Patent Application
20210338168
The disclosure relates generally to medical systems and, more particularly, medical systems configured to detect cardiac pause episodes based on a cardiac electrogram.
Some types of medical devices may monitor a cardiac electrogram (EGM) of a patient to monitor the electrical activity of the patient's heart. A cardiac EGM is an electrical signal sensed via electrodes. In some examples, the medical devices monitor a cardiac EGM to detect one or more types of arrhythmia, such as bradycardia, tachycardia, fibrillation, or asystole, e.g., caused by sinus pause or AV block, which is referred to herein as cardiac pause.
A cardiac EGM may include noise, artifacts, etc. in addition to the signal representing the electrical activity of the heart. Additionally, the amplitude of the signal representing the electrical activity of the heart within the cardiac EGM may vary over time, e.g., due to movement of the electrodes relative to the cardiac tissue. Noise, artifacts, and signal amplitude variations may confound detection of cardiac depolarizations and, consequently, the accurate identification of cardiac pause episodes using the cardiac EGM. This is partially due to the fact that when some cardiac depolarizations are undetected, one or more heartbeats are not accounted for in the cardiac EGM.
In general, the disclosure is directed to techniques for verifying detection of pause-triggered episodes in a cardiac EGM. The techniques include analyzing at least a portion of cardiac EGM data stored as a pause-triggered episode to determine whether the pause-triggered episode is most likely to be classified as a true pause (classification) or a false pause (classification) based upon one or more false pause detection criterion. In some examples, processing circuitry of a medical device/system performs this analysis in response to a pause-triggered episode detection criterion being satisfied.
In some examples, the processing circuitry of the medical device/system classifies the pause-triggered episode into one of a plurality of classifications based on the analysis, which may assist in prioritizing episodes for an episode review process by a qualified medical clinician. For example, if the processing circuitry determines that the pause-triggered episode is more likely a true pause, the processing circuitry may classify the pause-triggered episode as high priority episode in the review process, and if the processing circuitry determines that the pause-triggered episode is more likely a false pause episode, the processing circuitry may classify the pause-triggered episode either as normal priority episode or a low priority episode in the review process. The processing circuitry may utilize one or more false pause-triggered episode detection criterion to determine whether the pause-triggered episode is a likely false pause and to classify as the low priority episode or the normal low priority episode. At least one example criterion evaluates amplitude values to determine a relative flatness of the episode. In this manner, the techniques of this disclosure may advantageously enable improved accuracy in the identification of true pause, improved efficiency of review of pause episodes, and, consequently, better evaluation of the condition of the patient.
In one example, a medical system comprising processing circuitry and a storage medium, the processing circuitry configured to receive a cardiac electrogram of a pause-triggered episode, the cardiac electrogram sensed by a medical device via a plurality of electrodes, determine whether one or more of false pause detection criteria are satisfied based on the cardiac electrogram, wherein the one or more of false pause detection criteria comprise: at least one criterion for relative flatness of amplitude values of the cardiac electrogram in a time interval between a last pre-pause beat and a pause detection time, classify the pause-triggered episode as one of a plurality of classifications based on the determination of whether the false pause detection criterion is satisfied, and output an indication of the classification of the pause-triggered episode to a user display.
In another example, a method comprises receiving a cardiac electrogram of a pause-triggered episode, the cardiac electrogram sensed by a medical device via a plurality of electrodes; determining whether one or more of false pause detection criteria are satisfied based on the cardiac electrogram, wherein the one or more of false pause detection criteria comprise: at least one criterion for relative flatness of amplitude values of the cardiac electrogram in a time interval between a last pre-pause beat and a pause detection time; classifying the pause-triggered episode as one of a plurality of classifications based on the determination of whether the false pause detection criterion is satisfied; and output an indication of the classification of the pause-triggered episode to a user display device.
In another example, a non-transitory computer-readable storage medium comprises program instructions that, when executed by processing circuitry of a medical system, cause the processing circuitry to receive a cardiac electrogram of a pause-triggered episode, the cardiac electrogram sensed by a medical device via a plurality of electrodes; determine whether one or more of false pause detection criteria are satisfied based on the cardiac electrogram, wherein the one or more of false pause detection criteria comprise: at least one criterion for relative flatness of amplitude values of the cardiac electrogram in a time interval between a last pre-pause beat and a pause detection time; classify the pause-triggered episode as one of a plurality of classifications based on the determination of whether the false pause detection criterion is satisfied; and output an indication of the classification of the pause-triggered episode to a user display device.
The summary is intended to provide an overview of the subject matter described in this disclosure. It is not intended to provide an exclusive or exhaustive explanation of the systems, device, and methods described in detail within the accompanying drawings and description below. Further details of one or more examples of this disclosure are set forth in the accompanying drawings and in the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.
Like reference characters denote like elements throughout the description and figures.
A variety of types of medical devices sense and/or evaluate cardiac EGMs. Some medical devices that sense cardiac EGMs are non-invasive, e.g., using a plurality of electrodes placed in contact with external portions of the patient, such as at various locations on the skin of the patient. The electrodes used to monitor the cardiac EGM in these non-invasive processes may be attached to the patient using an adhesive, strap, belt, or vest, as examples, and electrically coupled to a monitoring device, such as an electrocardiograph, Holter monitor, or other electronic device. The electrodes are configured to sense electrical signals associated with the electrical activity of the heart or other cardiac tissue of the patient, and to provide these sensed electrical signals to the electronic device for further processing and/or display of the electrical signals. The non-invasive devices and methods may be utilized on a temporary basis, for example to monitor a patient during a clinical visit, such as during a doctor's appointment, or for example for a predetermined period of time, for example for one day (twenty-four hours), or for a period of several days.
External devices that may be used to non-invasively sense and monitor cardiac EGMs include wearable devices with electrodes configured to contact the skin of the patient, such as patches, watches, or necklaces. One example of a wearable physiological monitor configured to sense a cardiac EGM is the SEEQ™ Mobile Cardiac Telemetry System, available from Medtronic plc, of Dublin, Ireland. Such external devices may facilitate relatively longer-term monitoring of patients during normal daily activities, and may periodically transmit collected data to a network service, such as the Medtronic Carelink™ Network.
