Patent Publication Number: US-2021187312-A1

Title: Wearable cardioverter defibrillator (wcd) with power-saving function

Description:
CROSS REFERENCES TO RELATED PATENT APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 15/715,550, filed on Sep. 26, 2017, which claims the benefit of U.S. Provisional Patent Application Ser. No. 62/404,158, filed on Oct. 4, 2016, the entire disclosures of which, as initially made, are hereby incorporated by reference. 
    
    
     BACKGROUND 
     When people suffer from some types of heart arrhythmias, the result may be that blood flow to various parts of the body is reduced. Some arrhythmias may even result in a Sudden Cardiac Arrest (SCA). SCA can lead to death very quickly, e.g. within 10 minutes, unless treated in the interim. 
     Some people have an increased risk of SCA. People at a higher risk include patients who have had a heart attack, or a prior SCA episode. A frequent recommendation is for these people to receive an Implantable Cardioverter Defibrillator (ICD). The ICD is surgically implanted in the chest, and continuously monitors the patient&#39;s electrocardiogram (ECG). If certain types of heart arrhythmias are detected, then the ICD delivers an electric shock through the heart. 
     After being identified as having an increased risk of an SCA, and before receiving an ICD, these people are sometimes given a Wearable Cardioverter Defibrillator (WCD) system. (Early versions of such systems were called wearable cardiac defibrillator systems.) A WCD system typically includes a harness, vest, or other garment that the patient is to wear. The WCD system further includes electronic components, such as a defibrillator and electrodes, coupled to the harness, vest, or other garment. When the patient wears the WCD system, the external electrodes may then make good electrical contact with the patient&#39;s skin, and therefore can help determine the patient&#39;s ECG. If a shockable heart arrhythmia is detected, then the defibrillator delivers the appropriate electric shock through the patient&#39;s body, and thus through the heart. 
     To detect a shockable arrhythmia, a WCD system may perform computations on the patient&#39;s ECG signal. Typically, the more intensive the computations, the more reliable the detection result will be. Rhythm analysis algorithms can be computationally burdensome. For example, an algorithm proposed by Irusta et al. (A high-temporal resolution algorithm to discriminate shockable from nonshockable rhythms in adults and children, Resuscitation (2012)), involves a number of steps, some of which may include performing a Fast Fourier Transform (FFT) every 3.2 seconds. 
     Computations are not free, however. Computations are performed by machine operations of a processor of the WCD system. These machine operations require electrical current to be performed, and thus tax the stored energy of the battery accordingly. The more computations that are required, the more energy will be required from the battery. And FFTs require a lot of such computations. The more energy that is required from the battery, the more energy the battery needs to store from when it is put into service until it is switched out for recharging. 
     BRIEF SUMMARY 
     The present description gives instances of Wearable Cardioverter Defibrillator (WCD) systems, storage media that store programs, and methods, the use of which may help overcome problems and limitations of the prior art. 
     In embodiments, a WCD system has a processor that performs two different analyses to an ECG of the patient. A first-level analysis can be computationally economical, while a fuller second-level analysis can give shock/no-shock advice with more certainty. In some of these embodiments the second-level analysis of the ECG is performed only if the first-level analysis of the ECG detects a possible shockable condition. As such, the first-level analysis may operate as a gatekeeping function, often preventing the more computationally intensive second-level analysis from being performed. 
     An advantage can be that the WCD system needs to store less electrical charge, for powering the processor. In turn, this permits portions of the WCD system to be less bulky and weigh less. 
     These and other features and advantages of the claimed invention will become more readily apparent in view of the embodiments described and illustrated in the present disclosure, namely from the present written specification and the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram of components of a sample wearable cardioverter defibrillator (WCD) system, made according to embodiments. 
         FIG. 2  is a diagram showing sample components of an external defibrillator, such as the one belonging in the system of  FIG. 1 , made according to embodiments. 
         FIG. 3  is a diagram of sample components of a WCD system in relation to a patient according to embodiments. 
         FIG. 4  is a time diagram of sample first, second and third ECG data of respectively a first, a second and a third portion of a physiological input of the patient, rendered according to embodiments. 
         FIG. 5  is a diagram illustrating that at least two different types of analyses may be performed according to embodiments. 
         FIG. 6  is a conceptual diagram for illustrating how a WCD system can use electrodes to acquire ECG signals along different vectors according to embodiments. 
         FIG. 7  is a diagram indicating that ECG signals acquired along different vectors may be subjected to different types of analyses according to embodiments. 
         FIG. 8  is a time diagram that represents sample detection of a possible shockable condition when an extracted statistic exceeds a threshold, according to embodiments. 
         FIG. 9  is a block diagram of a sample processor of a WCD system according to embodiments, in which the processor includes different computational modules for the different analyses of the ECG data. 
         FIG. 10  is a block diagram of sample components of a chip of a processor of a WCD system according to embodiments, in which the chip can operate at different states depending on whether or not a single computational module is analyzing the ECG data. 
         FIG. 11  is a time diagram showing a sample plot of power consumption over time for a processor of a WCD system according to embodiments. 
         FIG. 12  is a flowchart for illustrating methods according to embodiments. 
     
    
    
     DETAILED DESCRIPTION 
     As has been mentioned, the present description is about Wearable Cardioverter Defibrillator (WCD) systems, storage media that store programs, and methods. Embodiments are now described in more detail. 
     A wearable cardioverter defibrillator (WCD) system made according to embodiments has a number of components. These components can be provided separately as modules that can be interconnected, or can be combined with other components, etc. 
       FIG. 1  depicts a patient  82 . Patient  82  may also be referred to as a person and/or wearer, since that patient wears components of the WCD system. Patient  82  is ambulatory, which means patient  82  can walk around and is not bed-ridden. 
       FIG. 1  also depicts components of a WCD system made according to embodiments. One such component is a support structure  170  that is wearable by patient  82 . It will be understood that support structure  170  is shown only generically in  FIG. 1 , and in fact partly conceptually.  FIG. 1  is provided merely to illustrate concepts about support structure  170 , and is not to be construed as limiting how support structure  170  is implemented, or how it is worn. 
     Support structure  170  can be implemented in many different ways. For example, it can be implemented in a single component or a combination of multiple components. In embodiments, support structure  170  could include a vest, a half-vest, a garment, etc. In such embodiments such items can be worn similarly to parallel articles of clothing. In embodiments, support structure  170  could include a harness, one or more belts or straps, etc. In such embodiments, such items can be worn by around the torso, hips, over the shoulder, etc. In embodiments, support structure  170  can include a container or housing, which can even be waterproof. In such embodiments, the support structure can be worn by being attached to the patient by adhesive material, for example as shown in U.S. Pat. No. 8,024,037. Support structure  170  can even be implemented as described for the support structure of US Pat. App. No. US 2017/0056682 A1, which is incorporated herein by reference. Of course, in such embodiments, the person skilled in the art will recognize that additional components of the WCD system can be in the housing of a support structure instead of attached externally to the support structure, for example as described in the 2017/0056682 document. There can be other examples. 
     A WCD system according to embodiments is configured to defibrillate a patient who is wearing it, by delivering an electrical charge to the patient&#39;s body in the form of an electric shock delivered in one or more pulses.  FIG. 1  shows a sample external defibrillator  100 , and sample defibrillation electrodes  104 ,  108 , which are coupled to external defibrillator  100  via electrode leads  105 . Defibrillator  100  and defibrillation electrodes  104 ,  108  can be coupled to support structure  170 . As such, many of the components of defibrillator  100  could be therefore coupled to support structure  170 . When defibrillation electrodes  104 ,  108  make good electrical contact with the body of patient  82 , defibrillator  100  can administer, via electrodes  104 ,  108 , a brief, strong electric pulse  111  through the body. Pulse  111 , also known as shock, defibrillation shock, therapy or therapy shock, is intended to go through and restart heart  85 , in an effort to save the life of patient  82 . Pulse  111  can further include one or more pacing pulses, and so on. 
     A prior art defibrillator typically decides whether to defibrillate or not based on an ECG signal of the patient. However, external defibrillator  100  may initiate defibrillation (or hold-off defibrillation) based on a variety of inputs, with ECG merely being one of them. 
