture component implemented at least partially in hardware of the external pacing device and configured to: determine, based on the data received at the second time, a likelihood that the first electrical stimulation has caused capture of a heart of the patient, compare the likelihood to a threshold likelihood, and responsive to determining that the likelihood is less than the threshold likelihood, cause the pacing component to provide a second electrical stimulation at a second current level, the second current level being different than the first current level. 
     AC. The system of clause AB, wherein the first electrical stimulation is provided at a first timing interval, and wherein the capture component is further configured to, responsive to determining that the likelihood is less than the threshold likelihood, cause the pacing component to provide the second electrical stimulation at a second timing interval, the second timing interval being different than the first timing interval. 
     AD. The system of clause AB or AC, wherein the capture component is configured to determine the likelihood by: inputting the data associated with the biological parameter into a machine-learned model trained to identify heart capture; and receiving, from the machine-learned model, the likelihood that the first electrical stimulation has caused the capture of the heart of the patient. 
     AE. A system including: a pacing component implemented at least partially in hardware of an external pacing device and configured to provide, at a first time, a first electrical stimulation at a first current level to an external surface of a patient; a sensor analysis component implemented at least partially in hardware of the external pacing device and configured to: receive, from a first biological sensor at a second time after the first time, first data associated with a first biological parameter of the patient, and receive, from a second biological sensor at the second time, second data associated with a second biological parameter of the patient, the second biological parameter different from the first biological parameter; a capture component implemented at least partially in hardware of the external pacing device and configured to: determining, based on the first data and the second data received at the second time, a likelihood that the first electrical stimulation has caused capture of a heart of the patient, comparing the likelihood to a threshold likelihood, and determine that the likelihood is less than the threshold likelihood; a user interface (UI) component implemented at least partially in hardware of the external pacing device and configured to display, responsive to the capture component determining that the likelihood is less than the threshold likelihood, a suggestion in a UI to provide a second electrical stimulation at a second current level via the external pacing device, the second current level being different than the first current level. 
     AF. The system of clause AE, wherein the suggestion is a first suggestion and the first electrical stimulation is provided at a first timing interval, and wherein the UI component is further configured to display a second suggestion in the UI to provide the second electrical stimulation at a second timing interval, the second timing interval being different than the first timing interval. 
     AG. The system of clause AE or AF, wherein the capture component is configured to determine the likelihood by: inputting the data associated with the biological parameter into a machine-learned model trained to identify heart capture; and receiving, from the machine-learned model, the likelihood that the first electrical stimulation has caused the capture of the heart of the patient. 
     AH. A system including: a pacing component implemented at least partially in hardware of an external pacing device and configured to provide, at a first time, a first electrical stimulation to an external surface of a patient, a first electrical stimulation being at a first current level; a sensor analysis component implemented at least partially in hardware of the external pacing device and configured to receive, from a biological sensor at a second time after the first time, a first value associated with a biological parameter of the patient, wherein the pacing component is further configured to provide a second electrical stimulation to the external surface of the patient at a third time after the second time, the second electrical stimulation being at the first current level, and wherein the sensor analysis component is further configured to receive, from the biological sensor at a fourth time after the third time, a second value associated with the biological parameter of the patient; and a capture component implemented at least partially in hardware of the external pacing device and configured to: determine a difference between the first value and the second value, compare the difference to a threshold difference, and responsive to determining that the difference is greater than or equal to the threshold difference, cause the pacing component to provide a third electrical stimulation at a second current level, the second current level being different than the first current level. 
     AI. The system of clause AH, wherein the difference is a first difference, and wherein: the pacing component is further configured to provide the third electrical stimulation at a fifth time after the fourth time, the sensor analysis component is further configured to receive, from the biological sensor at a sixth time after the fifth time, a third value associated with the biological parameter of the patient, the capture component is further configured to: determine a second difference between the second value and the third value, compare the second difference to the threshold difference, and responsive to determining that the second difference is greater than or equal to the threshold difference, cause the pacing component to provide a fourth electrical stimulation at a third current level, the third current level being different than the first current level and different than the second current level. 