Implantable medical devices (IMDs) also sense and monitor cardiac EGMs. The electrodes used by IMDs to sense cardiac EGMs are typically integrated with a housing of the IMD and/or coupled to the IMD via one or more elongated leads. Example IMDs that monitor cardiac EGMs include pacemakers and implantable cardioverter-defibrillators, which may be coupled to intravascular or extravascular leads, as well as pacemakers with housings configured for implantation within the heart, which may be leadless. An example of pacemaker configured for intracardiac implantation is the Micra™ Transcatheter Pacing System, available from Medtronic plc. Some IMDs that do not provide therapy, e.g., implantable patient monitors, sense cardiac EGMs. One example of such an IMD is the Reveal LINQ™ Insertable Cardiac Monitor, available from Medtronic plc, which may be inserted subcutaneously. Such IMDs may facilitate relatively longer-term monitoring of patients during normal daily activities, and may periodically transmit collected data to a network service, such as the Medtronic Carelink™ Network.
Regardless of which type or types of devices are used, a noise signal, which may be referred to as an artifact, may appear in the cardiac EGM and interfere with sensing of depolarizations, causing one or more normal beats to go undetected by the medical device and missing from the cardiac EGM. The time duration of the noise signal may extend over a portion of a normal timeframe for a cardiac cycle of the heart, or may extend over a time span during which multiple cardiac cycles may be expected to have occurred. Such noise signals may be more prevalent when cutaneous, subcutaneous, or extravascular electrodes are used to sense the cardiac EGM, e.g., due to temporary change in contact between at least one of the electrodes and the tissue where the electrode is located due to relative motion of the electrode and tissue. In some examples, the noise signal manifests as a baseline drift of the cardiac EGM, and may include a portion that decays back towards the steady-state baseline.
The presence of a noise signal, artifacts, or undetected beats in a sensed cardiac EGM may cause circuitry for detect a false pause-triggered episode. In addition, the amplitude of the cardiac signals within the sensed cardiac EGM may vary over time, e.g., due to respiration. Such cardiac signal amplitude variation may also be more prevalent in cardiac EGMs sensed using cutaneous, subcutaneous, or extravascular electrodes. Variation in cardiac signal amplitude may also cause detections of pause episodes that turn out to be false pause episodes.
The false pause-triggered episodes may be inserted into a queue for manual review (e.g., by a clinician), increasing the burden of episode review. These types of variations in cardiac signal amplitude may lead to improper analysis of the actual cardiac activity occurring with respect to the patient being monitored, for example, by triggering a false-positive indication of a cardiac event, such as asystole, that is not actually occurring in the patient. Such false-positive indications could lead to incorrect assessment of the patient condition, including provision of therapy and/or sending false alerts to medical personnel responsible for the care of the patient being monitored. Low pass filtering of the cardiac EGM will generally not help solve these problems because these types of noise signals and amplitude variations may occur at frequencies near or below that of the cardiac signals.
Medical systems/devices according to this disclosure implement techniques for identifying false detection of pause-triggered episode in cardiac EGMs by, for example, detecting the presence of noise signals, artifacts, undetected beats, and cardiac signal amplitude variations. In some examples, processing circuitry of the systems analyzes a cardiac EGM associated with an identified pause episode to determine whether one or more false pause detection criterion are satisfied. Each false pause detection criterion may be configured to detect one or more indicators of noise, artifacts, undetected beats and/or amplitude variations in the cardiac EGM. These indicators were found to be predictive of false pauses and are based upon features corresponding to a normal beat count, a noise status of the last pre-pause beat, and a relative flatness of the EGM signal in a portion of the episode that satisfied one or more pause detection criteria or that a medical device otherwise identified as a pause, referred to as a pause interval, e.g., between the last pre-pause beat and the point of the pause detection.
In some examples, processing circuitry of a medical system/device performs this analysis in response to a cardiac EGM received from another device, for example, after an initial pause detection criterion is satisfied. The medical system/device may determine whether to designate the cardiac EGM for high priority, normal priority, or low priority review based on the analysis. In some examples, the processing circuitry of the medical system classifies the episode as a true pause episode with high priority in response to a determination that none of the one or more false pause-triggered episode detection criterion are satisfied. On the other hand, if there is a determination that at least one false pause-triggered episode detection criterion is satisfied, the processing circuitry of the medical system classifies the episode as a false pause episode. Depending upon the one or more false pause-triggered episode detection criterion that is/are satisfied, the processing circuitry may further classify the false pause episode as either low priority or normal priority. At least one additional criterion may be employed for the classification of the false pause episode as either low priority or normal priority after application of at least one false pause detection criterion to determine whether the pause-triggered episode is a true pause episode or a false episode.
The processing circuitry may perform the techniques of this disclosure substantially in real-time in response to the detection of pause, or during a later review of cardiac EGM data for episodes that were identified as pause. In either case, the processing circuitry may include the processing circuitry of medical device that detected the pause episode and/or processing circuitry of another device, such as a local or remote computing device which retrieved the episode data from the medical device. In this manner, the techniques of this disclosure may advantageously enable improved accuracy in the identification of true pause and, consequently, better evaluation of the condition of the patient.
Some examples of the following disclose a medical system and technique for prioritizing cardiac EGM data in a review process for pause-triggered electrogram episodes after an initial detection. One example discloses at least one medical system and technique for classifying pause-triggered electrogram episodes as either “a true pause with high priority” or a “false pause” and then classifying false pause-triggered electrogram episodes as either “a false pause with normal priority” or “a false pause with low priority” and placing cardiac EGM data in corresponding review queues such that the cardiac EGM data placed in a high priority queue is reviewed first. For example, cardiac EGM data is placed in the high-priority queue based on the number of beats in the episode, the noise status of the last pre-pause beat, and the relative flatness of the signal within a pause interval. In particular, the medical system and technique will flag the cardiac EGM data as high-priority if the total number of beats in the episode window is above a threshold, the beat registered at a second immediately preceding the pause interval is not a noisy beat, and the signal is relatively flat within the pause interval of the episode window.
To define relative flatness within the pause interval, the medical system and technique may analyze one or more amplitude criteria such as a criterion requiring a positive final difference value between an amplitude difference (e.g., the difference between the maximum and minimum amplitudes) at another time interval and an amplitude difference of the pause interval. Another criterion may indicate a minimum number of samples crossing an amplitude threshold (e.g., in the pause interval). As an example, the medical system and technique will flag the cardiac EGM data as low priority if any of the following conditions are satisfied: 1) a number of normal beats in the 45-second episode window is less than 20; 2) a number of samples in the 2.5 second pause interval crossing a threshold is greater than 2 and the beat immediately before the medical system and technique detected pause period is a noisy beat; 3) the number of normal beats in the 45 second episode window is less than 30 and the final difference value is less than 2000; or 4) the final difference value is less than −600.