     Accordingly, it will be appreciated that signals such as physiological signals containing physiological data are obtained from patient  82 . While the patient may be considered also a “user” of the WCD system, this is not a requirement. That is, for example, a user of the wearable cardioverter defibrillator (WCD) may include a clinician such as a doctor, nurse, emergency medical technician (EMT) or other similarly situated individual (or group of individuals). The particular context of these and other related terms within this description should be interpreted accordingly. 
     The WCD system may optionally include an outside monitoring device  180 . Device  180  is called an “outside” device because it could be provided as a standalone device, for example not within the housing of defibrillator  100 . Device  180  can be configured to sense or monitor at least one local parameter. A local parameter can be a parameter of patient  82 , or a parameter of the WCD system, or a parameter of the environment, as will be described later in this document. Device  180  may include one or more transducers or sensors that are configured to render one or more physiological inputs from one or more patient parameters that it senses. 
     Optionally, device  180  is physically coupled to support structure  170 . In addition, device  180  can be communicatively coupled with other components, which are coupled to support structure  170 . Such communication can be implemented by a communication module, as will be deemed applicable by a person skilled in the art in view of this description. 
       FIG. 2  is a diagram showing components of an external defibrillator  200 , made according to embodiments. These components can be, for example, included in external defibrillator  100  of  FIG. 1 . The components shown in  FIG. 2  can be provided in a housing  201 , which may also be referred to as casing  201 . 
     External defibrillator  200  is intended for a patient who would be wearing it, such as patient  82  of  FIG. 1 . Defibrillator  200  may further include a user interface  280  for a user  282 . User  282  can be patient  82 , also known as wearer  82 . Or user  282  can be a local rescuer at the scene, such as a bystander who might offer assistance, or a trained person. Or, user  282  might be a remotely located trained caregiver in communication with the WCD system. 
     User interface  280  can be made in a number of ways. User interface  280  may include output devices, which can be visual, audible or tactile, for communicating to a user by outputting images, sounds or vibrations. Images, sounds, vibrations, and anything that can be perceived by user  282  can also be called human perceptible indications. There are many examples of output devices. For example, an output device can be a light, or a screen to display what is sensed, detected and/or measured, and provide visual feedback to rescuer  282  for their resuscitation attempts, and so on. Another output device can be a speaker, which can be configured to issue voice prompts, beeps, loud alarm sounds to warn bystanders, etc. 
     User interface  280  may further include input devices for receiving inputs from users. Such input devices may additionally include various controls, such as pushbuttons, keyboards, touchscreens, one or more microphones, and so on. An input device can be a cancel switch, which is sometimes called an “I am alive” switch or “live man” switch. In some embodiments, actuating the cancel switch can prevent the impending delivery of a shock. 
     Defibrillator  200  may include an internal monitoring device  281 . Device  281  is called an “internal” device because it is incorporated within housing  201 . Monitoring device  281  can sense or monitor patient parameters such as patient physiological parameters, system parameters and/or environmental parameters, all of which can be called patient data. In other words, internal monitoring device  281  can be complementary or an alternative to outside monitoring device  180  of  FIG. 1 . Allocating which of the parameters are to be monitored by which monitoring device can be done according to design considerations. Device  281  may include one or more transducers or sensors that are configured to render one or more physiological inputs from one or more patient parameters that it senses. 
     Patient parameters may include patient physiological parameters. Patient physiological parameters may include, for example and without limitation, those physiological parameters that can be of any help in detecting by the wearable defibrillation system whether the patient is in need of a shock, plus optionally their medical history and/or event history. Examples of such parameters include the patient&#39;s ECG, blood oxygen level, blood flow, blood pressure, blood perfusion, pulsatile change in light transmission or reflection properties of perfused tissue, heart sounds, heart wall motion, breathing sounds and pulse. Accordingly, monitoring devices  180 ,  281  may include one or more sensors configured to acquire patient physiological signals. Examples of such sensors or transducers include electrodes to detect ECG data, a perfusion sensor, a pulse oximeter, a device for detecting blood flow (e.g. a Doppler device), a sensor for detecting blood pressure (e.g. a cuff), an optical sensor, illumination detectors and sensors perhaps working together with light sources for detecting color change in tissue, a motion sensor, a device that can detect heart wall movement, a sound sensor, a device with a microphone, an SpO 2  sensor, and so on. In view of this disclosure, it will be appreciated that such sensors can help detect the patient&#39;s pulse, and can therefore also be called pulse detection sensors, pulse sensors, and pulse rate sensors. Pulse detection is also taught at least in Physic-Control&#39;s U.S. Pat. No. 8,135,462, which is hereby incorporated by reference in its entirety. In addition, a person skilled in the art may implement other ways of performing pulse detection. In such cases, the transducer includes an appropriate sensor, and the physiological input is a measurement by the sensor of that patient parameter. For example, the appropriate sensor for a heart sound may include a microphone, etc. 
     In some embodiments, the local parameter is a trend that can be detected in a monitored physiological parameter of patient  282 . A trend can be detected by comparing values of parameters at different times. Parameters whose detected trends can particularly help a cardiac rehabilitation program include: a) cardiac function (e.g. ejection fraction, stroke volume, cardiac output, etc.); b) heart rate variability at rest or during exercise; c) heart rate profile during exercise and measurement of activity vigor, such as from the profile of an accelerometer signal and informed from adaptive rate pacemaker technology; d) heart rate trending; e) perfusion, such as from SpO 2  or CO 2 ; f) respiratory function, respiratory rate, etc.; g) motion, level of activity; and so on. Once a trend is detected, it can be stored and/or reported via a communication link, along perhaps with a warning. From the report, a physician monitoring the progress of patient  282  will know about a condition that is either not improving or deteriorating. 
     Patient state parameters include recorded aspects of patient  282 , such as motion, posture, whether they have spoken recently plus maybe also what they said, and so on, plus optionally the history of these parameters. Or, one of these monitoring devices could include a location sensor such as a Global Positioning System (GPS) location sensor. Such a sensor can detect the location, plus a speed can be detected as a rate of change of location over time. Many motion detectors output a motion signal that is indicative of the motion of the detector, and thus of the patient&#39;s body. Patient state parameters can be very helpful in narrowing down the determination of whether SCA is indeed taking place. 
     A WCD system made according to embodiments may include a motion detector. In embodiments, a motion detector can be implemented within monitoring device  180  or monitoring device  281 . Such a motion detector can be configured to detect a motion event. In response, the motion detector may render or generate from the detected motion event a motion detection input that can be received by a subsequent device or functionality. A motion event can be defined as is convenient, for example a change in motion from a baseline motion or rest, etc. Such a motion detector can be made in many ways as is known in the art, for example by using an accelerometer. In such cases, the patient parameter is a motion, one of the transducers may include a motion detector, and the physiological input is a motion measurement. 
     System parameters of a WCD system can include system identification, battery status, system date and time, reports of self-testing, records of data entered, records of episodes and intervention, and so on. 
     Environmental parameters can include ambient temperature and pressure. Moreover, a humidity sensor may provide information as to whether it is likely raining. Presumed patient location could also be considered an environmental parameter. The patient location could be presumed if monitoring device  180  or  281  includes a GPS location sensor as per the above. 
     Defibrillator  200  typically includes a defibrillation port  210 , such as a socket in housing  201 . Defibrillation port  210  includes electrical nodes  214 ,  218 . Leads of defibrillation electrodes  204 ,  208 , such as leads  105  of  FIG. 1 , can be plugged into defibrillation port  210 , so as to make electrical contact with nodes  214 ,  218 , respectively. It is also possible that defibrillation electrodes  204 ,  208  are connected continuously to defibrillation port  210 , instead. Either way, defibrillation port  210  can be used for guiding, via electrodes, to the wearer the electrical charge that has been stored in an energy storage module  250  that is described more fully later in this document. The electric charge will be the shock for defibrillation, pacing, and so on. 
     Defibrillator  200  may optionally also have an ECG port  219  in housing  201 , for plugging in sensing electrodes  209 , which are also known as ECG electrodes and ECG leads. It is also possible that sensing electrodes  209  can be connected continuously to ECG port  219 , instead. Sensing electrodes  209  are types of transducers that can help sense an ECG signal, e.g. a 12-lead signal, or a signal from a different number of leads, especially if they make good electrical contact with the body of the patient. Sensing electrodes  209  can be attached to the inside of support structure  170  for making good electrical contact with the patient, similarly as defibrillation electrodes  204 ,  208 . 
