This application relates in general to electrocardiographic monitoring and, in particular, to a method for facilitating diagnosis of cardiac rhythm disorders with the aid of a digital computer.
An electrocardiogram (ECG) allows physicians to diagnose cardiac function by visually tracing the cutaneous electrical signals (action potentials) that are generated by the propagation of the transmembrane ionic currents that trigger the depolarization of cardiac fibers. An ECG trace contains alphabetically-labeled waveform deflections that represent distinct features within the cyclic cardiac activation sequence. The P-wave represents atrial depolarization, which causes atrial contraction. The QRS-complex represents ventricular depolarization. The T-wave represents ventricular repolarization.
The R-wave is often used as an abbreviation for the QRS-complex. An R-R interval spans the period between successive R-waves and, in a normal heart, is 600 milliseconds (ms) to one second long, which respectively correspond to 100 to 60 beats per minute (bpm). The R-wave is the largest waveform generated during normal conduction and represents the cardiac electrical stimuli passing through the ventricular walls. R-R intervals provide information that allows a physician to understand at a glance the context of cardiac rhythms both before and after a suspected rhythm abnormality and can be of confirmational and collaborative value in cardiac arrhythmia diagnosis and treatment.
Conventionally, the potential of R-R interval context has not been fully realized, partly due to the difficulty of presentation in a concise and effective manner to physicians. For instance, routine ECGs are typically displayed at an effective paper speed of 25 millimeters (mm) per second. A lower speed is not recommended because ECG graph resolution degrades at lower speeds and diagnostically-relevant features may be lost. Conversely, a half-hour ECG recording, progressing at 25 mm/s, results in 45 meters of ECG waveforms that, in printed form, is cumbersome and, in electronic display form, will require significant back and forth toggling between pages of waveforms, as well as presenting voluminous data transfer and data storage concerns. As a result, ECGs are less than ideal tools for diagnosing cardiac arrhythmia patterns that only become apparent over an extended time frame, such as 30 minutes or longer.
R-R intervals have also been visualized in Poincare plots, which graph RR(n) on the x-axis and RR(n+1) on the y-axis. However, a Poincare plot fails to preserve the correlation between an R-R interval and the R-R interval's time of occurrence and the linearity of time and associated contextual information, before and after a specific cardiac rhythm, are lost. In addition, significant changes in heart rate, particularly spikes in heart rate, such as due to sinus rhythm transitions to atrial flutter or atrial fibrillation, may be masked or distorted in a Poincare plot if the change occurs over non-successive heartbeats, rather than over two adjacent heartbeats, which undermines reliance on Poincare plots as dependable cardiac arrhythmia diagnostic tools. Further, Poincare plots cannot provide context and immediate temporal reference to the actual ECG, regardless of paper speed. Events both prior to and after a specific ECG rhythm can provide key clinical information disclosed in the R-R interval plot that may change patient management above and beyond the specific rhythm being diagnosed.
Therefore, a need remains for presenting R-R interval data to physicians to reveal temporally-related patterns as an aid to rhythm abnormality diagnosis.
R-R interval data is presented to physicians in a format that includes views of relevant near field and far field ECG data, which together provide contextual information that improves diagnostic accuracy. The near field (or short duration) ECG data view provides a “pinpoint” classical view of an ECG at traditional recording speed in a manner that is known to and widely embraced by physicians. The near field ECG data is coupled to a far field (or medium duration) ECG data view that provides an “intermediate” lower resolution, pre- and post-event contextual view.
Both near field and far field ECG data views are temporally keyed to an extended duration R-R interval data view. In one embodiment, the R-R interval data view is scaled non-linearly to maximize the visual differentiation for frequently-occurring heart rate ranges, such that a single glance allows the physician to make a diagnosis. All three views are presented simultaneously, thereby allowing an interpreting physician to diagnose rhythm and the pre- and post-contextual events leading up to a cardiac rhythm of interest.
The durations of the classical “pinpoint” view, the pre- and post-event “intermediate” view, and the R-R interval plot are flexible and adjustable. In one embodiment, a temporal point of reference is identified in the R-R interval plot and the ECG data that is temporally associated with the point of reference is displayed in the near field and far field ECG data views. In a further embodiment, diagnostically relevant cardiac events can be identified as the temporal point of reference. For clarity, the temporal point of reference will generally be placed in the center of the R-R interval data to allow pre- and post-event heart rhythm and ECG waveform data to present in the correct context. Thus, the pinpoint “snapshot” and intermediate views of ECG data with the extended term R-R interval data allow a physician to comparatively view heart rate context and patterns of behavior prior to and after a clinically meaningful arrhythmia, patient concern or other indicia, thereby enhancing diagnostic specificity of cardiac rhythm disorders and providing physiological context to improve diagnostic ability.
One embodiment provides a system for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer. A download station is adapted to retrieve cutaneous action potentials of a patient recorded over a set period of time as ECG data via an ECG monitoring and recording device. A processor calculates a difference between recording times of successive pairs of R-wave peaks in the ECG data as R-R intervals and determines a heart rate associated with each time difference. An R-R interval plot of the ECG data is generated and includes the R-R intervals plotted along an x-axis of the plot and the heart rates associated with the R-R intervals plotted along a y-axis of the plot. A display presents a presence of sinus tachycardia via the R-R interval plot characterized by each R-R interval and associated heart rate represented as a point in the R-R interval plot and at least a portion of the points representing a baseline that spikes up and gradually slopes down with a wide tail reflecting a sharp rise of heart rates followed by a gradual decline.
A further embodiment provides a system for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer. A download station is adapted to retrieve cutaneous action potentials of a patient recorded over a set period of time as ECG data via an ECG monitoring and recording device. A processor calculates a difference between recording times of successive pairs of R-wave peaks in the ECG data as R-R intervals and determines a heart rate associated with each time difference. An R-R interval plot of the ECG data is generated and includes the R-R intervals plotted along an x-axis of the plot and the heart rates associated with the R-R intervals plotted along a y-axis of the plot. A display presents a presence of bradycardia via the R-R interval plot characterized by each R-R interval and associated heart rate represented as a point in the R-R interval plot and a baseline of the points having multiple spikes of the points representing intermittent episodes of elevated heart rate.
A still further embodiment provides a method for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer. Cutaneous action potentials of a patient are recorded over a set period of time as ECG data and a difference between recording times of successive pairs of R-wave peaks are recorded as R-R intervals. A heart rate is associated with each time difference. An R-R interval plot of the ECG data is generated. A presence of a cardiac event is displayed by presenting a presence of sinus tachycardia or a presence of bradycardia via the R-R interval plot characterized by each R-R interval and associated heart rate represented as a point in the R-R interval plot and at least a portion of the points representing a baseline that spikes up and gradually slopes down with a wide tail reflecting a sharp rise of heart rates followed by a gradual decline. A presence of bradycardia can also be presented via the R-R interval plot and characterized by each R-R interval and associated heart rate represented as a point in the R-R interval plot and a baseline of the points having multiple spikes of the points representing intermittent episodes of elevated heart rate.
The foregoing aspects enhance the presentation of diagnostically relevant R-R interval data, reduce time and effort needed to gather relevant information by a clinician and provide the clinician with a concise and effective diagnostic tool, which is critical to accurate arrhythmia and cardiac rhythm disorder diagnoses.
Custom software packages have been used to identify diagnostically relevant cardiac events from the electrocardiography data, but usually require a cardiologist's diagnosis and verification. In contrast, when presented with a machine-identified event, the foregoing approach aids the cardiologist's diagnostic job by facilitating presentation of ECG-based background information prior to and after the identified event.
Still other embodiments will become readily apparent to those skilled in the art from the following detailed description, wherein are described embodiments by way of illustrating the best mode contemplated. As will be realized, other and different embodiments are possible and the embodiments' several details are capable of modifications in various obvious respects, including time and clustering of events, all without departing from their spirit and the scope. Accordingly, the drawings and detailed description are to be regarded as illustrative in nature and not as restrictive.