External device 12 may be a computing device with a display viewable by the user and an interface for providing input to external device 12 (i.e., a user input mechanism). In some examples, external device 12 may be a notebook computer, tablet computer, workstation, one or more servers, cellular phone, personal digital assistant, or another computing device that may run an application that enables the computing device to interact with IMD 10.
External device 12 is configured to communicate with IMD 10 and, optionally, another computing device (not illustrated in
External device 12 may be used to configure operational parameters for IMD 10. External device 12 may be used to retrieve data from IMD 10. The retrieved data may include values of physiological parameters measured by IMD 10, indications of episodes of arrhythmia or other maladies detected by IMD 10, and physiological signals recorded by IMD 10. For example, external device 12 may retrieve cardiac EGM segments recorded by IMD 10 due to IMD 10 determining that an episode of pause or another malady occurred during the segment. As will be discussed in greater detail below with respect to
Processing circuitry of medical system 2, e.g., of IMD 10, external device 12, and/or of one or more other computing devices, may be configured to perform the example techniques for identifying false detection of asystole of this disclosure. In some examples, the processing circuitry of medical system 2 analyzes a cardiac EGM sensed by IMD 10 and associated with an identified asystole episode to determine whether one or more of a plurality of false asystole detection criteria are satisfied. Each of the false asystole detection criteria may be configured to detect one or more indicators of noise, artifacts, and/or amplitude variations in the cardiac EGM. Although described in the context of examples in which IMD 10 that senses the cardiac EGM comprises an insertable cardiac monitor, example systems including one or more implantable or external devices of any type configured to sense a cardiac EGM may be configured to implement the techniques of this disclosure.
Processing circuitry 50 may include fixed function circuitry and/or programmable processing circuitry. Processing circuitry 50 may include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or equivalent discrete or analog logic circuitry. In some examples, processing circuitry 50 may include multiple components, such as any combination of one or more microprocessors, one or more controllers, one or more DSPs, one or more ASICs, or one or more FPGAs, as well as other discrete or integrated logic circuitry. The functions attributed to processing circuitry 50 herein may be embodied as software, firmware, hardware or any combination thereof.
Sensing circuitry 52 may be selectively coupled to electrodes 16 via switching circuitry 58, e.g., to select the electrodes 16 and polarity, referred to as the sensing vector, used to sense a cardiac EGM, as controlled by processing circuitry 50. Sensing circuitry 52 may sense signals from electrodes 16, e.g., to produce a cardiac EGM, in order to facilitate monitoring the electrical activity of the heart. Sensing circuitry 52 also may monitor signals from sensors 62, which may include one or more accelerometers, pressure sensors, and/or optical sensors, as examples. In some examples, sensing circuitry 52 may include one or more filters and amplifiers for filtering and amplifying signals received from electrodes 16 and/or sensors 62.
Sensing circuitry 52 and/or processing circuitry 50 may be configured to detect cardiac depolarizations (e.g., P-waves or R-waves) when the cardiac EGM amplitude crosses a sensing threshold. In some examples, the sensing threshold is automatically adjustable over time using any of a variety of automatic sensing threshold adjustment techniques known in the art. For example, in response to detection of a cardiac depolarization, the sensing threshold for detecting a subsequent cardiac depolarization may decay from an initial value over a period of time. Sensing circuitry 52 and/or processing circuitry 50 may determine the initial value based on the amplitude of detected cardiac depolarization. The initial value and decay of the adjustable sensing threshold may be configured such that the sensing threshold is relatively higher soon after the detected cardiac depolarization when a subsequent depolarization is not expected, and decays to relatively lower values over time as the occurrence of a cardiac depolarization becomes more likely. For cardiac depolarization detection, sensing circuitry 52 may include a rectifier, filter, amplifier, comparator, and/or analog-to-digital converter, in some examples.
In some examples, sensing circuitry 52 may output an indication to processing circuitry 50 in response to sensing of a cardiac depolarization. In this manner, processing circuitry 50 may receive detected cardiac depolarization indicators corresponding to the occurrence of detected R-waves and P-waves in the respective chambers of heart. Processing circuitry 50 may use the indications of detected R-waves and P-waves for determining heart rate and detecting arrhythmias, such as tachyarrhythmias and asystole.
Communication circuitry 54 may include any suitable hardware, firmware, software or any combination thereof for communicating with another device, such as external device 12, another networked computing device, or another IMD or sensor. Under the control of processing circuitry 50, communication circuitry 54 may receive downlink telemetry from, as well as send uplink telemetry to external device 12 or another device with the aid of an internal or external antenna, e.g., antenna 26. In addition, processing circuitry 50 may communicate with a networked computing device via an external device (e.g., external device 12) and a computer network, such as the Medtronic CareLink® Network. Antenna 26 and communication circuitry 54 may be configured to transmit and/or receive signals via inductive coupling, electromagnetic coupling, Near Field Communication (NFC), Radio Frequency (RF) communication, Bluetooth, WiFi, or other proprietary or non-proprietary wireless communication schemes.
In some examples, storage device 56 includes computer-readable instructions that, when executed by processing circuitry 50, cause IMD 10 and processing circuitry 50 to perform various functions attributed to IMD 10 and processing circuitry 50 herein. Storage device 56 may include any volatile, non-volatile, magnetic, optical, or electrical media, such as a random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), electrically-erasable programmable ROM (EEPROM), flash memory, or any other digital media. Storage device 56 may store, as examples, programmed values for one or more operational parameters of IMD 10 and/or data collected by IMD 10 for transmission to another device using communication circuitry 54. Data stored by storage device 56 and transmitted by communication circuitry 54 to one or more other devices may include episode data for suspected or potential pause-triggered episodes and/or indications that suspected or potential pause-triggered episodes satisfied one or more false pause-triggered episode detection criteria.
Processing circuitry 50 may detect a pause-triggered episode based on determining that the cardiac electrogram satisfies an initial pause-triggered episode detection criterion. Presence in a cardiac EGM signal of a pause (or an absence of a cardiac depolarization for a predetermined period of time (e.g., three seconds) without registering a normal beat) leads to an initial detection of the pause-triggered episode. In such examples, processing circuitry 50 may determine that the cardiac EGM satisfies the initial pause-triggered episode detection criterion based on reaching the predetermined period of time from detection of a cardiac depolarization without receiving another cardiac depolarization indication from sensing circuitry 52.