     Optionally a WCD system according to embodiments also includes a fluid that it can deploy automatically between the electrodes and the patient&#39;s skin. The fluid can be conductive, such as by including an electrolyte, for making a better electrical contact between the electrode and the skin. Electrically speaking, when the fluid is deployed, the electrical impedance between the electrode and the skin is reduced. Mechanically speaking, the fluid may be in the form of a low-viscosity gel, so that it does not flow away, after it has been deployed. The fluid can be used for both defibrillation electrodes  204 ,  208 , and sensing electrodes  209 . 
     The fluid may be initially stored in a fluid reservoir, not shown in  FIG. 2 , which can be coupled to the support structure. In addition, a WCD system according to embodiments further includes a fluid deploying mechanism  274 . Fluid deploying mechanism  274  can be configured to cause at least some of the fluid to be released from the reservoir, and be deployed near one or both of the patient locations, to which the electrodes are configured to be attached to the patient. In some embodiments, fluid deploying mechanism  274  is activated prior to the electrical discharge responsive to receiving activation signal AS from processor  230  that is described more fully later in this document. 
     In some embodiments, defibrillator  200  also includes a measurement circuit  220 , as one or more of its sensors or transducers. Measurement circuit  220  senses one or more electrical physiological signals of the patient from ECG port  219 , if provided. Even if defibrillator  200  lacks ECG port  219 , measurement circuit  220  can obtain physiological signals through nodes  214 ,  218  instead, when defibrillation electrodes  204 ,  208  are attached to the patient. In these cases, the physiological input reflects an ECG measurement. The parameter can be an ECG, which can be sensed as a voltage difference between electrodes  204 ,  208 . In addition the parameter can be an impedance, which can be sensed between electrodes  204 ,  208  and/or the connections of ECG port  219 . Sensing the impedance can be useful for detecting, among other things, whether these electrodes  204 ,  208  and/or sensing electrodes  209  are not making good electrical contact with the patient&#39;s body. These patient physiological signals can be sensed, when available. Measurement circuit  220  can then render or generate information about them as physiological inputs, data, other signals, etc. More strictly speaking, the information rendered by measurement circuit  220  is output from it, but this information can be called an input because it is received by a subsequent device or functionality as an input. 
     Defibrillator  200  also includes a processor  230 . Processor  230  may be implemented in a number of ways. Such ways include, by way of example and not of limitation, digital and/or analog processors such as microprocessors and Digital Signal Processors (DSPs); controllers such as microcontrollers; software running in a machine; programmable circuits such as Field Programmable Gate Arrays (FPGAs), Field-Programmable Analog Arrays (FPAAs), Programmable Logic Devices (PLDs), Application Specific Integrated Circuits (ASICs), any combination of one or more of these, and so on. 
     The processor  230  may include, or have access to, a non-transitory storage medium, such as memory  238  that is described more fully later in this document. Such a memory can have a non-volatile component for storage of machine-readable and machine-executable instructions. A set of such instructions can also be called a program. The instructions, which may also referred to as “software,” generally provide functionality by performing methods as may be disclosed herein or understood by one skilled in the art in view of the disclosed embodiments. In some embodiments, and as a matter of convention used herein, instances of the software may be referred to as a “module” and by other similar terms. Generally, a module includes a set of the instructions so as to offer or fulfill a particular functionality. Embodiments of modules and the functionality delivered are not limited by the embodiments described in this document. 
     Processor  230  can be considered to have a number of modules. One such module can be a detection module  232 . Detection module  232  can include a Ventricular Fibrillation (VF) detector. The patient&#39;s sensed ECG from measurement circuit  220 , which can be available as physiological inputs, data, or other signals, may be used by the VF detector to determine whether the patient is experiencing VF. Detecting VF is useful, because VF results in SCA. Detection module  232  can also include a Ventricular Tachycardia (VT) detector, and so on. 
     Another such module in processor  230  can be an advice module  234 , which generates advice for what to do. The advice can be based on outputs of detection module  232 . There can be many types of advice according to embodiments. In some embodiments, the advice is a shock/no shock determination that processor  230  can make, for example via advice module  234 . The shock/no shock determination can be made by executing a stored Shock Advisory Algorithm. A Shock Advisory Algorithm can make a shock/no shock determination from one or more ECG signals that are captured according to embodiments, and determining whether a shock criterion is met. This may determine whether a possible or actual shockable condition exists or not. The determination can be made from a rhythm analysis of the captured ECG signal or otherwise. 
     In some embodiments, when the determination is to shock, an electrical charge is delivered to the patient. Delivering the electrical charge is also known as discharging. Shocking can be for defibrillation, pacing, and so on. 
     Processor  230  can further include a timer  239 . Alternately, timer  239  can be provided as a separate module. 
     Processor  230  can include additional modules, such as other module  236 , for other functions. In addition, if internal monitoring device  281  is indeed provided, it may be operated in part by processor  230 , etc. 
     Defibrillator  200  optionally further includes a memory  238 , which can work together with processor  230 . Memory  238  may be implemented in a number of ways. Such ways include, by way of example and not of limitation, volatile memories, Nonvolatile Memories (NVM), Read-Only Memories (ROM), Random Access Memories (RAM), magnetic disk storage media, optical storage media, smart cards, flash memory devices, any combination of these, and so on. Memory  238  is thus a non-transitory storage medium. Memory  238 , if provided, can include programs for processor  230 , which processor  230  may be able to read and execute. More particularly, the programs can include sets of instructions in the form of code, which processor  230  may be able to execute upon reading. Executing is performed by physical manipulations of physical quantities, and may result in functions, operations, processes, actions and/or methods to be performed, and/or the processor to cause other devices or components or blocks to perform such functions, operations, processes, actions and/or methods. The programs can be operational for the inherent needs of processor  230 , and can also include protocols and ways that decisions can be made by advice module  234 . In addition, memory  238  can store prompts for user  282 , if this user is a local rescuer. Moreover, memory  238  can store data. This data can include patient data, system data and environmental data, for example as learned by internal monitoring device  281  and outside monitoring device  180 . The data can be stored in memory  238  before it is transmitted out of defibrillator  200 , or stored there after it is received by defibrillator  200 . 
     Defibrillator  200  may also include a power source  240 . To enable portability of defibrillator  200 , power source  240  typically includes a battery. Such a battery is typically implemented as a battery pack, which can be rechargeable or not. Sometimes a combination is used of rechargeable and non-rechargeable battery packs. Other embodiments of power source  240  can include an AC power override, for where AC power will be available, an energy storage capacitor, and so on. In some embodiments, power source  240  is controlled by processor  230 . Appropriate components may be included to provide for charging or replacing power source  240 . 
     Defibrillator  200  may additionally include an energy storage module  250 . Energy storage module  250  can be coupled to the support structure of the WCD system, for example either directly or via the electrodes and their leads. Module  250  is where some electrical energy can be stored temporarily in the form of an electrical charge, when preparing it for discharge to administer a shock. In embodiments, module  250  can be charged from power source  240  to the desired amount of energy, as controlled by processor  230 . In typical implementations, module  250  includes a capacitor  252 , which can be a single capacitor or a system of capacitors, and so on. In some embodiments, energy storage module  250  includes a device that exhibits high power density, such as an ultracapacitor. As described above, capacitor  252  can store the energy in the form of an electrical charge, for delivering to the patient. 
     Defibrillator  200  moreover includes a discharge circuit  255 . When the decision is to shock, processor  230  can be configured to control discharge circuit  255  to discharge through the patient the electrical charge stored in energy storage module  250 . When so controlled, circuit  255  can permit the energy stored in module  250  to be discharged to nodes  214 ,  218 , and from there also to defibrillation electrodes  204 ,  208 , so as to cause a shock to be delivered to the patient. Circuit  255  can include one or more switches  257 . Switches  257  can be made in a number of ways, such as by an H-bridge, and so on. Circuit  255  can also be controlled via user interface  280 . 
     Defibrillator  200  can optionally include a communication module  290 , for establishing one or more wired or wireless communication links with other devices of other entities, such as a remote assistance center, Emergency Medical Services (EMS), and so on. Module  290  may also include such sub-components as may be deemed necessary by a person skilled in the art, for example an antenna, portions of a processor, supporting electronics, outlet for a telephone or a network cable, etc. This way, data, commands, etc. can be communicated. The data can include patient data, event information, therapy attempted, CPR performance, system data, environmental data, and so on. 