A normal healthy cardiac cycle repeats through an expected sequence of events that can be visually traced through an ECG. Each cycle starts with cardiac depolarization originating high in the right atrium in the sinoatrial (SA) node before spreading leftward towards the left atrium and inferiorly towards the atrioventricular (AV) node. After a delay in the AV node, the depolarization impulse transits the Bundle of His and moves into the right and left bundle branches and Purkinje fibers to activate the right and left ventricles.
When a rhythm disorder is suspected, diagnostically-relevant arrhythmic events in the cardiac cycle can often be identified and evaluated with the assistance of an ECG and R-R interval tachography, such as Poincaré plots. Routine ECG evaluation is primarily focused identifying changes to expected ECG waveform shapes.
A full ECG consists of a stream of alphabetically-labeled waveforms 10 that collectively cover cardiac performance over a period of observation. For a healthy patient, within each ECG waveform 10, the P-wave 11 will normally have a smooth, normally upward, positive waveform that indicates atrial depolarization. The QRS complex 17 will usually follow, often with a downward deflection of a Q-wave 12, followed by a larger upward deflection of an R-wave 13, and be terminated with a downward waveform of the S-wave 14, which are collectively representative of ventricular depolarization. The T-wave 15 will normally be a modest upward waveform, representative of ventricular repolarization, while the U-wave 16, which is often not directly observable, will indicate the recovery period of the Purkinje conduction fibers.
Rhythm disorders often manifest through R-R interval variability and the patterns formed by R-R intervals over an extended time period are important tools in the diagnosis of cardiac rhythm abnormalities. For example, atrial fibrillation (AF) is the chaotic firing of the atria that leads to an erratic activation of the ventricles. AF is initially diagnosed by an absence of organized P-waves 11 and confirmed by erratic ventricular rates that manifest in an ECG R-R interval plot as a cloud-like pattern of irregular R-R intervals due to an abnormal conduction of impulses to the ventricles. There is a Gaussian-like distribution to these R-R intervals during AF. Similarly, atrial flutter (AFL) is an abnormal heart rhythm in which cardiac impulses travel along pathways within the right atrium in an organized circular motion, causing the atria to beat faster than and out of sync with the ventricles. During AFL, the heart beats quickly, yet with a regular pattern. Although AFL presents in an electrogram (e-gram) as a “sawtooth” pattern, AFL can be confirmed in an ECG by characteristic R-R interval patterns that usually manifest as 2:1 atrioventricular (AV) conduction or 4:1 atrioventricular conduction. On occasion, the conduction through the AV node is variable and not fixed.
Conventionally, R-R intervals have been visualized using Poincare plots.
The number of dots deviating from the trend line 19 in a Poincare plot can indicate the frequency of occurrence of irregular heartbeats when compared to the number of dots on the trend line 19. The distance of the dots to the trend line 19 can approximate the extent of heart rate change from one heartbeat to the next. However, as heart rate change is limited to only successively-occurring heartbeats, the linearity of time and associated contextual information over an extended time frame are lost. In addition, significant changes in heart rate, particularly spikes in heart rate, such as due to sinus rhythm transitions to atrial flutter, may be masked, distorted or even omitted in a Poincare plot if the change occurs over non-successive heartbeats. In summary, a Poincare plot is more useful as a mathematical tool than a physiological one, and therefore a Poincare plot cannot truly represent what the heart is doing serially over time with respect to changes in the heart's normal and abnormal physiology.
Despite the limitations of Poincare plots and related forms of R-R interval tachography, R-R interval data when presented in a format duplicating temporal physiological events remains a key tool that physicians can rely upon to identify temporally-related cardiac dysrhythmic patterns. Interpretation of R-R interval data can be assisted by including multiple temporal points of reference and a plot of R-R interval data that comparatively depicts heart rate variability in concert with R-R interval data.
As a precursor step, the cutaneous action potentials of a patient are monitored and recorded as ECG data over a set time period (step 21), which can be over a short term or extended time frame. ECG recordation, as well as physiological monitoring, can be provided through various kinds of ECG-capable monitoring ensembles, including a standardized 12-lead ECG setup, such as used for clinical ECG monitoring, a portable Holter-type ECG recorder for traditional ambulatory ECG monitoring, or a wearable ambulatory ECG monitor, such as a flexible extended wear electrode patch and a removable reusable (or single use) monitor recorder, such as described in commonly-assigned U.S. Pat. No. 9,345,414, issued May 24, 2016, the disclosure of which is incorporated by reference, the latter of which includes an electrode patch and monitor recorder that are synergistically optimized to capture electrical signals from the propagation of low amplitude, relatively low frequency content cardiac action potentials, particularly the P-waves, generated during atrial activation. Still other forms of ECG monitoring assembles are possible.
Upon completion of the monitoring period, the ECG and any physiological data are downloaded or retrieved into a digital computer, as further described infra with reference to
To improve diagnosis of heart rate variability, a diagnostic composite plot is constructed that includes one or more temporal points of reference into the ECG data, which provide important diagnostic context, and a plot of R-R interval data is constructed based on the vector of ECG data (step 24), as further described infra with reference to
In a further embodiment, findings made through interpretation of heart rate variability patterns in the diagnostic composite plot can be analyzed to form a diagnosis of a cardiac rhythm disorder (step 25), such as the cardiac rhythm disorders listed, by way of example, in Table 1. For instance, the heart rate variability patterns in the diagnostic composite plot could be provided to a system that programmatically detects AF by virtue of looking for the classic Gaussian-type distribution on the “cloud” of heart rate variability formed in the plot of R-R interval data, which can be corroborated by the accompanying contextual ECG data. Finally, therapy to address diagnosed disorder findings can optionally be programmed into a cardiac rhythm therapy delivery device (step 26), such as an implantable medical device (IMD) (not shown), including a pacemaker, implantable cardioverter defibrillator (ICD), or similar devices.
A diagnostic composite plot is constructed and displayed to help physicians identify and diagnose temporally-related cardiac dysrhythmic patterns. The diagnostic composite plot includes ECG traces from two or more temporal points of reference and a plot of R-R interval data, although other configurations of ECG data plots when combined with the R-R interval plot will also provide critical information.
In the diagnostic composite plot, R-R interval data is presented to physicians in a format that includes views of relevant near field and far field ECG data, which together provide contextual information that improves diagnostic accuracy. In a further embodiment, other views of ECG data can be provided in addition to or in lieu of the near field and far field ECG data views. The near field (or short duration) ECG data provides a “pinpoint” classical view of an ECG at traditional recording speed in a manner that is known to and widely embraced by physicians. The near field ECG data is coupled to a far field (or medium duration) ECG data view that provides an “intermediate” lower resolution, pre- and post-event contextual view. Thus, the extended-duration R-R interval plot is first constructed (step 31), as further described infra with reference to
Rhythm disorders have different weightings depending upon the context with which they occur. In the diagnostic composite plot, the R-R interval data view and the multiple views of the ECG data provide that necessary context. Effectively, the short and medium duration ECG data that accompanies the extended-duration R-R interval plot represents the ECG data “zoomed” in around a temporal point of reference identified in the center (or other location) of the R-R interval plot, thereby providing a visual context to the physician that allows temporal assessment of cardiac rhythm changes in various complementary views of the heart's behavior. The durations of the classical “pinpoint” view, the pre- and post-event “intermediate” view, and the R-R interval plot are flexible and adjustable. In one embodiment, the diagnostic composite plot displays R-R interval data over a forty-minute duration and ECG data over short and medium durations (steps 34 and 35), such as four-second and 24-second durations that provide two- and 12-second segments of the ECG data before and after the R-R interval plot's temporal point of reference, which is generally in the center of the R-R interval plot, although other locations in the R-R interval plot could be identified as the temporal point of reference. The pinpoint “snapshot” and intermediate views of ECG data with the extended term R-R interval data comparatively depicts heart rate context and patterns of behavior prior to and after a clinically meaningful arrhythmia or patient concern, thereby enhancing diagnostic specificity of cardiac rhythm disorders and providing physiological context to improve diagnostic ability. In a further embodiment, diagnostically relevant cardiac events can be identified and the R-R interval plot can be constructed with a cardiac event centered in the middle (or other location) of the plot, which thereby allows pre- and post-event heart rhythm data to be contextually “framed” through the pinpoint and intermediate ECG data views. Other durations, intervals and presentations of ECG data are possible.