Sensing circuitry 52 may also provide one or more digitized cardiac EGM signals to processing circuitry 50 for analysis, e.g., for use in cardiac rhythm discrimination, and/or for analysis to determine whether the initial pause-triggered episode detection criteria are satisfied. In some examples, based on satisfaction of the initial pause-triggered episode detection criterion, processing circuitry 50 may store a segment of the digitized cardiac EGM corresponding to the suspected pause-triggered episode as episode data in storage device 56. The digitized cardiac EGM segment may include samples of the cardiac EGM spanning the period of time for which sensing circuitry 52 did not indicate detection of a depolarization, as well as a period of time before and/or after this period of time during which depolarizations were detected. Processing circuitry 50 of IMD 10, and/or processing circuitry of another device that retrieves the episode data from IMD 10, may analyze the cardiac EGM segment to determine whether one or more false asystole detection criteria are satisfied according to the techniques of this disclosure.
Sensing circuitry 52 may also provide one or more digitized cardiac EGM signals to external device 12 for real-time or off-line analysis, e.g., for use in cardiac rhythm discrimination, and/or for real-time or off-line analysis to determine whether one or more false pause-triggered episode detection criteria are satisfied according to the techniques of this disclosure. Sensing circuitry 52 may also provide cardiac EGM data to external device 12 for real-time or off-line analysis, e.g., for use in cardiac rhythm discrimination, and/or for real-time or off-line analysis to determine whether one or more false pause-triggered episode detection criteria are satisfied according to the techniques of this disclosure. As an alternative, sensing circuitry 52 may also provide one or more digitized cardiac EGM signals to processing circuitry 50 for analysis, e.g., for use in cardiac rhythm discrimination, and/or for analysis to determine whether one or more false pause-triggered episode detection criteria are satisfied.
Communication circuitry 54 may provide cardiac EGM data to external device 12 for real-time or off-line analysis, e.g., for use in cardiac rhythm discrimination, and/or for real-time or off-line analysis to determine whether one or more false pause-triggered episode detection criteria are satisfied according to the techniques of this disclosure.
One or more of antenna 26 or circuitries 50-62 may be formed on the inner side of insulative cover 76, such as by using flip-chip technology. Insulative cover 76 may be flipped onto a housing 15. When flipped and placed onto housing 15, the components of IMD 10 formed on the inner side of insulative cover 76 may be positioned in a gap 78 defined by housing 15. Electrodes 16 may be electrically connected to switching circuitry 58 through one or more vias (not shown) formed through insulative cover 76. Insulative cover 76 may be formed of sapphire (i.e., corundum), glass, parylene, and/or any other suitable insulating material. Housing 15 may be formed from titanium or any other suitable material (e.g., a biocompatible material). Electrodes 16 may be formed from any of stainless steel, titanium, platinum, iridium, or alloys thereof. In addition, electrodes 16 may be coated with a material such as titanium nitride or fractal titanium nitride, although other suitable materials and coatings for such electrodes may be used.
Processing circuitry 80 may include one or more processors that are configured to implement functionality and/or process instructions for execution within external device 12. For example, processing circuitry 80 may be capable of processing instructions stored in storage device 84. Processing circuitry 80 may include, for example, microprocessors, DSPs, ASICs, FPGAs, or equivalent discrete or integrated logic circuitry, or a combination of any of the foregoing devices or circuitry. Accordingly, processing circuitry 80 may include any suitable structure, whether in hardware, software, firmware, or any combination thereof, to perform the functions ascribed herein to processing circuitry 80.
Communication circuitry 82 may include any suitable hardware, firmware, software or any combination thereof for communicating with another device, such as IMD 10. Under the control of processing circuitry 80, communication circuitry 82 may receive downlink telemetry from, as well as send uplink telemetry to, IMD 10, or another device. Communication circuitry 82 may be configured to transmit or receive signals via inductive coupling, electromagnetic coupling, NFC, RF communication, Bluetooth, WiFi, or other proprietary or non-proprietary wireless communication schemes. Communication circuitry 82 may also be configured to communicate with devices other than IMD 10 via any of a variety of forms of wired and/or wireless communication and/or network protocols.
Storage device 84 may be configured to store information within external device 12 during operation. Storage device 84 may include a computer-readable storage medium or computer-readable storage device. In some examples, storage device 84 includes one or more of a short-term memory or a long-term memory. Storage device 84 may include, for example, RAM, DRAM, SRAM, magnetic discs, optical discs, flash memories, or forms of EPROM or EEPROM. In some examples, storage device 84 is used to store data indicative of instructions for execution by processing circuitry 80. Storage device 84 may be used by software or applications running on external device 12 to temporarily store information during program execution.
Data exchanged between external device 12 and IMD 10 may include operational parameters. External device 12 may transmit data including computer readable instructions which, when implemented by IMD 10, may control IMD 10 to change one or more operational parameters and/or export collected data. For example, processing circuitry 80 may transmit an instruction to IMD 10 which requests IMD 10 to export collected data (e.g., asystole episode data) to external device 12. In turn, external device 12 may receive the collected data from IMD 10 and store the collected data in storage device 84. Processing circuitry 80 may implement any of the techniques described herein to analyze cardiac EGMs received from IMD 10, e.g., to determine whether one or more false pause-triggered episode detection criterion are satisfied.
A user, such as a clinician or patient 4, may interact with external device 12 through user interface 86. User interface 86 includes a display (not shown), such as a liquid crystal display (LCD) or a light emitting diode (LED) display or other type of screen, with which processing circuitry 80 may present information related to IMD 10, e.g., cardiac EGMs, indications of detections of arrhythmia episodes, and indications of determinations that one or more false pause-triggered episode detection criterion were satisfied. In addition, user interface 86 may include an input mechanism configured to receive input from the user. The input mechanisms may include, for example, any one or more of buttons, a keypad (e.g., an alphanumeric keypad), a peripheral pointing device, a touch screen, or another input mechanism that allows the user to navigate through user interfaces presented by processing circuitry 80 of external device 12 and provide input. In other examples, user interface 86 also includes audio circuitry for providing audible notifications, instructions or other sounds to the user, receiving voice commands from the user, or both.