     Defibrillator  200  can optionally include other components. 
     Returning to  FIG. 1 , in embodiments, one or more of the components of the shown WCD system have been customized for patient  82 . This customization may include a number of aspects. For instance, support structure  170  can be fitted to the body of patient  82 . For another instance, baseline physiological parameters of patient  82  can be measured, such as the heart rate of patient  82  while resting, while walking, motion detector outputs while walking, etc. Such baseline physiological parameters can be used to customize the WCD system, in order to make its diagnoses more accurate, since the patients&#39; bodies differ from one another. Of course, such parameters can be stored in a memory of the WCD system, and so on. 
     A programming interface can be made according to embodiments, which receives such measured baseline physiological parameters. Such a programming interface may input automatically in the WCD system the baseline physiological parameters, along with other data. 
     Referring now to  FIG. 3 , in some versions or embodiments, a set of components  302  of a wearable cardioverter defibrillator (WCD), such as those mentioned above, are described in relation to a patient  382 . For example, components  302  include a support structure  370  that is configured to be worn by patient  382 , which can be made as support structure  170 . Components  302  also include a power source  340 , an energy storage module  350  that is configured to receive an electrical charge from power source  340  and to store the received electrical charge, and a discharge circuit  355  coupled to energy storage module  350 , all made as described for power source  240 , energy storage module  250  and discharge circuit  255 , respectively. 
     Components  302  may further include a transducer  322  that can have ECG electrodes such as sensing electrodes  209 . Transducer  322  can be configured to render, from a parameter  303  that is an Electrocardiogram (ECG) of patient  382 , a physiological input  323  that includes ECG data of patient  382 . 
     Components  302  may further include a processor  330 , which can be made as described for processor  230 . Processor  330  can be configured to perform analyses on physiological input  323 , for example as described later in this document in more detail. Depending on the results of these analyses, processor  330  may control discharge circuit  355  to discharge the electrical charge  351  that is stored in energy storage module  350  through patient  382  so as to deliver a shock to patient  382  while support structure  370  is worn by patient  382 . 
     In embodiments, components  302  may perform different types of analyses on physiological input  323 . Examples are now described. 
     Referring to  FIG. 4 , a time diagram  401  is shown, where sample ECG data  423  is plotted against a time axis. A first, a second, and a third portion of the physiological input are identified. In particular, the first portion includes first ECG data  423 _ 1  from a first time segment T 4 _ 1 , the second portion includes second ECG data  423 _ 2  from a second time segment T 4 _ 2 , and the third portion includes third ECG data  423 _ 3  from a third time segment T 4 _ 3 . Such time segments can also be called time intervals, and so on. Moreover, even though these portions of the ECG data are shown in the context of these time segments or intervals, there is no requirement that the ECG data has been stored already in a memory. Nor is there a requirement that the subsequently described analyses  541 ,  542  cannot be running continuously. In fact, such analyses can be running continuously, on ECG data that is running continuously. Nor is there a requirement that such time segments or intervals be defined, between moments in time for example. Rather, time segments or intervals are being used in this document only to provide a common denominator for comparing and contrasting analyses  541 ,  542  in terms of their complexity, intensiveness, the number of their machine operations, their energy consumption, etc. 
     It will be observed that, in this example of  FIG. 4 , the first time segment and the second time segment have equal durations. The third time segment, however, lasts longer than either the first time segment or the second time segment. 
     In addition, in this example of  FIG. 4 , none of the intervals is temporally contiguous with any of the others, although that could well happen. For example, the second time segment could follow immediately after the first time segment, and so on. Moreover, in this example of  FIG. 4 , none of the intervals overlaps any of the others, although that could well happen. For example, the second time segment could overlap with the first time segment at least in part, include all of the first time segment, be identical to it, and so on. 
     Possible analyses, decisions, and other actions by processor  330  are now described in more detail. In some embodiments, processor  330  may be able to perform a first-level analysis on a first portion of the physiological input, to detect whether or not a possible shockable condition exists. The first portion may include first ECG data  423 _ 1 , from first time segment T 4 _ 1 . 
     In addition, processor  330  may be able to perform a second-level analysis on a second portion of the physiological input, to detect whether or not an actual shockable condition exists. The second portion may include second ECG data  423 _ 2 , from second time segment T 4 _ 2 , or third ECG data  423 _ 3 , from third time segment T 4 _ 3 , and so on. It will be further recognized that, if the intervals were to overlap, the first-level analysis and the second-level analysis of the ECG could be of the same ECG data at least in part. 
     Referring now to  FIG. 5 , a set  597  of arrows  598 ,  599  illustrates a choice that at least two different types of analyses  541 ,  542  may be performed by processor  330  according to embodiments. It will be understood that this representation is the same regardless of whether analyses  541 ,  542  are performed by different computational modules or a single one. 
     In  FIG. 5 , solid arrow  598  points to a first-level analysis  541 , which is to be performed to determine whether or not a Possible Shockable Condition (PSC) exists. Or, dotted arrow  599  points to a second-level analysis  542  alternately to first-level analysis  541 . Second-level analysis  542  can be performed to determine whether or not an Actual Shockable Condition (ASC) exists. The actual shockable condition is generally different from the possible shockable condition, although that is not required. 
     In this representation, arrow  598  is solid, to indicate the present choice of set  597  in this example. These choices are thought of in the alternative, but this need not be the case. Both analyses could be running at some time, to compare their results. 
     First-level analysis  541  is different from second-level analysis  542 , in that these analyses may be performed differently, and/or be performed to detect shockable conditions that are different. In some embodiments first-level analysis  541  has a higher sensitivity than second-level analysis  542 . Indeed, first-level analysis  541  can be designed to have a high sensitivity so that there is a very high probability that it will detect any rhythm that might require the patient to be shocked. In addition, in some embodiments, second-level analysis  542  has a higher specificity than first-level analysis  541 . By way of background, in medical diagnosis, test sensitivity is the ability of a test to correctly identify those with a problem, which is also called the true positive rate. On the other hand, test specificity is the ability of the test to correctly identify those without the problem, which is also called the true negative rate. Put another way, if a test is highly sensitive and the test result is negative, one can be nearly certain that they don&#39;t have the problem. A highly sensitive test thus helps rule out the problem, when its result is negative. 
     In embodiments, second-level analysis  542  is more computationally intensive than first-level analysis  541 . This is conceptually hinted at, in this particular single instance of  FIG. 5 , by drawing box  542  as larger than box  541 . Of course, the relative scale of boxes  541  and  542  is not intended to convey how much more computationally simpler process  541  over process  542 , and so on. 
     In embodiments where second-level analysis  542  is more computationally intensive than first-level analysis  541 , the processor consumes more electrical power in performing second-level analysis  542  than first-level analysis  541 . Since power is found by dividing energy over time, in such embodiments performing second-level analysis  542  may require the processor to consume more energy than performing first-level analysis  541 , if the first time segment had an equal duration with the second time segment. As already mentioned previously, this supposition that the first time segment would have an equal duration with the second time segment is made simply so as to equalize the denominators of the consumed energy to arrive at consumed electrical power, and does not require that the ECG data is cast in time intervals as opposed to running continuously, or that these time segments actually have equal durations. 
     For describing the above-mentioned computationally intensiveness or its opposite (simplicity), a computational statistic may be considered. The computational statistic can be the number of machine operations by processor  330  for processing a set of ECG data, divided by the duration during which this set of ECG data was acquired. As such, in embodiments, more machine operations per the duration of the second time segment can be required for performing the second-level analysis, than the machine operations per the duration of the first time segment required for performing the first-level analysis. In another way of saying this, performing the second-level analysis can require more machine operations by processor  330  than performing the first-level analysis, if the first time segment had an equal duration with the second time segment. 
     Embodiments or versions may save on computations, which can save electrical power for the wearable system. Indeed, microprocessor power consumption is related to the number of computations required. Moreover, a microprocessor that is used only lightly, i.e. for fewer computations, can be clocked at a slower rate to further reduce power consumption. Or, for intermittent computations according to embodiments, such a microprocessor can be put to sleep in a low-power state the majority of the time and woken up only when there are computations to be done. In embodiments, the computations are completed quickly, and the microprocessor spends most of its time in a dormant state. It is understood that, in this disclosure, words like dormant may connote pauses in activity that are long, or much shorter than are typically associated with chip states, etc. 