The extended-duration R-R interval plot presents beat-to-beat heart rate variability in a format that is intuitive and contextual, yet condensed. The format of the R-R interval plot is selected to optimize visualization of cardiac events in a compressed, yet understandable field of view, that allows for compact presentation of the data akin to a cardiologists understanding of clinical events.
The pairings of R-R intervals and associated heart rates are formed into a two-dimensional plot. R-R intervals are plotted along the x-axis and associated heart rates are plotted along the y-axis. The range and scale of the y-axis (heart rate) can be adjusted according to the range and frequency of normal or patient-specific heart rates, so as to increase the visual distinctions between the heart rates that correspond to different R-R intervals. In one embodiment, the y-axis of the R-R interval plot has a range of 20 to 300 beats per minute and R-R intervals corresponding to heart rates falling extremely outside of this range are excluded to allow easy visualization of 99+% of the heart rate possibilities.
In a further embodiment, they-axis has a non-linear scale that is calculated as a function of the x-axis (R-R interval), such that:
where x is the time difference, min bpm is the minimum heart rate, max bpm is the maximum heart rate, and n<1. The non-linear scale of the y-axis accentuates the spatial distance between successive heart rates when heart rate is low. For example, when n=2, the spatial difference between 50 and 60 bpm is 32% larger than the spatial difference between 90 bpm and 100 bpm, and 68% larger than the spatial difference between 150 bpm and 160 bpm. As a result the overall effect is to accentuate the spatial differences in frequently-occurring ranges of heart rate and de-emphasize the spatial differential in ranges of heart rate where a deviation from norm would have been apparent, thus maximizing the spatial efficiency in data presentation. The goal is to show cardiac events in a simple, small visual contextual format. Larger scales and larger formats bely the practical limits of single-page presentations for the easy visualization at a glance by the busy physician. The visual distinctions between the heart rates that correspond to different R-R intervals stand out, especially when plotted on a non-linear scale. Other y-axis ranges and scales are possible as may be selected by distinct clinical needs and specific diagnostic requirements.
The diagnostic composite plot includes a single, long range view of R-R interval data and a pair of pinpoint ECG data views that together help to facilitate rhythm disorder diagnosis by placing focused long-term heart rate information alongside short-term and medium-term ECG information. Such pairing of ECG and R-R interval data is unique in its ability to inform the physician of events prior to, during and after a cardiovascular event.
The diagnostic composite plot 50 includes an ECG plot presenting a near field (short duration) view 51, an ECG plot presenting an intermediate field (medium duration) view 52, and an R-R interval data plot presenting a far field (extended duration) view 53. The three views 51, 52, 53 are juxtaposed alongside one other to allow quick back and forth referencing of the full context of the heart's normal and abnormal physiology. Typically, a temporal point of reference, which could be a diagnostically relevant cardiac event, patient concern or other indicia, would be identified and centered on the x-axis in all three views. The placement of the temporal point of reference in the middle of all three x-axes enables the ECG data to be temporally keyed to the R-R interval data appearing in the center 60 of the R-R interval data view 53, with a near field view 51 of an ECG displayed at normal (paper-based) recording speed and a far field view 52 that presents the ECG data occurring before and after the center 60. As a result, the near field view 51 provides the ECG data corresponding to the R-R interval data at the center 60 (or other location) in a format that is familiar to all physicians, while the intermediate field view 52 enables presentation of the broader ECG data context going beyond the borders of the near field view 51. In a further embodiment, the center 60 can be slidably adjusted backwards and forwards in time, with the near field view 51 and the far field view 52 of the ECG data automatically adjusting accordingly to stay in context with the R-R interval data view 51. In a still further embodiment, multiple temporal points of reference can be identified with each temporal point of reference being optionally accompanied by one or more dedicated sets of ECG data views.
The collection of plots are conveniently arranged close enough to one another to facilitate printing on a single page of standard sized paper (or physical paper substitute, such as a PDF file), although other layouts of the plots are possible. The far field view 53 is plotted with time in the x-axis and heart rate in the y-axis. The R-R intervals are calculated by measuring the time occurring between successive R-wave peaks. In one embodiment, the far field view 53 presents R-R interval data (expressed as heart rate in bpm) that begins about 20 minutes prior to and ends about 20 minutes following the center 60, although other durations are possible.
The near field view 51 and intermediate field view 52 present ECG data relative to the center 60 of the far field view 53. The near field view 51 provides a pinpoint or short duration view of the ECG data. In one embodiment, the near field view 51 presents ECG data 55 that begins about two seconds prior to and ends about two seconds following the center 60, although other durations are possible. The intermediate field view 52 provides additional contextual ECG information allowing the physician to assess the ECG itself and gather a broader view of the rhythm before and after a “blow-up” of the specific arrhythmia of interest. In one embodiment, the intermediate field view 52 presents ECG data 56 that begins about 12 seconds prior to and ends about 12 seconds following the center 60, although other durations are possible. For convenience, the eight-second interval of the ECG data 56 in the intermediate field view 52 that makes up the ECG data 56 in the near field view 51 is visually highlighted, here, with a surrounding box 57. In addition, other views of the ECG data, either in addition to or in lieu of the near field view 51 and the far field view 52 are possible.
Optionally, an ECG plot presenting an extended far field view 54 of the background information can be included in the diagnostic composite plot 50. In one embodiment, the background information is presented as average heart rate with day and night periods 58 alternately shaded along the x-axis. Other types of background information, such as activity amount, activity intensity, posture, syncope impulse detection, respiratory rate, blood pressure, oxygen saturation (SpO2), blood carbon dioxide level (pCO2), glucose, lung wetness, and temperature, are possible.
Examples of the diagnostic composite plot as applied to specific forms of cardiac rhythm disorders will now be discussed. These examples help to illustrate the distinctive weightings that accompany different forms of rhythm disorders and the R-R interval and ECG waveform deflection context with which they occur.
The diagnostic composite plots are a tool used by physicians as part of a continuum of cardiac care provisioning that begins with ECG monitoring, continues through diagnostic overread and finally, if medically appropriate, concludes with cardiac rhythm disorder treatment. Each of these steps involve different physical components that collaboratively allow physicians to acquire and visualize R-R interval and ECG data in a way that accurately depicts heart rate variability over time.
Each diagnostic composite plot 151 is based on ECG data 166 that has been recorded over a period of observation, which can be for just a short term, such as during a clinic appointment, or over an extended time frame of months. ECG recordation and, in some cases, physiological monitoring can be provided through various types of ECG-capable monitoring ensembles, including a standardized 12-lead ECG setup (not shown), such as used for clinical ECG monitoring, a portable Holter-type ECG recorder for traditional ambulatory ECG monitoring (also not shown), or a wearable ambulatory ECG monitor.
One form of ambulatory ECG monitor 142 particularly suited to monitoring and recording ECG and physiological data employs an electrode patch 143 and a removable reusable (or single use) monitor recorder 144, such as described in commonly-assigned U.S. Pat. No. 9,345,414, cited supra. The electrode patch 143 and monitor recorder 144 are synergistically optimized to capture electrical signals from the propagation of low amplitude, relatively low frequency content cardiac action potentials, particularly the P-waves generated during atrial activation. The ECG monitor 142 sits centrally (in the midline) on the patient's chest along the sternum 169 oriented top-to-bottom. The ECG monitor 142 interfaces to a pair of cutaneous electrodes (not shown) on the electrode patch 143 that are adhered to the patient's skin along the sternal midline (or immediately to either side of the sternum 169). The ECG monitor 142 has a unique narrow “hourglass”-like shape that significantly improves the ability of the monitor to be comfortably worn by the patient 141 for an extended period of time and to cutaneously sense cardiac electric signals, particularly the P-wave (or atrial activity) and, to a lesser extent, the QRS interval signals in the ECG waveforms indicating ventricular activity.