Between external device 12 and IMD 10, IMD may transmit cardiac EGM data recording cardiac EGM signals and external device 12 may receive the cardiac EGM data and classify the cardiac EGM signals into a plurality of classifications. Processing circuitry 80 may apply the one or more false pause-triggered episode detection criteria to determine whether a pause-triggered episode is a false pause or a true pause and then to classify the false pause or the true pause as a low priority, a normal priority, or a high priority episode for a review process. In some examples, the one or more false pause-triggered episode detection criterion include at least one amplitude criterion configured to evaluate a relative flatness of at least a portion of the pause-triggered episode. The cardiac EGM signal indicates electrical activity of a heart and during a pause interval, amplitude values remain relatively flat in true pauses but varies considerably in false pauses.
In some examples, the processing circuitry 80 of the external device 12 determines whether to provide or withhold an indication (e.g., to a clinician or other user) that the patient experienced a true pause-triggered episode (or simply pause episode) based on the analysis. In some examples, the processing circuitry 80 of the external device determines whether to provide or withhold an indication (e.g., to a clinician or other user) that the patient experienced a false pause-triggered episode (or simply pause episode) based on the analysis.
Access point 90 may include a device that connects to network 92 via any of a variety of connections, such as telephone dial-up, digital subscriber line (DSL), or cable modem connections. In other examples, access point 90 may be coupled to network 92 through different forms of connections, including wired or wireless connections. In some examples, access point 90 may be a user device, such as a tablet or smartphone, that may be co-located with the patient. IMD 10 may be configured to transmit data, such as asystole episode data and indications that one or more false asystole detection criteria are satisfied, to access point 90. Access point 90 may then communicate the retrieved data to server 94 via network 92.
In some cases, server 94 may be configured to provide a secure storage site for data that has been collected from IMD 10 and/or external device 12. In some cases, server 94 may assemble data in web pages or other documents for viewing by trained professionals, such as clinicians, via computing devices 100. One or more aspects of the illustrated system of
In some examples, one or more of computing devices 100 may be a tablet or other smart device located with a clinician, by which the clinician may program, receive alerts from, and/or interrogate IMD 10. For example, the clinician may access data collected by IMD 10 through a computing device 100, such as when patient 4 is in in between clinician visits, to check on a status of a medical condition. In some examples, the clinician may enter instructions for a medical intervention for patient 4 into an application executed by computing device 100, such as based on a status of a patient condition determined by IMD 10, external device 12, server 94, or any combination thereof, or based on other patient data known to the clinician. Device 100 then may transmit the instructions for medical intervention to another of computing devices 100 located with patient 4 or a caregiver of patient 4. For example, such instructions for medical intervention may include an instruction to change a drug dosage, timing, or selection, to schedule a visit with the clinician, or to seek medical attention. In further examples, a computing device 100 may generate an alert to patient 4 based on a status of a medical condition of patient 4, which may enable patient 4 proactively to seek medical attention prior to receiving instructions for a medical intervention. In this manner, patient 4 may be empowered to take action, as needed, to address his or her medical status, which may help improve clinical outcomes for patient 4.
In the example illustrated by
Storage device 96 may include a computer-readable storage medium or computer-readable storage device. In some examples, storage device 96 includes one or more of a short-term memory or a long-term memory. Storage device 96 may include, for example, RAM, DRAM, SRAM, magnetic discs, optical discs, flash memories, or forms of EPROM or EEPROM. In some examples, storage device 96 is used to store data indicative of instructions for execution by processing circuitry 98.
In one example, processing circuitry 50 of example medical device IMD 10 determines that at least one pause-triggered episode detection criterion is satisfied based on a cardiac EGM sensed by sensing circuitry 52 of IMD 10. For example, as discussed in greater detail with respect to
External device 12, another example medical device of medical system 2, includes processing circuitry 80 to receive the cardiac EGM and evaluate various corresponding data sets by applying one or more false pause-triggered episode detection criterion to those data sets (120). An example false pause-triggered episode detection criterion, as described herein, may include one or more conditions that, if satisfied, indicate a likely false pause-triggered episode. If none of the one or more false pause-triggered episode detection criterion are satisfied, the pause-triggered episode is most likely a true pause. In some instances, medical system 2 classifies the pause-triggered episode for a review process as depicted in
To properly evaluate the cardiac EGM for a false positive, medical system 2 may apply three false pause-triggered episode detection criterion to the cardiac EGM, as illustrated by the example of
One example threshold number of normal beats is a fixed, predetermined number while another example threshold may be determined as a ratio or percentage of a normal beat count to the total number of beats in the above-mentioned predetermined time period; for example, processing circuitry 80 may identify a pause-triggered episode as a false pause if the normal beat count is less than eighty (80)% of total beat count in that predetermined time period. Implementation of such a normal beat count criterion is based on an observation that false detection of a pause-triggered episode tends to occur when there is considerable noise, such as when there is an insufficient number of normal beats. Noise signals may occur in the cardiac EGM intermittently or with varying frequency based on, for example, changes in the condition of IMD 10 or patient 4. Consequently, there may be a greater likelihood that a recently detected pause is actually false (e.g., caused by noise) during a period in which a number of detected normal beats is insufficient (indicating that there may be noise in the EGM) than a period in which there is a sufficient number of detected normal beats. Requiring satisfaction for the normal beat count criterion, as in the example operation of
In some examples, processing circuitry 80 analyzes the morphology of the cardiac EGM signal for each of the beats detected within the cardiac EGM, or a portion thereof. Processing circuitry 80 may classify each of the beats as normal or another classification based on the analysis. The morphological analysis may include a comparison of the cardiac EGM signal for each beat to one or more templates, e.g., a normal beat template.
In response to determining that the normal beat count criterion is not satisfied (NO branch of 122), processing circuitry 80 proceeds to apply a second false pause-triggered episode detection criterion of the three false pause-triggered episode detection criterion. If the normal beat count criterion is satisfied (YES branch of 122), the pause-triggered episode is most likely a false pause and the example operation of
In response to determining that the noise status criterion is not satisfied (NO branch of 124), processing circuitry 80 proceeds to apply at least a third false pause-triggered episode detection criterion of the three false pause-triggered episode detection criterion. Based on whether the noise status criterion is satisfied (YES branch of 124), the pause-triggered episode is most likely a false pause and the example operation of
One example amplitude criterion is satisfied with a non-positive difference value between a comparison window max-min amplitude difference value and a candidate window max-min amplitude difference. The candidate window max-min amplitude difference value refers to a difference value between a maximum amplitude and a minimum amplitude within a time interval encompassing the pause (i.e., the pause interval). The comparison window max-min amplitude difference value refers to a difference value between a maximum amplitude and a minimum amplitude within another time interval in the same cardiac EGM for the episode containing normal beats. An alternative example amplitude criterion includes a threshold difference value of less than zero (0) or greater than twenty thousand (20,000) for the difference value between max-min amplitude difference values between the comparison window and the candidate window. If the example amplitude criterion is satisfied (YES branch of 126), the pause-triggered episode is a likely false pause.