     In some embodiments, discharge circuit  355  is controlled to discharge stored electrical charge  351  through the patient responsive to thus detecting that the possible shockable condition exists or that the actual shockable condition exists. Some embodiments can be even more sophisticated, as will be seen later in this document. 
     In embodiments, second-level analysis  542  may provide analyses of higher certainty than first-level analysis  541 . In fact, this can be supported by second-level analysis  542  being more computationally intensive than first-level analysis  541 . 
     In some embodiments, first-level analysis  541  is running routinely, while second-level analysis  542  is running only occasionally, or when triggered. The preference for running first-level analysis  541  over second-level analysis  542  over the long term may conserve power. 
     Triggering may take place as a result of an outcome of the first-level analysis. Alternately, triggering may take place from a different kind of event, such as a checking input being received upon being generated, regardless of whether or not the first-level analysis was being performed at the time, or what its outcome is. Examples of such triggering are now described, and it will be understood that these examples are not mutually exclusive. 
     In some embodiments, second-level analysis  542  is performed responsive to a checking input  586  being received, for example by processor  330 . In  FIG. 5 , arrow  587  is drawn to suggest that checking input  586  triggers the performance of second-level analysis  542 . A number of possible devices  584  can generate checking input  586  according to arrow  585 . For one example, device  584  can be a motion detector that is configured to generate checking input  586  responsive to a motion of the patient that is detected by the motion detector. This could be generated, for instance, upon detecting that the previously moving patient has suddenly stopped moving. 
     For another example, device  584  can be a timer  239  configured to generate checking input  586  at a preset time. The preset time can be programmed to be any suitable time. For instance, the preset time is such that the checking input is generated at substantially periodic time segments, e.g. such as every 30 min, 10 min, 1 min, 20 sec, etc. Or, the preset time is when a predefined time period has elapsed during which the second-level analysis has not been performed. 
     In some embodiments, device  584  can be a leads-off module. The leads-off module may be configured to detect when one or more of the electrodes have lost contact with patient  82 , and to generate checking input  586  responsive to so detecting. 
     In some embodiments, device  584  can be a noise detector that is configured to detect when there is a certain amount of electrical noise, for example in an ECG signal, in a detected impedance, and so on. In such embodiments, the noise detector can be configured to generate checking input  586  responsive to so detecting. 
     In some embodiments checking input  586  can be generated if a condition is sustained for a predetermined duration. Such a condition can be as mentioned in this document, for example VT, VF, SVT (Supraventricular Tachycardia), bradycardia, asystole, noise, leas off, or other. 
     In some embodiments, first-level analysis  541  is performed, and second-level analysis  542  is further performed responsive detecting, by first-level analysis  541 , that the possible shockable condition exists. This is indicated in  FIG. 5  by arrow  547 . In such embodiments it can be said that first-level analysis  541  performs a function of gatekeeping, or functions as a gatekeeper. The gatekeeping function results in power savings from not having to process as much, where deemed as not needed. In such embodiments, the discharge circuit can be controlled to thus discharge the stored electrical charge only responsive to detecting that the actual shockable condition exists, but not simply if the possible shockable condition exists. 
     Of course, all previously mentioned combinations are possible. In this case, second-level analysis  542  will be performed after first-level analysis  541 . Analysis  542  can be performed on subsequent ECG data, or even on the same ECG data as analysis  541 , for example if the ECG data has been stored and so on. 
     If an actual shocking condition is not detected to exist by second-level analysis  542 , a number of operations may be performed afterwards. For example first-level analysis  541  may be repeated, and then repeated again, and so on, so as not to delay any VT/VF detection time. It is also possible to perform neither analysis for a preset pause time, to further save power. Again, in a number of embodiments, so as not to delay any VT/VF detection time, if any such pauses of first-level analysis  541  are indeed performed, they are preferably of a short duration so they are not clinically significant in the context of the overall detection—unless other detection provisions have been made. 
     Various ways of establishing such gatekeeping functions are described in this document. In general, it is preferred that the gatekeeper is designed to be computationally simple so that it can run on a low-power microcontroller. 
     One way to implement a gatekeeper that is computationally simple is to have it process a single ECG channel or vector. While a WCD system according to embodiments may be able to acquire data simultaneously from multiple ECG channels, the gatekeeper may process data from only one channel, or a reduced number of channels, so that it can execute first-level analysis  541  on a small, low-power microcontroller. Second-level analysis  542 , however, can use more channels to achieve a more reliable rhythm analysis, even at the expense of computational complexity. An example is now described. 
       FIG. 6  is a conceptual diagram for illustrating how electrodes of a WCD system may capture ECG signals along different channels or vectors according to embodiments. A section of the torso of a patient  682  is shown. Patient  682  has heart  685 . There are four electrodes  604 ,  606 ,  607 ,  608 , attached to the torso. Any pair of these four electrodes may define a vector or channel, across with an ECG signal may be measured. The four electrodes  604 ,  606 ,  607 ,  608  therefore can define six vectors, across which six respective ECG signals  611 ,  612 ,  613 ,  614 ,  615 ,  616  can be captured. In  FIG. 6  it will be understood that electrodes  604 ,  606 ,  607 ,  608  are drawn on the same plane for simplicity, while that is not necessarily the case. Accordingly, the vectors of ECG signals  611 ,  612 ,  613 ,  614 ,  615 ,  616  are not necessarily on the plane of the diagram, either. 
       FIG. 7  is a diagram indicating that ECG signals acquired along different vectors, such as by the configuration of  FIG. 6 , may be subjected to different types of analyses according to embodiments. A first-level analysis  741  may include analyzing the ECG data of a first number of the ECG channels. Here, first-level analysis  741  includes analyzing ECG Data A  711  of a single channel. In other words, that first number of the ECG channels is just one. 
     A second-level analysis  742  may include analyzing the ECG data of a second number of the ECG channels that is larger than that first number. Here, second-level analysis  742  includes analyzing ECG Data B  712 , . . . , ECG Data N  716  of multiple channels. In fact, in embodiments, second-level analysis  742  may further include analyzing ECG Data A  711  of the earlier-mentioned channel. 
     In some embodiments, the first level analysis is from only one of the ECG channels, which has been designated as the best available channel. In particular, the ECG data can be acquired from at least a first and a second distinct ECG channels. As some time, the first ECG channel can be designated as the best ECG channel, and the first-level analysis may include analyzing the ECG data of only the ECG channel that has been thus designated as the best ECG channel, in other words of only the first channel. Responsive to the second-level analysis, the second ECG channel may later become designated as the best ECG channel, in other words, the second ECG channel may be deemed to be providing more reliable data. After the second-level analysis is performed, the first-level analysis can be performed again, and it may include analyzing the ECG data of only the ECG channel that has been thus designated as the best ECG channel. In this latter case, however, the “best channel” designation has shifted to the second channel in this example. 
     In some embodiments, the first-level analysis includes extracting a numerical statistic from the first ECG data. In such embodiments, the possible shockable condition is detected if a value of the statistic is beyond a threshold value TH, either by exceeding the threshold value TH or by being lower than the threshold value TH. It will be understood that, and as will be seen in more detail below, for the specific case of tachycardia detection, the numerical statistic would be derived from a detected heart rate, and would exceed a high threshold. Moreover, the numerical statistic that represents the heart rate might need to be lower than a low threshold in some instances. Examples are now described. 
       FIG. 8  is a time diagram  802 . The value of the extracted statistic is plotted on the vertical axis against a time axis. The plot is a line  803  that starts at time TO, at which time line  803  has a value less than that of a threshold value TH. At time TD, however, line  803  exceeds threshold value TH, which means detection. A number of values can be used as the extracted statistic. 
     When the first-level analysis is used as a gatekeeping function, it does not necessarily require a high specificity. This is because the subsequent second-level analysis can be made more reliable, by performing a full rhythm analysis before a final shock decision is made. Of course, if the first-level gatekeeper is not to have a high specificity, there will likely be instances where the gatekeeper flags a non-shockable rhythm as being potentially shockable, and the subsequent full second-level analysis would discern correctly that the patient does not need to be shocked. Those cases can be considered as internal false alarms within the WCD system. These are to be distinguished from false alarms where the WCD system is preparing to shock the patient, unless the latter acts to prevent it. Rather, in cases of those internal false alarms, the patient need not become alarmed or even notified for that matter. Even if the patient is notified, that can be done in a context of an assurance. 