The electrode patch 143 itself is shaped to conform to the contours of the patient's chest approximately centered on the sternal midline. To counter the dislodgment due to compressional and torsional forces, a layer of non-irritating adhesive, such as hydrocolloid, is provided at least partially on the underside, or contact, surface of the electrode patch, but only on the electrode patch's distal and proximal ends. To counter dislodgment due to tensile and torsional forces, a strain relief is defined in the electrode patch's flexible circuit using cutouts partially extending transversely from each opposite side of the flexible circuit and continuing longitudinally towards each other to define in ‘S’-shaped pattern. In a further embodiment, the electrode patch 143 is made from a type of stretchable spunlace fabric. To counter patient bending motions and prevent disadhesion of the electrode patch 143, the outward-facing aspect of the backing, to which a (non-stretchable) flexible circuit is fixedly attached, stretches at a different rate than the backing's skin-facing aspect, where a skin adhesive removably affixes the electrode patch 143 to the skin. Each of these components are distinctive and allow for comfortable and extended wear, especially by women, where breast mobility would otherwise interfere with ECG monitor use and comfort. Still other forms of ECG monitoring and recording assembles are possible.
When operated standalone, the monitor recorder 142 senses and records the patient's ECG data 166 and physiological data (not shown) into a memory onboard the monitor recorder 144. The recorded data can be downloaded using a download station 147, which could be a dedicated download station 145 that permits the retrieval of stored ECG data 166 and physiological data, if applicable, execution of diagnostics on or programming of the monitor recorder 144, or performance of other functions. To facilitate physical connection with the download station 145, the monitor recorder 144 has a set of electrical contacts (not shown) that enable the monitor recorder 144 to physically interface to a set of terminals 148. In turn, the download station 145 can be operated through user controls 149 to execute a communications or data download program 146 (“Download”) or similar program that interacts with the monitor recorder 144 via the physical interface to retrieve the stored ECG data 166. The download station 145 could alternatively be a server, personal computer, tablet or handheld computer, smart mobile device, or purpose-built device designed specific to the task of interfacing with a monitor recorder 144. Still other forms of download station 145 are possible. In a further embodiment, the ECG data 166 from the monitor recorder 144 can be offloaded wirelessly.
The ECG data 166 can be retrieved from the download station 145 using a control program 157 (“Ctl”) or analogous application executing on a personal digital computer 156 or other connectable computing device, via a hard wired link 158, wireless link (not shown), or by physical transfer of storage media (not shown). The personal digital computer 156 may also execute middleware (not shown) that converts the ECG data 166 into a format suitable for use by a third-party post-monitoring analysis program. The personal digital computer 156 stores the ECG data 166 along with each patient's electronic medical records (EMRs) 165 in the secure database 64, as further discussed infra. In a further embodiment, the download station 145 is able to directly interface with other devices over a computer communications network 155, which could be a combination of local area and wide area networks, including the Internet or another telecommunications network, over wired or wireless connections.
A client-server model can be employed for ECG data 166 analysis. In this model, a server 62 executes a patient management program 160 (“Mgt”) or similar application that accesses the retrieved ECG data 166 and other information in the secure database 164 cataloged with each patient's EMRs 165. The patients' EMRs can be supplemented with other information (not shown), such as medical history, testing results, and so forth, which can be factored into automated diagnosis and treatment. The patient management program 160, or other trusted application, also maintains and safeguards the secure database 164 to limit access to patient EMRs 165 to only authorized parties for appropriate medical or other uses, such as mandated by state or federal law, such as under the Health Insurance Portability and Accountability Act (HIPAA) or per the European Union's Data Protection Directive. Other schemes and safeguards to protect and maintain the integrity of patient EMRs 165 are possible.
In a further embodiment, the wearable monitor 142 can interoperate wirelessly with other wearable or implantable physiology monitors and activity sensors 152, such as activity trackers worn on the wrist or body, and with mobile devices 153, including smart watches and smartphones. Wearable or implantable physiology monitors and activity sensors 152 encompass a wide range of wirelessly interconnectable devices that measure or monitor a patient's physiological data, such as heart rate, temperature, blood pressure, respiratory rate, blood pressure, blood sugar (with or without an appropriate subcutaneous probe), oxygen saturation, minute ventilation, and so on; physical states, such as movement, sleep, footsteps, and the like; and performance, including calories burned or estimated blood glucose level. Frequently, wearable and implantable physiology monitors and activity sensors 152 are capable of wirelessly interfacing with mobile devices 153, particularly smart mobile devices, including so-called “smartphones” and “smart watches,” as well as with personal computers and tablet or handheld computers, to download monitoring data either in real-time or in batches through an application (“App”) or similar program.
Based on the ECG data 166, physicians can rely on the data as medically certifiable and are able to directly proceed with diagnosing cardiac rhythm disorders and determining the appropriate course of treatment for the patient 141, including undertaking further medical interventions as appropriate. The ECG data 166 can be retrieved by a digital computer 150 over the network 155. A diagnostic composite plot 151 that includes multiple temporal points of reference and a plot of R-R interval data is then constructed based on the ECG data 166, as discussed in detail supra with reference to
In a further embodiment, the server 159 executes a patient diagnosis program 161 (“Dx”) or similar application that can evaluate the ECG data 166 to form a diagnosis of a cardiac rhythm disorder. The patient diagnosis program 161 compares and evaluates the ECG data 166 to a set of medical diagnostic criteria 167, from which a diagnostic overread 162 (“diagnosis”) is generated. Each diagnostic overread 162 can include one or more diagnostic findings 168 that can be rated by degree of severity, such as with the automated diagnosis of atrial fibrillation. If at least one of the diagnostic findings 168 for a patient exceed a threshold level of tolerance, which may be tailored to a specific client, disease or medical condition group, or applied to a general patient population, in a still further embodiment, therapeutic treatment (“Therapy”) to address diagnosed disorder findings can be generated and, optionally, programmed into a cardiac rhythm therapy delivery device, such as an IMD (not shown), including a pacemaker, implantable cardioverter defibrillator (ICD), or similar devices.
While the invention has been particularly shown and described as referenced to the embodiments thereof, those skilled in the art will understand that the foregoing and other changes in form and detail may be made therein without departing from the spirit and scope.
This non-provisional patent application is a continuation of U.S. Pat. No. 10,736,532, issued Aug. 11, 2020; which is a continuation U.S. Pat. No. 10,045,709, issued Aug. 14, 2018; which is a continuation of U.S. Pat. No. 9,408,551, issued Aug. 9, 2016; which is a continuation-in-part of U.S. Pat. No. 9,345,414, issued May 24, 2016; which is a continuation-in-part of U.S. Pat. No. 9,408,545, issued Aug. 9, 2016; which is a continuation-in-part of U.S. Pat. No. 9,700,227, issued Jul. 11, 2017; which is a continuation-in-part of U.S. Pat. No. 9,730,593, issued Aug. 15, 2017; and further claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application, Ser. No. 62/132,497, filed Mar. 12, 2015, and U.S. Provisional Patent Application, Ser. No. 61/882,403, filed Sep. 25, 2013, the disclosures of which are incorporated by reference.