Another example amplitude criterion is satisfied when a negligible number of samples (e.g., zero or one) in the pause interval cross a maximum amplitude limit. In one example, the other example amplitude criterion defines the maximum amplitude limit as a value equal to a maximum amplitude minus a first parameter where the first parameter is a threshold amplitude value. In another example, the other example amplitude criterion defines a second parameter as a threshold for the number of samples crossing the maximum amplitude limit. If the other example amplitude criterion is satisfied or both the example amplitude criterion and the other example amplitude criterion are satisfied (YES branch of 126), the pause-triggered episode is a likely false pause.
Based on the example operation of
In the illustrated example of
Processing circuitry 80 classifies the likely false pause-triggered episode as normal priority if none of four or more additional false pause-triggered episode detection criteria are satisfied and, on the other hand, classifies the likely false pause-triggered episode as low priority if at least one of the four or more additional criterion are satisfied. Hence, the four or more additional criterion may be considered classification criteria.
In the illustrated example of
In response to the determination that the second normal beat count criterion is satisfied (YES branch of 154), processing circuitry 80 classifies the likely false pause-triggered episode as low priority (162). In response to the determination that the second normal beat count criterion is not satisfied (NO branch of 154), processing circuitry 80 proceeds to apply a second additional criterion having, as conditions, a noisy last pre-pause beat and sufficient number of samples (e.g., two (2)) crossing an amplitude limit (e.g., a maximum amplitude limit) (156). In some example, processing circuitry 80 accesses an amplitude threshold as a parameter and sets the amplitude limit as a difference between a maximum amplitude value and the parameter.
In response to the determination that the second additional criterion is not satisfied (NO branch of 156), processing circuitry 80 proceeds to apply a third additional criterion having, as conditions, the first normal beat count and the first max-min amplitude difference criterions (158). The first max-min amplitude difference criterion refers to a threshold difference value between the comparison window max-min amplitude difference value and the candidate window max-min amplitude difference. As described herein, the first max-min amplitude difference criterion is used as one of the false pause-triggered episode detection criterion for determining whether the pause-triggered episode is a false pause or a true pause. The candidate window refers to the pause time interval and the comparison window refers to the second non-overlapping time interval in the same cardiac EGM containing normal beats. Comparing amplitude values in these time intervals determines the relative flatness of the cardiac EGM data of the pause-triggered episode.
Satisfaction with these conditions by the likely false pause-triggered episode indicates to processing circuitry 80 that the third additional criterion is satisfied (YES branch of 158), resulting in classification of the likely false pause-triggered episode as low priority (162). An example of the first max-min amplitude difference criterion includes a threshold difference of less than 2000 for the difference value between maximum amplitude and minimum amplitude difference values in two different time intervals; satisfying the first max-min amplitude difference criterion depends on whether an actual difference between difference values of max-min amplitude difference values is less than or equal to the above threshold difference. Respective ones of the maximum amplitude and minimum amplitude values may be extracted from samples in the first time interval encompassing the likely false pause and from samples in the non-overlapping second time interval encompassing a number of seconds equal to the first time interval. Samples in the second time interval define a pattern (e.g., a measurement of amplitude variation such as flatness) for normal cardiac electrical activity. Comparing the first and second time intervals in terms of max-min amplitude value differences determines a relative flatness of the likely false pause-triggered episode.
Based on the determination that the third additional criterion is not satisfied (NO branch of 158), processing circuitry 80 applies a fourth additional criterion (160). One example of the fourth additional criterion includes a second max-mix amplitude difference threshold. Compared to the first max-mix amplitude difference threshold, the second max-mix amplitude difference criterion may be a lower threshold, satisfaction of which is even more indicative of a false pause due to relative flatness in amplitude values.
In response to the determination that the fourth additional criterion is satisfied (YES branch of 160), processing circuitry 80 determines that the likely false pause-triggered episode is to be classified as low priority and the example operation of
The order and flow of the operations illustrated in
Additionally, although described in the context of an example in which external device 12, and processing circuitry 80 of external device 12, perform each of the portions of the example operation, the example operation of
As illustrated in
As described herein, relative flatness of amplitude values in a possible pause-triggered episode distinguishes episodes that are true pauses from those that are false pauses. One or more amplitude criterion defining the relative flatness in a first interval of the cardiac EGM may be used in one or more false pause-triggered episode criterion. Numerical values measuring the amplitude variations in the first interval (e.g., a max-min amplitude difference) may indicate a false pause if those values exceed a threshold. The threshold may be defined using amplitude values in a second time interval or may be pre-determined. If the amplitude variations exceed the threshold, the cardiac EGM most likely indicates a false pause.
Another example false pause-triggered episode criterion determines an insufficient number of normal beats as indicative of a false pause. This is, in part, because a true pause cannot be determined with insufficient normal beats. As depicted in
Yet another example false pause-triggered episode criterion includes a noise status of a last pre-pause beat 202 that is indicative of a false pause. In some examples, a noisy last pre-pause beat indicates noise in the time interval encompassing the pause-triggered episodes. Samples and corresponding data sets in the time interval are not reliable and cannot be used in confirming a true pause.
Time intervals 231 and 232 of
To determine a given pause-triggered episode's relative flatness, two time intervals within that episode are selected. The following description utilizes 2.5 second time because the pause-triggered persisted for 3 seconds; hence, the described medical system and technique is not limited to a specific amount of time but may be set to any suitable amount of time less than a duration of the pause-triggered episode. If the pause-triggered episode lasted for five seconds, the time intervals may be set to 4.5 or 5 seconds. The described medical system and technique also may depend on the pause-triggered episode duration threshold and/or an amount of EGM data stored relative to the pause-triggered episode detection. In general, a candidate window is the time interval between a timepoint 0.5 seconds after the last pre-pause beat and a pause detection timepoint. In
In one example, the first time interval, a candidate window, consists of the EGM between the 12.5 and 15 second marks of the pause-triggered episode when a pause occurred between the 12 and 15 second marks. The first time interval tends to be relatively flat in true pause episodes, while false pause episodes tend to have artifact/noise signal and/or beats that are not detected by the device in this period. A start time for this window is the 12.5 second mark (rather than the 12 second mark) in order to avoid wide QRS complexes or T-waves following the last pre-pause beat at the 12 second mark. For the second time interval, a comparison window of 2.5 second duration is chosen from the pause-triggered episode.