     In embodiments, the extracted statistic of  FIG. 8  is a detected heart rate. When the first-level analysis is used as a gatekeeping function, then the gatekeeper can simply be a heart rate detector. 
     In some embodiments, the heart rate detector detects when the heart rate is too high. The gatekeeper could flag a rhythm as being potentially shockable if the detected heart rate exceeds a threshold value TH; for such an example the value of TH could equal 135 BPM+/−10%. BPM is a frequency measurement for the heart rate, standing for “beats” per minute. Shockable rhythms, such as ventricular fibrillation (VF) and high-rate ventricular tachycardia (VT), both exhibit a heart rate greater than 135 BPM. Patients wearing a WCD system who do not need a defibrillation shock would not normally have a heart rate greater than 135 BPM. 
     It is possible that some non-shockable rhythms might occasionally have a heart rate higher than 135 BPM. For example, supraventricular tachycardia (SVT) can occasionally exceed 135 BPM and it should not be shocked. It is also possible that noise might cause the heart rate detector to erroneously measure a heart rate &gt;135 BPM when the actual heart rate is lower. Both of these situations can be accommodated by the WCD system according to embodiments because, in some of these embodiments, the full rhythm analysis algorithm has the ability to distinguish noise and SVT from a shockable rhythm. As long as the gatekeeper does not detect a heart rate greater than 135 BPM very often, then a substantial power savings can be achieved, while the patient may be continuously monitored so that any shockable rhythms are detected. 
     In other embodiments, the heart rate detector detects when the heart rate is too low. For example, it might be desirable to detect bradycardia, even though it is not shockable. A bradycardia condition can be detected if a value of the heart rate is less than a threshold value TH of 40 BPM+1-10%. Other provisions can be made for detecting asystole. 
     Still referring to  FIG. 8 , in some embodiments, the processor is configured to set or adjust the value TH of the threshold adaptively, so as to individualize the WCD for the patient. There are discrepancies among patients, both clinical and in terms of their daily activities. Indeed, patients are not alike, their daily activities are not alike, and their physiological responses to their daily activities are not uniform. As such, the same settings might cause the possible shockable condition PSC to be detected more often in some patients than others. If there are too many internal false alarms, it may be beneficial to raise the threshold. A young patient who is likely to tolerate a high heart rate could also benefit from a higher threshold. On the other hand, an older, medically fragile patient may benefit from a lower threshold to ensure that no tachyarrhythmias are missed. 
     As such, the value TH of the threshold may set initially, and then adjusted in a number of ways. One such way is according to how often the possible shockable condition PSC is detected. In embodiments where arrow  547  is implemented, this may further set according to how often the more computationally intensive second-level analysis is performed. Depending on the purpose of the adjustment, there are different examples of how the value TH of the threshold can be set or adjusted. 
     Some examples account for an initial setting, and proceed with adjusting. The gatekeeper could begin with a relatively low threshold, thereby triggering a full analysis relatively often. After repeated full analyses yield a no-shock result at, say, 140 BPM, the WCD system might conclude that it is safe to increase the threshold value to 150 BPM. In this scheme an upper threshold limit of perhaps 180 BPM would be set to prevent the possibility of missing a dangerous arrhythmia. Conversely, if the threshold is set at 150 BPM and the patient never reaches that rate, the device may conclude that it is safe to decrease the threshold value. 
     In some embodiments, the threshold value can be set such that the possible shockable condition is detected on an expected number of occasions per day. To achieve a specific number of full analyses per day the WCD system can track the patient&#39;s heart rate over time. Over that time, the WCD system can develop an estimate of the distribution of the patient&#39;s heart rate in a typical day. This distribution could be used to set a heart rate threshold at a value that can be calculated to trigger approximately one full analysis per hour. A full analysis would still be triggered by the gatekeeper based on the patient&#39;s heart rate, as described hereinabove, but the heart rate threshold would be adjusted so that the desired number of full analyses is performed per day. Executing a full analysis approximately periodically may provide extra reassurance that a lethal arrhythmia has not been overlooked. The period may be a suitable amount of time, e.g. once every minute. 
     Other examples account for challenging situations that may be encountered. For instance, the power source may include a battery, and the threshold value can be set based on a charge level of the battery. As such, perhaps a higher threshold will cause fewer computation-intensive and power-consuming second-level analyses to be performed, so as to conserve battery power. This approach may slightly raise the risk of missing an important arrhythmia, but that may be better than letting the battery run dead with consequent total failure of the WCD system. 
     In some embodiments, the threshold value is set depending on one or more results of the second-level analysis. For instance, the threshold value can be set based on a number of actual shockable conditions detected by a plurality of iterations of the second-level analysis. Moreover, the full, second-level analysis may be able to measure more characteristics than just a shock/no shock conclusion, and diagnose a patient condition. For example, the full analysis may have the additional ability to: distinguish cardiac signals from noise, to distinguish supraventricular rhythms from ventricular rhythms, and to measure the duration of self-terminating arrhythmias. For example, if a non-sustained run of VT is detected (which is very dangerous for the patient), the gatekeeper threshold value might be lowered to provide increased vigilance. On the other hand, if the patient is prone to supraventricular tachycardia (which has a high rate but is relatively benign), the threshold value might be raised to avoid consuming too much power. If the gatekeeper is tripped due to noise, the threshold value might also be raised. 
     As seen above, the defibrillator of  FIG. 2  includes memory  238 . In fact, a WCD system may include one or more memories. Ordinarily the ECG data streaming from the transducer, which can be the electrodes, is first stored in one of the memories, and then it is analyzed. In some embodiments, the gatekeeper may operate on continuously streaming digital data of the ECG, only in a single direction. In some embodiments, the first-level analysis can be performed on the first ECG data as the first ECG data is streaming from the transducer, and without the streaming first ECG data having been stored in any of the one or more memories. In contrast, ECG data can be saved for the full analysis, and the saved ECG data can be partitioned into segments for analysis. Segmental analysis can be beneficial because the saved ECG data can be analyzed forwards and/or backwards, whereas continuously streaming data can only be processed in one direction. In addition, the full second-level analysis can make as multiple passes through each segment of ECG data as necessary, whereas continuously streaming data can only be handled in a single pass. An example of a multiple pass algorithm to be used in the full analysis might be a QRS detector that first finds all of the ECG peaks in a segment of ECG data, then sorts the ECG peaks by amplitude, and retains all of the peaks that are greater than 25% of the maximum amplitude (&gt;0.25 A max ). As such, having the gatekeeper operate on continuously streaming digital data of the ECG may reduce memory requirements. 
     The gatekeeping function could also be based on functions other than heart rate. For example, and as mentioned above, in some embodiments a WCD system can further include a detector configured to generate a detector signal. Many possible detectors are described above, such as a motion detector, detector of patient physiological conditions, detector of environmental conditions, a timer, and so one. In such embodiments, the first-level analysis may include analyzing ECG data, while the second-level analysis includes analyzing ECG data and the detector signal. 
     Another possible gatekeeping function might be the bWT function described by Irusta. This function yields a low value for signals with tall, narrow QRS complexes (which do not need to be shocked), and a higher value for signals with wide, fast QRS complexes like VT and VF (which do need to be shocked). The gatekeeper could also use an RMS measurement, a Peak-Peak measurement or other parameter as part of its initial rhythm assessment. 
     The gatekeeping function may also include an assessment of the patient activity level. This assessment could be made directly based on an accelerometer signal (to detect movement) or it could be based on a measurement that indirectly indicates patient motion, such as an impedance waveform measurement or a common mode voltage measurement. The gatekeeper may be able to reduce how often it falsely triggers a full analysis by taking into account patient activity. A patient who is moving under their own accord generally does not require a defibrillation shock. 
     The gatekeeping function could also include a combination of functions, such as a linear combination of heart rate and bWT. Such an algorithm might have more discriminating power than a single function alone, invoking a full analysis less often. On the other hand, a more complicated (and more discriminating) gatekeeper may cause the low-power microcontroller to consume more power. 