Number | Name | Date | Kind |
---|---|---|---|
3215136 | Holter et al. | Nov 1965 | A |
3569852 | Berkovits | Mar 1971 | A |
3602215 | Parnell | Aug 1971 | A |
3699948 | Ota et al. | Oct 1972 | A |
3718772 | Sanctuary | Feb 1973 | A |
3893453 | Goldberg | Jul 1975 | A |
4123785 | Cherry et al. | Oct 1978 | A |
4151513 | Menken et al. | Apr 1979 | A |
4328814 | Arkans | May 1982 | A |
4441500 | Sessions et al. | Apr 1984 | A |
4506678 | Russell et al. | Mar 1985 | A |
4532934 | Kelen | Aug 1985 | A |
4546342 | Weaver et al. | Oct 1985 | A |
4550502 | Grayzel | Nov 1985 | A |
4580572 | Granek et al. | Apr 1986 | A |
4635646 | Gilles et al. | Jan 1987 | A |
4653022 | Koro | Mar 1987 | A |
4716903 | Hansen | Jan 1988 | A |
4788983 | Brink et al. | Dec 1988 | A |
4809705 | Ascher | Mar 1989 | A |
4915656 | Alferness | Apr 1990 | A |
5007429 | Treatch et al. | Apr 1991 | A |
5025794 | Albert et al. | Jun 1991 | A |
5107480 | Naus | Apr 1992 | A |
5168876 | Quedens et al. | Dec 1992 | A |
5215098 | Steinhaus | Jun 1993 | A |
5231990 | Gauglitz | Aug 1993 | A |
D341423 | Bible | Nov 1993 | S |
5263481 | Axelgaard | Nov 1993 | A |
5265579 | Ferrari | Nov 1993 | A |
5312446 | Holschbach et al. | May 1994 | A |
5314453 | Jeutter | May 1994 | A |
5331966 | Bennett et al. | Jul 1994 | A |
5333615 | Craelius et al. | Aug 1994 | A |
5341806 | Gadsby et al. | Aug 1994 | A |
5348008 | Bomn et al. | Sep 1994 | A |
5355891 | Wateridge et al. | Oct 1994 | A |
5365934 | Leon et al. | Nov 1994 | A |
5365935 | Righter et al. | Nov 1994 | A |
5392784 | Gudaitis | Feb 1995 | A |
D357069 | Plahn et al. | Apr 1995 | S |
5402780 | Faasse, Jr. | Apr 1995 | A |
5402884 | Gilman et al. | Apr 1995 | A |
5450845 | Axelgaard | Sep 1995 | A |
5451876 | Sendford et al. | Sep 1995 | A |
5458141 | Neil | Oct 1995 | A |
5473537 | Glazer et al. | Dec 1995 | A |
5479922 | Reichl | Jan 1996 | A |
5483969 | Testerman et al. | Jan 1996 | A |
5511553 | Segalowitz | Apr 1996 | A |
5540733 | Testerman et al. | Jul 1996 | A |
5546952 | Erickson | Aug 1996 | A |
5549655 | Erickson | Aug 1996 | A |
5579919 | Gilman et al. | Dec 1996 | A |
5582181 | Ruess | Dec 1996 | A |
D377983 | Sabri et al. | Feb 1997 | S |
5601089 | Bledsoe et al. | Feb 1997 | A |
5623935 | Faisandier | Apr 1997 | A |
5682901 | Kamen | Nov 1997 | A |
5697955 | Stolte | Dec 1997 | A |
5724967 | Venkatachalam | Mar 1998 | A |
5749902 | Olsen et al. | May 1998 | A |
5788633 | Mahoney | Aug 1998 | A |
5817151 | Olsen et al. | Oct 1998 | A |
5819741 | Karlsson et al. | Oct 1998 | A |
5850920 | Gilman et al. | Dec 1998 | A |
5860918 | Schradi | Jan 1999 | A |
D407159 | Roberg | Mar 1999 | S |
5876351 | Rohde | Mar 1999 | A |
5906583 | Rogel | May 1999 | A |
5951598 | Bishay et al. | Sep 1999 | A |
5956013 | Raj et al. | Sep 1999 | A |
5957857 | Hartley | Sep 1999 | A |
5984102 | Tay | Nov 1999 | A |
5987352 | Klein et al. | Nov 1999 | A |
6032064 | Devlin et al. | Feb 2000 | A |
6038469 | Karlsson et al. | Mar 2000 | A |
6101413 | Olsen et al. | Aug 2000 | A |
6115638 | Groenke | Sep 2000 | A |
6117077 | Del Mar et al. | Sep 2000 | A |
6134479 | Brewer et al. | Oct 2000 | A |
6148233 | Owen et al. | Nov 2000 | A |
6149602 | Arcelus | Nov 2000 | A |
6149781 | Forand | Nov 2000 | A |
6185452 | Schulman et al. | Feb 2001 | B1 |
6188407 | Smith et al. | Feb 2001 | B1 |
D443063 | Pisani et al. | May 2001 | S |
6245025 | Torok et al. | Jun 2001 | B1 |
6246330 | Nielsen | Jun 2001 | B1 |
6249696 | Olson et al. | Jun 2001 | B1 |
D445507 | Pisani et al. | Jul 2001 | S |
6269267 | Bardy et al. | Jul 2001 | B1 |
6272385 | Bishay et al. | Aug 2001 | B1 |
6298255 | Cordero et al. | Oct 2001 | B1 |
6301502 | Owen et al. | Oct 2001 | B1 |
6304773 | Taylor et al. | Oct 2001 | B1 |
6304780 | Owen et al. | Oct 2001 | B1 |
6304783 | Lyster et al. | Oct 2001 | B1 |
6374138 | Owen et al. | Apr 2002 | B1 |
6381482 | Jayaraman et al. | Apr 2002 | B1 |
6416471 | Kumar et al. | Jul 2002 | B1 |
6418342 | Owen et al. | Jul 2002 | B1 |
6424860 | Karlsson et al. | Jul 2002 | B1 |
6427083 | Owen et al. | Jul 2002 | B1 |
6427085 | Boon et al. | Jul 2002 | B1 |
6434410 | Cordero | Aug 2002 | B1 |
6454708 | Ferguson et al. | Sep 2002 | B1 |
6456256 | Amundson et al. | Sep 2002 | B1 |
6456872 | Faisandier | Sep 2002 | B1 |
6463320 | Xue et al. | Oct 2002 | B1 |
6546285 | Owen et al. | Apr 2003 | B1 |
6605046 | Del Mar | Aug 2003 | B1 |
6607485 | Bardy | Aug 2003 | B2 |
6611705 | Hopman et al. | Aug 2003 | B2 |
6671545 | Fincke | Dec 2003 | B2 |
6671547 | Lyster et al. | Dec 2003 | B2 |
6694186 | Bardy | Feb 2004 | B2 |
6704595 | Bardy | Mar 2004 | B2 |
6705991 | Bardy | Mar 2004 | B2 |
6719701 | Lade | Apr 2004 | B2 |
6754523 | Toole | Jun 2004 | B2 |
6782293 | Dupelle et al. | Aug 2004 | B2 |
6856832 | Matsumura | Feb 2005 | B1 |
6860897 | Bardy | Mar 2005 | B2 |
6866629 | Bardy | Mar 2005 | B2 |
6887201 | Bardy | May 2005 | B2 |
6893397 | Bardy | May 2005 | B2 |
6895261 | Palamides | May 2005 | B1 |
6904312 | Bardy | Jun 2005 | B2 |
6908431 | Bardy | Jun 2005 | B2 |
6913577 | Bardy | Jul 2005 | B2 |
6944498 | Owen et al. | Sep 2005 | B2 |
6960167 | Bardy | Nov 2005 | B2 |
6970731 | Jayaraman et al. | Nov 2005 | B1 |
6978169 | Guerra | Dec 2005 | B1 |
6993377 | Flick et al. | Jan 2006 | B2 |
7020508 | Stivoric et al. | Mar 2006 | B2 |
7027864 | Snyder et al. | Apr 2006 | B2 |
7052472 | Miller et al. | May 2006 | B1 |
7065401 | Worden | Jun 2006 | B2 |