The comparison window of the second time interval must satisfy a number of conditions, such as the following conditions: 1) The comparison window should not overlap with the 12.5-15 second candidate window; 2) The 2.5 second comparison window should not have any noisy or PVC beats; and 3) The comparison window must contain at least two normal beat markers.
The second time interval is determined by starting to search from the first 500 ms of the episode and moving the window until an acceptable 2.5 second window which satisfies all three above-mentioned conditions is obtained. If the 2.5 second window does not satisfy all three conditions, the search window is moved to the next beat marker and the 3 seconds after the marker are analyzed for the three conditions. If the conditions are satisfied, then the comparison window is chosen from the 0.5 second mark of the beat marker till the 3 second mark (for a total of 2.5 seconds).
After finding an acceptable comparison window to use as the second time interval, the following steps are performed to determine that the first time interval indicates a true pause or a false pause: 1) Subtract a mean from a 2.5 second ECG in the comparison window; 2) Find the minimum and maximum amplitude values in the comparison window; 3) Compute the comparison window difference (e.g., maximum amplitude minus minimum amplitude); 4) Repeat steps 1-3 for the candidate window of the first time interval and compute the candidate window difference (e.g., maximum amplitude minus minimum amplitude); and 5) Compute a final difference between comparison window and candidate window (e.g., comparison window difference minus candidate window difference).
For true pause episodes, the comparison window difference is expected to be high and the candidate window difference is expected to be comparatively lower due to the true pause. Thus, we can expect to see large and positive final difference values (e.g., any value between 0 and 20000). Whereas, for false pause episodes, both the candidate window and comparison window difference values are expected to be closer together, and more final difference values are expected to be negative or closer to zero.
A second false pause episode detection criterion corresponding to amplitude values includes a maximum amplitude objective for normal beats in the first time interval. By way of such a maximum amplitude objective, medical system 2 determines how many samples in the candidate window have amplitude values that cross a maximum amplitude limit for the first time interval. If the samples crossing this limit exceed the maximum amplitude objective, a probability for the true false episode decreases.
Computing the maximum amplitude limit may include performing the following steps: 1) Compute, for each normal beat marker in the 45 second cardiac EGM, a maximum amplitude value among one or more (e.g., 20) samples before and after the marker; 2) Compute a median of the maximum amplitudes of all the normal beats; 3) Compute the number of samples in the 2.5 second candidate window (e.g., from the 12.5 to 15 second marks in the episode) where the amplitude crosses the (median—first parameter) value; and 5) compare the number of samples to a second parameter. Medical system 2 classifies the episode as a false pause episode if the number of samples crossing the (median—first parameter) value is greater than the second parameter.
The first and second parameters may be optimized to obtain a desired balance between sensitivity and specificity for the relative flatness of the cardiac EGM. Medical system 2 may calibrate the first and second parameters to achieve different pairs of sensitivity and specificity values for the classification and prioritization of cardiac EGM data for pause-triggered episodes. An example of the first parameter may be a value of 500 and an example of the second parameter may be zero (0), one (1), or two (2).
In some examples, the medical system 410 is an extravascular implantable cardioverter-defibrillator (EV-ICD) system implanted within patient 408. Medical system 410 includes IMD 412, which in the illustrated example is implanted subcutaneously or submuscularly on the left midaxillary of patient 408, such that IMD 412 may be positioned on the left side of patient 408 above the ribcage. In some other examples, IMD 412 may be implanted at other subcutaneous locations on patient 408 such as at a pectoral location or abdominal location. IMD 412 includes housing 420 that may form a hermetic seal that protects components of IMD 412. In some examples, housing 420 of IMD 412 may be formed of a conductive material, such as titanium, or of a combination of conductive and non-conductive materials, which may function as a housing electrode. IMD 412 may also include a connector assembly (also referred to as a connector block or header) that includes electrical feedthroughs through which electrical connections are made between lead 422 and electronic components included within the housing.
IMD 412 may provide the cardiac EGM sensing, asystole detection, and other functionality described herein with respect to IMD 10, and housing 420 may house circuitries 50-62 and an antenna 26 (
In the illustrated example, IMD 412 is connected to at least one implantable cardiac lead 422. Lead 422 includes an elongated lead body having a proximal end that includes a connector (not shown) configured to be connected to IMD 412 and a distal portion that includes electrodes 432A, 432B, 434A, and 434B. Lead 422 extends subcutaneously above the ribcage from IMD 412 toward a center of the torso of patient 408. At a location near the center of the torso, lead 422 bends or turns and extends intrathoracically superior under/below sternum 424. Lead 422 thus may be implanted at least partially in a substernal space, such as at a target site between the ribcage or sternum 424 and heart 418. In one such configuration, a proximal portion of lead 422 may be configured to extend subcutaneously from IMD 12 toward sternum 24 and a distal portion of lead 22 may be configured to extend superior under or below sternum 424 in the anterior mediastinum 426 (
For example, lead 422 may extend intrathoracically superior under/below sternum 424 within anterior mediastinum 426. Anterior mediastinum 426 may be viewed as being bounded posteriorly by pericardium 416, laterally by pleurae 428, and anteriorly by sternum 424. In some examples, the anterior wall of anterior mediastinum 426 may also be formed by the transversus thoracis and one or more costal cartilages. Anterior mediastinum 426 includes a quantity of loose connective tissue (such as areolar tissue), some lymph vessels, lymph glands, substernal musculature (e.g., transverse thoracic muscle), and small vessels or vessel branches. In one example, the distal portion of lead 422 may be implanted substantially within the loose connective tissue and/or substernal musculature of anterior mediastinum 426. In such examples, the distal portion of lead 422 may be physically isolated from pericardium 416 of heart 418. A lead implanted substantially within anterior mediastinum 426 is an example of a substernal lead or, more generally, an extravascular lead.