     The gatekeeper might also detect whether an electrode or electrode lead has become disconnected from the patient. Although this is not a potentially shockable event, the patient does need to be alerted so that they can reconnect the electrode/lead. The main processor would have the task of giving an audible and/or visual alert to the patient to let them know that corrective action is needed. 
     In some embodiments, the processor includes different computational modules for the different analyses of the ECG data. An example is now described. 
       FIG. 9  shows a processor  930 , which could be processor  230 ,  330 , etc. Processor  930  includes a first computational module  931 , which is configured to perform a first-level analysis  941 . First-level analysis  941  can be as described above for first-level analysis  541 . Processor  930  also includes a second computational module  932 , which can be configured to perform a second-level analysis  942 . Second-level analysis  942  can be as described above for second-level analysis  542 . 
     Second computational module  932  can be distinct from first computational module  931 . For example, first computational module  931  and second computational module  932  could be implemented in distinct cores of a multi-core processor. In such embodiments, the multi-core processor can be implemented by a single chip. 
     For another example, first computational module  931  and second computational module  932  could be implemented in distinct chips. In particular, first computational module  931  can be implemented by a first chip. The low-power microcontroller has sufficient bandwidth to perform an initial gatekeeping function. 
     In addition, second computational module  932  can be implemented by a second chip that is distinct from the first chip. This second chip can be thought of as the main microprocessor. A good candidate can be a processor with high computational bandwidth, even if not very power efficient. That is because, in some embodiments, this second chip is woken up only when the gatekeeper detects a possible shockable condition, such as a potentially shockable rhythm. A benefit of thinking this second chip as the main microprocessor is that, in some embodiments, many of its other tasks will not be performed while the WCD system is performing only the first-level analysis. 
     In embodiments, second computational module  932  is not performing second-level analysis  942  at a time when first computational module  931  is performing first-level analysis  941 . Advantageously, at such times second computational module  932  may be in a dormant state, such as standby or OFF, which results in power consumption that is substantially reduced or nil. Second computational module  932  can be, however, in an awake state that is distinct than the dormant state when second computational module  932  is performing second-level analysis  942 . 
     First computational module  931  can be made to have sufficient bandwidth to perform the gatekeeping function. Second computational module  932  can be woken up when triggered for second-level analysis  942 . Examples of that were described above at least with reference to  FIG. 5 . 
     In such embodiments of separate chips, in order to optimize overall power consumption, more or less complexity can be allocated between the first-level analysis of the gatekeeping function and the second-level analysis. A more complicated gatekeeper will consume more power in the low-power microcontroller, but it may wake up the main processor less often. 
     In other embodiments, the processor has a chip that includes a single computational module for performing the different analyses of the ECG data. An example is now described, where the gatekeeping function runs in a processor that could be the main microprocessor. 
       FIG. 10  shows a chip  1031  that can include an integrated circuit (IC). Chip  1031  is part of a processor  1030 , which could be as described for processor  230 ,  330 , etc. Chip  1031  includes, among other components, a single computational module  1032 . In some embodiments, computational module  1032  can be considered to be the same as, coextensive with, chip  1031  and in fact the entire processor  1030 . 
     A set  1097  of arrows  1998 ,  1099  illustrates a choice that at chip  1031  can be in different states. In this representation, arrow  1098  is solid, to indicate the present choice of set  1097  in this example. Computational module  1032  can be configured to operate in an awake state  1058 , when computational module  1032  performs either a first-level analysis  1041  or a second-level analysis  1042 . First-level analysis  1041  and second-level analysis  1042  can be as described above for first-level analysis  541  and second-level analysis  542  respectively. When in awake state  1058 , computational module  1032  may be drawing different amounts of power depending on which analysis it is performing. 
     Or, as indicated by a dotted arrow  1099 , computational module  1032  can be configured to operate in a dormant state  1054  when computational module  1032  performs neither first-level analysis  1041  nor second-level analysis  1042 . Dormant state  1054  is different from awake state  1058 . Dormant state  1054  can be a standby state, an OFF state, and so on. Of course, and as mentioned above, the WCD system can pause this way from operating at least first-level analysis  1041  only judiciously. Indeed, pausing first-level analysis  1041  could delay detecting a tachycardia. 
     Chip  1031  consumes a high amount of power when computational module  1032  operates in awake state  1058 , while it consumes a low amount of power when in dormant state  1054 . The low amount of power is lesser than the high amount of power, which results in energy savings. Plus, while in awake state  1058 , chip  1031  can be expending more power for performing analysis  1042  than analysis  1041 . One reason can be a higher clock speed, because the calculations are more. 
     Computational module  1032  can be further configured to transition between awake state  1058  and dormant state  1054 , and back again. For example, computational module  1032  may transition from awake state  1058  to dormant state  1054  according to an arrow  1064 . This transition may be responsive to the possible shockable condition or the actual shockable condition not being detected, plus other factors such as passage of time, this having happened multiple times, and so on. 
     In addition, computational module  1032  may transition from dormant state  1054  to awake state  1058  according to an arrow  1068 . This transition may be responsive to a wake-up input  1086  received according to an arrow  1087 . What was written previously about checking input  586  may be applied also for creating wake-up input  1086 , similarly or analogously. For example, a motion detector can be configured to generate wake-up input  1086  responsive to a motion of the patient that is detected by the motion detector, and so on. 
     For another example, a timer can be configured to generate wake-up input  1086  at a preset time. For instance, the preset time can be such that the wake-up input is generated at substantially periodic time segments, for example 3 times per hour. Or, the preset time can be when a predefined time period has elapsed during which computational module  1032  has been operating in dormant state  1054 . 
     It will be appreciated that combinations of the above embodiments are also possible. For example, in the embodiment of  FIG. 9 , both computational modules may be put to a dormant state, with module  931  performing first-level analysis  941  only occasionally, and module  932  performing second-level analysis  942  even less frequently, except as other planning dictates for various conditions, some of which have already been discussed. 
     In some embodiments, the processor has a clock speed. That clock speed can be faster when second-level analysis  542  is performed than when first-level analysis  541  is performed. The higher clock speed can accommodate the more operations needed, and can result in more power being consumed. It will be recognized that this higher clock speed can be implemented in embodiments described above. 
     An operational example is now described, for showing many possible embodiments. 
       FIG. 11  is a diagram that shows a sample plot  1103  of power consumed over time for a processor of a WCD system according to embodiments. It will be appreciated that plot  1103  is possible in various embodiments, for example where one chip or two separate chips are used for the computational modules, and so on. 
     In  FIG. 11 , the processor consumes power PO when none of the analyses are performed, power P 1  when only the first-level analysis is being performed, and power P 2  when the second-level analysis is being performed. Power P 2  is larger than power P 1 , but the diagram is not to scale. Moreover, in this example there are long pauses where power PO is consumed. In some embodiments these pauses are short. In other embodiments, there are no such pauses and only power P 1  or P 2  is consumed. 
     In  FIG. 11 , the total energy consumed is the area under plot  1103 . It will be appreciated that this is much less than for a processor that performs a full, second-level analysis all the time. In the latter case, the power consumed would be the area under line P 2 . 
     Various times are indicated for plot  1103 . At time T 1 , the processor is in a regular monitoring pattern. In particular, the monitor could be mostly dormant, and only occasionally performing the gatekeeping function. As such, the consumed power occasionally jumps from PO to P 1 , and then back. It will be appreciated that the processor spends a lot less time at P 1  than at PO. 
     At time T 2 , the gatekeeping function has detected a possible shockable condition. As such, a full analysis is performed, which is why the consumed power jumps to P 2 . The full analysis indicates that the actual shockable condition does not exist, which was therefore an internal false alarm. The processor continues the gatekeeping function, and then checks again with a full analysis. Again, the actual shocking condition does not exist. At time T 3 , the processor returns to its regular monitoring pattern, assured that the internal false alarm of T 2  is not a problem. 
     The regular monitoring pattern of time T 3  is interrupted at time T 4  by a triggering event, as described in connection with  FIG. 5 . Accordingly, direct full analysis is performed and is continued for some time. 
     At time TS, the full second-level analysis is paused, with the processor resuming only the gatekeeping function. The full analysis is repeated, but at increasing intervals as confidence in the well-being of the patient is restored. 
     Then the processor returns to its regular monitoring pattern, with occasional gatekeeping functions during time T 6 , followed by routine full second-level analysis at time T 7 . In this instance, the full second-level analysis was triggered only by a routine periodic checking input  586 . The pattern of times T 6 , T 7  is repeated at times T 8 , T 9 , and so on. 