7085601 | Bardy et al. | Aug 2006 | B1 |
7104955 | Bardy | Sep 2006 | B2 |
7134996 | Bardy | Nov 2006 | B2 |
7137389 | Berthon-Jones | Nov 2006 | B2 |
7147600 | Bardy | Dec 2006 | B2 |
7215991 | Besson et al. | May 2007 | B2 |
7248916 | Bardy | Jul 2007 | B2 |
7257438 | Kinast | Aug 2007 | B2 |
7277752 | Matos | Oct 2007 | B2 |
7294108 | Bomzin et al. | Nov 2007 | B1 |
D558882 | Brady | Jan 2008 | S |
7328061 | Rowlandson et al. | Feb 2008 | B2 |
7412395 | Rowlandson et al. | Aug 2008 | B2 |
7429938 | Corndorf | Sep 2008 | B1 |
7552031 | Vock et al. | Jun 2009 | B2 |
D606656 | Kobayashi et al. | Dec 2009 | S |
7672714 | Kuo et al. | Mar 2010 | B2 |
7706870 | Shieh et al. | Apr 2010 | B2 |
7756721 | Falchuk et al. | Jul 2010 | B1 |
7787943 | McDonough | Aug 2010 | B2 |
7874993 | Bardy | Jan 2011 | B2 |
7881785 | Nassif et al. | Feb 2011 | B2 |
D639437 | Bishay et al. | Jun 2011 | S |
7959574 | Bardy | Jun 2011 | B2 |
8108035 | Bharmi | Jan 2012 | B1 |
8116841 | Bly et al. | Feb 2012 | B2 |
8135459 | Bardy et al. | Mar 2012 | B2 |
8172761 | Rulkov et al. | May 2012 | B1 |
8180425 | Selvitelli et al. | May 2012 | B2 |
8200320 | Kovacs | Jun 2012 | B2 |
8231539 | Bardy | Jul 2012 | B2 |
8231540 | Bardy | Jul 2012 | B2 |
8239012 | Felix et al. | Aug 2012 | B2 |
8249686 | Libbus et al. | Aug 2012 | B2 |
8260414 | Nassif et al. | Sep 2012 | B2 |
8266008 | Siegel et al. | Sep 2012 | B1 |
8277378 | Bardy | Oct 2012 | B2 |
8285356 | Bly et al. | Oct 2012 | B2 |
8285370 | Felix et al. | Oct 2012 | B2 |
8308650 | Bardy | Nov 2012 | B2 |
8366629 | Bardy | Feb 2013 | B2 |
8374688 | Libbus et al. | Feb 2013 | B2 |
8412317 | Mazar | Apr 2013 | B2 |
8460189 | Libbus et al. | Jun 2013 | B2 |
8473047 | Chakravarthy et al. | Jun 2013 | B2 |
8478418 | Fahey | Jul 2013 | B2 |
8538503 | Kumar et al. | Sep 2013 | B2 |
8545416 | Kayyali et al. | Oct 2013 | B1 |
8554311 | Warner et al. | Oct 2013 | B2 |
8560046 | Kumar et al. | Oct 2013 | B2 |
8591430 | Amurthur et al. | Nov 2013 | B2 |
8594763 | Bibian et al. | Nov 2013 | B1 |
8600486 | Kaib et al. | Dec 2013 | B2 |
8613708 | Bishay et al. | Dec 2013 | B2 |
8613709 | Bishay et al. | Dec 2013 | B2 |
8620418 | Kuppuraj et al. | Dec 2013 | B1 |
8626277 | Felix et al. | Jan 2014 | B2 |
8628020 | Beck | Jan 2014 | B2 |
8668653 | Nagata et al. | Mar 2014 | B2 |
8684925 | Manicka et al. | Apr 2014 | B2 |
8688190 | Libbus et al. | Apr 2014 | B2 |
8718752 | Libbus et al. | May 2014 | B2 |
8744561 | Fahey | Jun 2014 | B2 |
8774932 | Fahey | Jul 2014 | B2 |
8790257 | Libbus et al. | Jul 2014 | B2 |
8790259 | Katra et al. | Jul 2014 | B2 |
8795174 | Manicka et al. | Aug 2014 | B2 |
8798729 | Kaib et al. | Aug 2014 | B2 |
8798734 | Kuppuraj et al. | Aug 2014 | B2 |
8818478 | Scheffler et al. | Aug 2014 | B2 |
8818481 | Bly et al. | Aug 2014 | B2 |
8823490 | Libbus et al. | Sep 2014 | B2 |
8858432 | Robertson et al. | Oct 2014 | B2 |
8938287 | Felix et al. | Jan 2015 | B2 |
8948935 | Peeters | Feb 2015 | B1 |
8965492 | Baker et al. | Feb 2015 | B2 |
9066664 | Karjalainen | Jun 2015 | B2 |
9135608 | Herlitz | Sep 2015 | B2 |
9155484 | Baker et al. | Oct 2015 | B2 |
9204813 | Kaib et al. | Dec 2015 | B2 |
9241649 | Kumar et al. | Jan 2016 | B2 |
9259154 | Miller et al. | Feb 2016 | B2 |
9277864 | Yang et al. | Mar 2016 | B2 |
9339202 | Brockway et al. | May 2016 | B2 |
9375179 | Schultz et al. | Jun 2016 | B2 |
9414786 | Brockway et al. | Aug 2016 | B1 |
9439566 | Arne et al. | Sep 2016 | B2 |
9597004 | Hughes et al. | Mar 2017 | B2 |
9603542 | Veen et al. | Mar 2017 | B2 |
9700222 | Quinlan et al. | Jul 2017 | B2 |
9730593 | Felix | Aug 2017 | B2 |
9770182 | Bly et al. | Sep 2017 | B2 |
10034614 | Edic et al. | Jul 2018 | B2 |
10045708 | Dusan | Aug 2018 | B2 |
10045709 | Bardy | Aug 2018 | B2 |
10049182 | Chefles et al. | Aug 2018 | B2 |
10736532 | Bardy | Aug 2020 | B2 |
20010051766 | Gazdzinski | Dec 2001 | A1 |
20020013538 | Teller | Jan 2002 | A1 |
20020013717 | Ando et al. | Jan 2002 | A1 |
20020016798 | Sakai | Feb 2002 | A1 |
20020082867 | MacCarter et al. | Jun 2002 | A1 |
20020103422 | Harder et al. | Aug 2002 | A1 |
20020109621 | Khair et al. | Aug 2002 | A1 |
20020120310 | Linden et al. | Aug 2002 | A1 |
20020128686 | Minogue et al. | Sep 2002 | A1 |
20020184055 | Naghavi et al. | Dec 2002 | A1 |
20020193668 | Munneke | Dec 2002 | A1 |
20030004547 | Owen et al. | Jan 2003 | A1 |
20030028811 | Walker et al. | Feb 2003 | A1 |
20030073916 | Yonce | Apr 2003 | A1 |
20030083559 | Thompson | May 2003 | A1 |
20030097078 | Maeda | May 2003 | A1 |
20030139785 | Riff et al. | Jul 2003 | A1 |
20030149349 | Jensen | Aug 2003 | A1 |
20030174881 | Simard et al. | Sep 2003 | A1 |
20030176802 | Galen et al. | Sep 2003 | A1 |
20030211797 | Hill et al. | Nov 2003 | A1 |
20040008123 | Carrender | Jan 2004 | A1 |
20040019288 | Kinast | Jan 2004 | A1 |
20040034284 | Aversano et al. | Feb 2004 | A1 |
20040049120 | Cao et al. | Mar 2004 | A1 |
20040049132 | Barron et al. | Mar 2004 | A1 |
20040073127 | Istvan et al. | Apr 2004 | A1 |
20040087836 | Green et al. | May 2004 | A1 |
20040088019 | Rueter et al. | May 2004 | A1 |
20040093192 | Hasson et al. | May 2004 | A1 |
20040116784 | Gavish | Jun 2004 | A1 |
20040148194 | Wellons et al. | Jul 2004 | A1 |
20040163034 | Colbath et al. | Aug 2004 | A1 |
20040167416 | Lee | Aug 2004 | A1 |
20040207530 | Nielsen | Oct 2004 | A1 |
20040210165 | Marmaropoulos et al. | Oct 2004 | A1 |
20040236202 | Burton | Nov 2004 | A1 |