     AJ. The system of clause AH or AI, wherein the biological parameter includes an electrocardiogram (ECG) pulse, the first value corresponds to a first magnitude of the ECG pulse at the second time, and the second value corresponds to a second magnitude of the ECG pulse at the fourth time. 
     While the example clauses described above are described with respect to one particular implementation, it should be understood that, in the context of this document, the content of the example clauses can also be implemented via a method, device, system, computer-readable medium, and/or another implementation. Additionally, any one of examples A-AJ may be implemented alone or in combination with any other one or more of the examples A-AJ. 
     CONCLUSION 
     The features disclosed in the foregoing description, or the following claims, or the accompanying drawings, expressed in their specific forms or in terms of a means for performing the disclosed function, or a method or process for attaining the disclosed result, as appropriate, may, separately, or in any combination of such features, be used for realizing implementations of the disclosure in diverse forms thereof. 
     As will be understood by one of ordinary skill in the art, each implementation disclosed herein can comprise, consist essentially of or consist of its particular stated element, step, or component. Thus, the terms “include” or “including” should be interpreted to recite: “comprise, consist of, or consist essentially of.” The transition term “comprise” or “comprises” means has, but is not limited to, and allows for the inclusion of unspecified elements, steps, ingredients, or components, even in major amounts. The transitional phrase “consisting of” excludes any element, step, ingredient or component not specified. The transition phrase “consisting essentially of” limits the scope of the implementation to the specified elements, steps, ingredients or components and to those that do not materially affect the implementation. As used herein, the term “based on” is equivalent to “based at least partly on,” unless otherwise specified. 
     Unless otherwise indicated, all numbers expressing quantities, properties, conditions, and so forth used in the specification and claims are to be understood as being modified in all instances by the term “about.” Accordingly, unless indicated to the contrary, the numerical parameters set forth in the specification and attached claims are approximations that may vary depending upon the desired properties sought to be obtained by the present disclosure. At the very least, and not as an attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical parameter should at least be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. When further clarity is required, the term “about” has the meaning reasonably ascribed to it by a person skilled in the art when used in conjunction with a stated numerical value or range, i.e. denoting somewhat more or somewhat less than the stated value or range, to within a range of ±20% of the stated value; 19% of the stated value; 18% of the stated value; 17% of the stated value; ±16% of the stated value; 15% of the stated value; 14% of the stated value; 13% of the stated value; 12% of the stated value; 11% of the stated value; 10% of the stated value; 9% of the stated value; ±8% of the stated value; 7% of the stated value; 6% of the stated value; 5% of the stated value; 4% of the stated value; 3% of the stated value; 2% of the stated value; or ±1% of the stated value. 
     Notwithstanding that the numerical ranges and parameters setting forth the broad scope of the disclosure are approximations, the numerical values set forth in the specific examples are reported as precisely as possible. Any numerical value, however, inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements. 
     The terms “a,” “an,” “the” and similar referents used in the context of describing implementations (especially in the context of the following claims) are to be construed to cover both the singular and the plural, unless otherwise indicated herein or clearly contradicted by context. Recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g., “such as”) provided herein is intended merely to better illuminate implementations of the disclosure and does not pose a limitation on the scope of the disclosure. No language in the specification should be construed as indicating any non-claimed element essential to the practice of implementations of the disclosure. 
     Groupings of alternative elements or implementations disclosed herein are not to be construed as limitations. Each group member may be referred to and claimed individually or in any combination with other members of the group or other elements found herein. It is anticipated that one or more members of a group may be included in, or deleted from, a group for reasons of convenience and/or patentability. When any such inclusion or deletion occurs, the specification is deemed to contain the group as modified thus fulfilling the written description of all Markush groups used in the appended claims. 
     Certain implementations are described herein, including the best mode known to the inventors for carrying out implementations of the disclosure. Of course, variations on these described implementations will become apparent to those of ordinary skill in the art upon reading the foregoing description. The inventors expect skilled artisans to employ such variations as appropriate, and the inventors intend for implementations to be practiced otherwise than specifically described herein. Accordingly, the scope of this disclosure includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described elements in all possible variations thereof is encompassed by implementations of the disclosure unless otherwise indicated herein or otherwise clearly contradicted by context.