     Saving on power consumption may also reduce the needed size of a WCD system. Indeed, a WCD system generally requires a minimum operating time during which there will be no changing or recharging the battery. Such a minimum operating time can be, say, 24 hours. The size of the battery required to achieve this operating time depends on the product power consumption. The battery is typically one of the larger components of a WCD system. The physical size of a WCD system is important for patient acceptance since the WCD system must be carried everywhere the patient goes. 
     The devices and/or systems mentioned in this document perform functions, processes and/or methods. These functions, processes and/or methods may be implemented by one or more devices that include logic circuitry. Such a device can be alternately called a computer, and so on. It may be a standalone device or computer, such as a general purpose computer, or part of a device that has one or more additional functions. The logic circuitry may include a processor and non-transitory computer-readable storage media, such as memories, of the type described elsewhere in this document. Often, for the sake of convenience only, it is preferred to implement and describe a program as various interconnected distinct software modules or features. These, along with data are individually and also collectively known as software. In some instances, software is combined with hardware, in a mix called firmware. 
     Moreover, methods and algorithms are described below. These methods and algorithms are not necessarily inherently associated with any particular logic device or other apparatus. Rather, they are advantageously implemented by programs for use by a computing machine, such as a general-purpose computer, a special purpose computer, a microprocessor, a processor such as described elsewhere in this document, and so on. 
     This detailed description includes flowcharts, display images, algorithms, and symbolic representations of program operations within at least one computer readable medium. An economy is achieved in that a single set of flowcharts is used to describe both programs, and also methods. So, while flowcharts described methods in terms of boxes, they also concurrently describe programs. 
     Methods are now described. 
       FIG. 12  shows a flowchart  1200  for describing methods according to embodiments. According to an operation  1210 , a patient parameter can be sensed. The patient parameter can be an ECG of the patient. 
     According to another operation  1220 , a physiological input (P.I.) may be rendered by the transducer from the sensed patient parameter. The physiological input may include ECG data of the patient. 
     According to another operation  1230 , a first-level analysis may be performed on a first portion of the physiological input, to detect whether or not a possible shockable condition exists. The first portion may include first ECG data from a first time segment, and the first-level analysis may be as described for first-level analysis  541 . 
     If at operation  1230  it is determined that the possible shockable condition does not exist then, according to a subsequent operation  1240 , execution may return to operation  1210 . Else, a subsequent operation  1250  takes place responsive to detecting, by the first-level analysis of operation  1230 , that the possible shockable condition exists. 
     According to operation  1250  then, a second-level analysis is performed on a second portion of the physiological input, to detect whether or not an actual shockable condition exists. The second portion may include second ECG data from a second time segment. The second-level analysis may be such that performing the second-level analysis requires more machine operations by the processor than performing the first-level analysis of operation  1230 , if the first time segment had an equal duration with the second time segment. In some embodiments, the second-level analysis may as described for second-level analysis  542 . 
     If at operation  1250  it is determined that the actual shockable condition does not exist then, according to a subsequent operation  1260 , execution may return to operation  1210 . Else, a subsequent operation  1270  takes place responsive to detecting, by the second-level analysis of operation  1250 , that the actual shockable condition exists. 
     According to operation  1270  then, a discharge circuit is controlled to discharge a stored electrical charge through the patient, so as to deliver a shock to the patient while the support structure is worn by the patient. 
     In normal operation of some embodiments, the gatekeeper function of operations  1230  and  1240  would evaluate the patient&#39;s ECG and wake up the main processor only when a full rhythm analysis is necessary or when other patient action is required. When the patient experiences a shockable rhythm the system would operate like this: 
     The gatekeeper function monitors the ECG; 
     the gatekeeper function detects a potentially shockable rhythm; 
     the gatekeeper function wakes up the main processor; 
     the main processor performs a full rhythm analysis, possibly also using an expanded number of channels; and 
     if the full rhythm analysis indicates that a shock is required, then the main processor alerts the patient that a shock is about to be delivered, it stores ECG data to document the event, and it delivers the shock, optionally having alerted the patient and given the patient the chance to avert the shock. 
     In the methods described above, each operation can be performed as an affirmative step of doing, or causing to happen, what is written that can take place. Such doing or causing to happen can be by the whole system or device, or just one or more components of it. It will be recognized that the methods and the operations may be implemented in a number of ways, including using systems, devices and implementations described above. In addition, the order of operations is not constrained to what is shown, and different orders may be possible according to different embodiments. Examples of such alternate orderings may include overlapping, interleaved, interrupted, reordered, incremental, preparatory, supplemental, simultaneous, reverse, or other variant orderings, unless context dictates otherwise. Moreover, in certain embodiments, new operations may be added, or individual operations may be modified or deleted. The added operations can be, for example, from what is mentioned while primarily describing a different system, apparatus, device or method. 
     A person skilled in the art will be able to practice the present invention in view of this description, which is to be taken as a whole. Details have been included to provide a thorough understanding. In other instances, well-known aspects have not been described, in order to not obscure unnecessarily this description. Anything written in the background section of this document is not, and should not be taken as, an acknowledgement or any form of suggestion that such is already known in the art, except where it is expressly pointed out. Plus, any reference to any prior art in this description is not, and should not be taken as, an acknowledgement or any form of suggestion that such prior art forms parts of the common general knowledge in any country or any art. 
     This description includes one or more examples, but this fact does not limit how the invention may be practiced. Indeed, examples, instances, versions or embodiments of the invention may be practiced according to what is described, or yet differently, and also in conjunction with other present or future technologies. Other such embodiments include combinations and sub-combinations of features described herein, including for example, embodiments that are equivalent to the following: providing or applying a feature in a different order than in a described embodiment; extracting an individual feature from one embodiment and inserting such feature into another embodiment; removing one or more features from an embodiment; or both removing a feature from an embodiment and adding a feature extracted from another embodiment, while providing the features incorporated in such combinations and sub-combinations. 
     In general, the present disclosure reflects preferred embodiments of the invention. The attentive reader will note, however, that some aspects of the disclosed embodiments extend beyond the scope of the claims. To the respect that the disclosed embodiments indeed extend beyond the scope of the claims, the disclosed embodiments are to be considered supplementary background information and do not constitute definitions of the claimed invention. 
     In this document, the phrases “constructed to” and/or “configured to” denote one or more actual states of construction and/or configuration that is fundamentally tied to physical characteristics of the element or feature preceding these phrases and, as such, reach well beyond merely describing an intended use. Any such elements or features can be implemented in a number of ways, as will be apparent to a person skilled in the art after reviewing the present disclosure, beyond any examples shown in this document. 
     Any and all parent, grandparent, great-grandparent, etc. patent applications, whether mentioned in this document or in an Application Data Sheet (“ADS”) of this patent application, are hereby incorporated by reference herein as originally disclosed, including any priority claims made in those applications and any material incorporated by reference, to the extent such subject matter is not inconsistent herewith. 
     In this description a single reference numeral may be used consistently to denote a single item, aspect, component, or process. Moreover, a further effort may have been made in the drafting of this description to use similar though not identical reference numerals to denote other versions or embodiments of an item, aspect, component or process that are identical or at least similar or related. Where made, such a further effort was not required, but was nevertheless made gratuitously so as to accelerate comprehension by the reader. Even where made in this document, such a further effort might not have been made completely consistently for all of the versions or embodiments that are made possible by this description. Accordingly, the description controls in defining an item, aspect, component or process, rather than its reference numeral. Any similarity in reference numerals may be used to infer a similarity in the text, but not to confuse aspects where the text or other context indicates otherwise. 
     This disclosure is meant to be illustrative and not limiting on the scope of the following claims. The claims of this document define certain combinations and subcombinations of elements, features and steps or operations, which are regarded as novel and non-obvious. Additional claims for other such combinations and subcombinations may be presented in this or a related document. These claims are intended to encompass within their scope all changes and modifications that are within the true spirit and scope of the subject matter described herein. The terms used herein, including in the claims, are generally intended as “open” terms. For example, the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” etc. If a specific number is ascribed to a claim recitation, this number is a minimum but not a maximum unless stated otherwise. For example, where a claim recites “a” component or “an” item, it means that it can have one or more of this component or item.