20040243435 | Williams | Dec 2004 | A1 |
20040256453 | Lammle | Dec 2004 | A1 |
20040260188 | Syed et al. | Dec 2004 | A1 |
20040260192 | Yamamoto | Dec 2004 | A1 |
20050010139 | Aminian et al. | Jan 2005 | A1 |
20050043640 | Chang | Feb 2005 | A1 |
20050058701 | Gross et al. | Mar 2005 | A1 |
20050096717 | Bishay et al. | May 2005 | A1 |
20050101875 | Semler et al. | May 2005 | A1 |
20050108055 | Ott et al. | May 2005 | A1 |
20050113661 | Nazeri | May 2005 | A1 |
20050137485 | Cao et al. | Jun 2005 | A1 |
20050151640 | Hastings | Jul 2005 | A1 |
20050154267 | Bardy | Jul 2005 | A1 |
20050154294 | Uchiyama et al. | Jul 2005 | A1 |
20050182308 | Bardy | Aug 2005 | A1 |
20050182309 | Bardy | Aug 2005 | A1 |
20050215918 | Frantz et al. | Sep 2005 | A1 |
20050222513 | Hadley et al. | Oct 2005 | A1 |
20050228243 | Bardy | Oct 2005 | A1 |
20050245839 | Stivoric et al. | Nov 2005 | A1 |
20050261564 | Ryu et al. | Nov 2005 | A1 |
20050275416 | Hervieux et al. | Dec 2005 | A1 |
20060025696 | Kurzweil et al. | Feb 2006 | A1 |
20060025824 | Freeman et al. | Feb 2006 | A1 |
20060030767 | Lang et al. | Feb 2006 | A1 |
20060030781 | Shennib | Feb 2006 | A1 |
20060030904 | Quiles | Feb 2006 | A1 |
20060041201 | Behbehani et al. | Feb 2006 | A1 |
20060084883 | Linker | Apr 2006 | A1 |
20060100530 | Kliot et al. | May 2006 | A1 |
20060111642 | Baura et al. | May 2006 | A1 |
20060111943 | Wu | May 2006 | A1 |
20060122469 | Martel | Jun 2006 | A1 |
20060124193 | Orr et al. | Jun 2006 | A1 |
20060167502 | Haefner | Jul 2006 | A1 |
20060224072 | Shennib | Oct 2006 | A1 |
20060229522 | Barr | Oct 2006 | A1 |
20060235320 | Tan et al. | Oct 2006 | A1 |
20060253006 | Bardy | Nov 2006 | A1 |
20060264730 | Stivoric et al. | Nov 2006 | A1 |
20060264767 | Shennib | Nov 2006 | A1 |
20070003115 | Patton et al. | Jan 2007 | A1 |
20070038057 | Nam et al. | Feb 2007 | A1 |
20070050209 | Yered | Mar 2007 | A1 |
20070078324 | Wijisiriwardana | Apr 2007 | A1 |
20070078354 | Holland | Apr 2007 | A1 |
20070088406 | Bennett et al. | Apr 2007 | A1 |
20070088419 | Fiorina et al. | Apr 2007 | A1 |
20070089800 | Sharma | Apr 2007 | A1 |
20070093719 | Nichols, Jr. et al. | Apr 2007 | A1 |
20070100248 | Van Dam et al. | May 2007 | A1 |
20070100667 | Bardy | May 2007 | A1 |
20070123801 | Goldberger et al. | May 2007 | A1 |
20070131595 | Jansson et al. | Jun 2007 | A1 |
20070136091 | McTaggart | Jun 2007 | A1 |
20070142722 | Chang | Jun 2007 | A1 |
20070179357 | Bardy | Aug 2007 | A1 |
20070185390 | Perkins et al. | Aug 2007 | A1 |
20070203415 | Bardy | Aug 2007 | A1 |
20070203423 | Bardy | Aug 2007 | A1 |
20070208232 | Kovacs | Sep 2007 | A1 |
20070208233 | Kovacs | Sep 2007 | A1 |
20070208266 | Hadley | Sep 2007 | A1 |
20070225611 | Kumar et al. | Sep 2007 | A1 |
20070233198 | Ghanem et al. | Oct 2007 | A1 |
20070244405 | Xue et al. | Oct 2007 | A1 |
20070249946 | Kumar et al. | Oct 2007 | A1 |
20070255153 | Kumar et al. | Nov 2007 | A1 |
20070265510 | Bardy | Nov 2007 | A1 |
20070270678 | Fadem | Nov 2007 | A1 |
20070276270 | Tran | Nov 2007 | A1 |
20070276275 | Proctor et al. | Nov 2007 | A1 |
20070293738 | Bardy | Dec 2007 | A1 |
20070293739 | Bardy | Dec 2007 | A1 |
20070293740 | Bardy | Dec 2007 | A1 |
20070293741 | Bardy | Dec 2007 | A1 |
20070293772 | Bardy | Dec 2007 | A1 |
20070299325 | Farrell et al. | Dec 2007 | A1 |
20070299617 | Willis | Dec 2007 | A1 |
20080027337 | Dugan | Jan 2008 | A1 |
20080027339 | Nagai et al. | Jan 2008 | A1 |
20080051668 | Bardy | Feb 2008 | A1 |
20080058661 | Bardy | Mar 2008 | A1 |
20080143080 | Burr | Mar 2008 | A1 |
20080088467 | Al-Ali et al. | Apr 2008 | A1 |
20080091089 | Guillory et al. | Apr 2008 | A1 |
20080091097 | Linti et al. | Apr 2008 | A1 |
20080108890 | Teng et al. | May 2008 | A1 |
20080114232 | Gazit | May 2008 | A1 |
20080139953 | Baker et al. | Jun 2008 | A1 |
20080177168 | Callahan et al. | Jul 2008 | A1 |
20080194927 | KenKnight et al. | Aug 2008 | A1 |
20080208009 | Shklarski | Aug 2008 | A1 |
20080208014 | KenKnight et al. | Aug 2008 | A1 |
20080243012 | Fujihashi et al. | Oct 2008 | A1 |
20080284599 | Zdeblick et al. | Nov 2008 | A1 |
20080288026 | Cross et al. | Nov 2008 | A1 |
20080294024 | Cosentino et al. | Nov 2008 | A1 |
20080306359 | Zdeblick et al. | Dec 2008 | A1 |
20080309481 | Tanaka et al. | Dec 2008 | A1 |
20080312522 | Rowlandson et al. | Dec 2008 | A1 |
20090009342 | Karjalainen | Jan 2009 | A1 |
20090012412 | Wiesel | Jan 2009 | A1 |
20090012979 | Bateni et al. | Jan 2009 | A1 |
20090054737 | Magar et al. | Feb 2009 | A1 |
20090054952 | Glukhovsky et al. | Feb 2009 | A1 |
20090062670 | Sterling | Mar 2009 | A1 |
20090062897 | Axelgaard | Mar 2009 | A1 |
20090069867 | KenKnight et al. | Mar 2009 | A1 |
20090073991 | Landrum et al. | Mar 2009 | A1 |
20090076336 | Mazar et al. | Mar 2009 | A1 |
20090076341 | James et al. | Mar 2009 | A1 |
20090076342 | Amurthur et al. | Mar 2009 | A1 |
20090076343 | James et al. | Mar 2009 | A1 |
20090076346 | James et al. | Mar 2009 | A1 |
20090076349 | Libbus et al. | Mar 2009 | A1 |
20090076397 | Libbus et al. | Mar 2009 | A1 |
20090076401 | Mazar et al. | Mar 2009 | A1 |
20090076559 | Libbus et al. | Mar 2009 | A1 |
20090076364 | Libbus et al. | Apr 2009 | A1 |
20090088652 | Tremblay | Apr 2009 | A1 |
20090093687 | Telfort et al. | Apr 2009 | A1 |
20090112116 | Lee et al. | Apr 2009 | A1 |
20090131759 | Sims et al. | May 2009 | A1 |
20090133047 | Lee et al. | May 2009 | A1 |