The distal portion of lead 422 is described herein as being implanted substantially within anterior mediastinum 426. Thus, some of distal portion of lead 422 may extend out of anterior mediastinum 426 (e.g., a proximal end of the distal portion), although much of the distal portion may be positioned within anterior mediastinum 426. In other embodiments, the distal portion of lead 422 may be implanted intrathoracically in other non-vascular, extra-pericardial locations, including the gap, tissue, or other anatomical features around the perimeter of and adjacent to, but not attached to, the pericardium 416 or other portion of heart 418 and not above sternum 424 or the ribcage. Lead 422 may be implanted anywhere within the “substernal space” defined by the undersurface between the sternum and/or ribcage and the body cavity but not including pericardium 416 or other portions of heart 418. The substernal space may alternatively be referred to by the terms “retrosternal space” or “mediastinum” or “infrasternal” as is known to those skilled in the art and includes the anterior mediastinum 426. The substernal space may also include the anatomical region described in Baudoin, Y. P., et al., entitled “The superior epigastric artery does not pass through Larrey's space (trigonum sternocostale).” Surg. Radiol. Anat. 25.3-4 (2003): 259-62 as Larrey's space. In other words, the distal portion of lead 422 may be implanted in the region around the outer surface of heart 418, but not attached to heart 418. For example, the distal portion of lead 422 may be physically isolated from pericardium 416.
Lead 422 may include an insulative lead body having a proximal end that includes connector 430 configured to be connected to IMD 412 and a distal portion that includes one or more electrodes. As shown in
Electrodes 432A, 432B may be defibrillation electrodes (individually or collectively “defibrillation electrode(s) 432”). Although electrodes 432 may be referred to herein as “defibrillation electrodes 432,” electrodes 432 may be configured to deliver other types of anti-tachyarrhythmia shocks, such as cardioversion shocks. Though defibrillation electrodes 432 are depicted in
Lead 422 may be implanted at a target site below or along sternum 424 such that a therapy vector is substantially across a ventricle of heart 418. In some examples, a therapy vector (e.g., a shock vector for delivery of anti-tachyarrhythmia shock) may be between defibrillation electrodes 432 and a housing electrode formed by or on IMD 412. The therapy vector may, in one example, be viewed as a line that extends from a point on defibrillation electrodes 432 (e.g., a center of one of the defibrillation electrodes 432) to a point on a housing electrode of IMD 412. As such, it may be advantageous to increase an amount of area across which defibrillation electrodes 432 (and therein the distal portion of lead 422) extends across heart 418. Accordingly, lead 422 may be configured to define a curving distal portion as depicted in
Electrodes 434A, 434B may be pace/sense electrodes (individually or collectively, “pace/sense electrode(s) 434”) located on the distal portion of lead 422. Electrodes 434 are referred to herein as pace/sense electrodes as they generally are configured for use in delivery of pacing pulses and/or sensing of cardiac electrical signals. In some instances, electrodes 434 may provide only pacing functionality, only sensing functionality, or both pacing functionality and sensing functionality. In the example illustrated in
In the example of
Deploying lead 422 such that electrodes 432, 434 are at the depicted peaks and valleys of serpentine shape may provide access to preferred sensing or therapy vectors. Orienting the serpentine shaped lead such that pace/sense electrodes 434 are closer to heart 418 may provide better electrical sensing of the cardiac signal and/or lower pacing capture thresholds than if pace/sense electrodes 434 were oriented further from heart 418. The serpentine or other shape of the distal portion of lead 422 may have increased fixation to patient 408 as a result of the shape providing resistance against adjacent tissue when an axial force is applied. Another advantage of a shaped distal portion is that electrodes 432, 434 may have access to greater surface area over a shorter length of heart 418 relative to a lead having a straighter distal portion.
In some examples, the elongated lead body of lead 422 may include one or more elongated electrical conductors (not illustrated) that extend within the lead body from the connector at the proximal lead end to electrodes 432, 434 located along the distal portion of lead 422. The one or more elongated electrical conductors contained within the lead body of lead 422 may engage with respective ones of electrodes 432, 434. The conductors may electrically couple to circuitry, such as a therapy delivery circuitry and sensing circuitry 52, of IMD 412 via connections in connector assembly. The electrical conductors transmit therapy from the therapy delivery circuitry to one or more of electrodes 432, 434, and transmit sensed cardiac EGMs from one or more of electrodes 432, 434 to sensing circuitry 52 within IMD 412.
In general, IMD 412 may sense cardiac EGMs, such as via one or more sensing vectors that include combinations of pace/sense electrodes 434 and/or a housing electrode of IMD 412. In some examples, IMD 412 may sense cardiac EGMs using a sensing vector that includes one or both of the defibrillation electrodes 432 and/or one of defibrillation electrodes 432 and one of pace/sense electrodes 434 or a housing electrode of IMD 412. Medical system 410, including processing circuitry of IMD 412 and/or external device 12, may perform any of the techniques described herein for determining whether asystole detection and false asystole detection criteria are satisfied, e.g., based on cardiac EGMs sensed via extravascular electrodes 432, 434. Cardiac EGMs sensed via extravascular electrodes may include noise, e.g., due to changing contact with tissue and/or orientation relative to heart, in a similar manner as described herein with respect to subcutaneous electrodes. In general, when electrodes are not fixed directly to the myocardium, motion, e.g., respiratory motion, can cause variability in depolarization amplitudes and other noise that may lead to false asystole detections. The techniques described herein may be implemented with cardiac EGMs sensed via subcutaneous electrodes, cutaneous electrodes, substernal electrodes, extravascular electrodes, intra-muscular electrodes, or any electrodes positioned in (or in contact with) any tissue of a patient.
The techniques described in this disclosure may be implemented, at least in part, in hardware, software, firmware, or any combination thereof. For example, various aspects of the techniques may be implemented within one or more microprocessors, DSPs, ASICs, FPGAs, or any other equivalent integrated or discrete logic QRS circuitry, as well as any combinations of such components, embodied in external devices, such as physician or patient programmers, stimulators, or other devices. The terms “processor” and “processing circuitry” may generally refer to any of the foregoing logic circuitry, alone or in combination with other logic circuitry, or any other equivalent circuitry, and alone or in combination with other digital or analog circuitry.
For aspects implemented in software, at least some of the functionality ascribed to the systems and devices described in this disclosure may be embodied as instructions on a computer-readable storage medium such as RAM, DRAM, SRAM, magnetic discs, optical discs, flash memories, or forms of EPROM or EEPROM. The instructions may be executed to support one or more aspects of the functionality described in this disclosure.
In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and/or software modules. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware or software components, or integrated within common or separate hardware or software components. Also, the techniques could be fully implemented in one or more circuits or logic elements. The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including an IMD, an external programmer, a combination of an IMD and external programmer, an integrated circuit (IC) or a set of ICs, and/or discrete electrical circuitry, residing in an IMD and/or external programmer.