20090156908 | Belalcazar et al. | Jun 2009 | A1 |
20090182204 | Semler et al. | Jul 2009 | A1 |
20090216132 | Orbach | Aug 2009 | A1 |
20090270708 | Shen et al. | Oct 2009 | A1 |
20090270747 | Van Dam et al. | Oct 2009 | A1 |
20090292194 | Libbus et al. | Nov 2009 | A1 |
20090327715 | Smith et al. | Dec 2009 | A1 |
20100007413 | Herleikson et al. | Jan 2010 | A1 |
20100022897 | Parker et al. | Jan 2010 | A1 |
20100056877 | Fein et al. | Mar 2010 | A1 |
20100056881 | Libbus et al. | Mar 2010 | A1 |
20100076517 | Imran | Mar 2010 | A1 |
20100081913 | Cross et al. | Apr 2010 | A1 |
20100137694 | Irazoqui et al. | Jun 2010 | A1 |
20100174229 | Hsu et al. | Jul 2010 | A1 |
20100177100 | Carnes | Jul 2010 | A1 |
20100185063 | Bardy | Jul 2010 | A1 |
20100185076 | Jeong et al. | Jul 2010 | A1 |
20100191154 | Berger et al. | Jul 2010 | A1 |
20100191310 | Bly | Jul 2010 | A1 |
20100223020 | Goetz | Sep 2010 | A1 |
20100234697 | Walter et al. | Sep 2010 | A1 |
20100234715 | Shin et al. | Sep 2010 | A1 |
20100234716 | Engel | Sep 2010 | A1 |
20100268103 | McNamara et al. | Oct 2010 | A1 |
20100280366 | Arne et al. | Nov 2010 | A1 |
20100298720 | Potkay | Nov 2010 | A1 |
20100312188 | Robertson et al. | Dec 2010 | A1 |
20100317957 | Lee et al. | Dec 2010 | A1 |
20100324384 | Moon et al. | Dec 2010 | A1 |
20100324405 | Niemi et al. | Dec 2010 | A1 |
20110021937 | Hugh et al. | Jan 2011 | A1 |
20110054286 | Crosby et al. | Mar 2011 | A1 |
20110060215 | Tupin et al. | Mar 2011 | A1 |
20110066041 | Pandia et al. | Mar 2011 | A1 |
20110077497 | Oster et al. | Mar 2011 | A1 |
20110082842 | Groseclose, Jr. et al. | Apr 2011 | A1 |
20110105861 | Derchak et al. | May 2011 | A1 |
20110112379 | Li et al. | May 2011 | A1 |
20110144470 | Mazar et al. | Jun 2011 | A1 |
20110160548 | Forster | Jun 2011 | A1 |
20110160601 | Wang et al. | Jun 2011 | A1 |
20110208076 | Fong et al. | Aug 2011 | A1 |
20110224564 | Moon et al. | Sep 2011 | A1 |
20110237922 | Parker, III et al. | Sep 2011 | A1 |
20110237924 | McGusty et al. | Sep 2011 | A1 |
20110245699 | Snell et al. | Oct 2011 | A1 |
20110245711 | Katra et al. | Oct 2011 | A1 |
20110288605 | Kaib et al. | Nov 2011 | A1 |
20110313305 | Rantala | Dec 2011 | A1 |
20120003933 | Baker et al. | Jan 2012 | A1 |
20120029300 | Paquet | Feb 2012 | A1 |
20120029306 | Paquet et al. | Feb 2012 | A1 |
20120029309 | Paquest et al. | Feb 2012 | A1 |
20120029314 | Paquet et al. | Feb 2012 | A1 |
20120029315 | Raptis et al. | Feb 2012 | A1 |
20120029316 | Raptis et al. | Feb 2012 | A1 |
20120035432 | Katra et al. | Feb 2012 | A1 |
20120059668 | Baldock et al. | Mar 2012 | A1 |
20120078127 | McDonald et al. | Mar 2012 | A1 |
20120088998 | Bardy et al. | Apr 2012 | A1 |
20120088999 | Bishay et al. | Apr 2012 | A1 |
20120089000 | Bishay et al. | Apr 2012 | A1 |
20120089001 | Bishay et al. | Apr 2012 | A1 |
20120089037 | Bishay et al. | Apr 2012 | A1 |
20120089412 | Bishay et al. | Apr 2012 | A1 |
20120089417 | Bardy et al. | Apr 2012 | A1 |
20120095352 | Tran | Apr 2012 | A1 |
20120101358 | Boettcher et al. | Apr 2012 | A1 |
20120101396 | Solosko et al. | Apr 2012 | A1 |
20120108993 | Gordon et al. | May 2012 | A1 |
20120165645 | Russel et al. | Jun 2012 | A1 |
20120172695 | Ko et al. | Jul 2012 | A1 |
20120179665 | Baarman et al. | Jul 2012 | A1 |
20120184207 | Gaines | Jul 2012 | A1 |
20120220835 | Chung | Aug 2012 | A1 |
20120232929 | Experton | Sep 2012 | A1 |
20120238910 | Nordstrom | Sep 2012 | A1 |
20120253847 | Dell'Anno et al. | Oct 2012 | A1 |
20120265080 | Yu et al. | Oct 2012 | A1 |
20120265738 | Beckmann et al. | Oct 2012 | A1 |
20120302906 | Felix et al. | Nov 2012 | A1 |
20120306662 | Vosch et al. | Dec 2012 | A1 |
20120330126 | Hoppe et al. | Dec 2012 | A1 |
20130041272 | Javier et al. | Feb 2013 | A1 |
20130077263 | Oleson et al. | Mar 2013 | A1 |
20130079611 | Besko | Mar 2013 | A1 |
20130079618 | Sandmore et al. | Mar 2013 | A1 |
20130085347 | Manicka et al. | Apr 2013 | A1 |
20130085403 | Gunderson et al. | Apr 2013 | A1 |
20130087609 | Nichol et al. | Apr 2013 | A1 |
20130096395 | Katra et al. | Apr 2013 | A1 |
20130116533 | Lian et al. | May 2013 | A1 |
20130123651 | Bardy | May 2013 | A1 |
20130124891 | Donaldson | May 2013 | A1 |
20130131530 | Brockway et al. | May 2013 | A1 |
20130158361 | Bardy | Jun 2013 | A1 |
20130172763 | Wheeler | Jul 2013 | A1 |
20130197380 | Oral et al. | Aug 2013 | A1 |
20130225963 | Kodandaramaiah et al. | Aug 2013 | A1 |
20130225966 | Barber et al. | Aug 2013 | A1 |
20130231947 | Shusterman | Sep 2013 | A1 |
20130243105 | Lei et al. | Sep 2013 | A1 |
20130274565 | Langer et al. | Oct 2013 | A1 |
20130274584 | Finlay et al. | Oct 2013 | A1 |
20130275158 | Fahey | Oct 2013 | A1 |
20130324809 | Lisogurski et al. | Dec 2013 | A1 |
20130324855 | Lisogurski et al. | Dec 2013 | A1 |
20130324856 | Lisogurski et al. | Dec 2013 | A1 |
20130325081 | Karst et al. | Dec 2013 | A1 |
20130325359 | Jarverud et al. | Dec 2013 | A1 |
20130331665 | Libbus et al. | Dec 2013 | A1 |
20130338448 | Libbus et al. | Dec 2013 | A1 |
20130338472 | Barber et al. | Dec 2013 | A1 |
20140002234 | Alwan | Jan 2014 | A1 |
20140005502 | Klap et al. | Jan 2014 | A1 |
20140012154 | Mazar et al. | Jan 2014 | A1 |
20140031663 | Gallego | Jan 2014 | A1 |
20140056452 | Moss et al. | Feb 2014 | A1 |
20140088399 | Lian et al. | Mar 2014 | A1 |
20140107509 | Banet et al. | Apr 2014 | A1 |
20140121557 | Gannon et al. | May 2014 | A1 |
20140140359 | Kalevo et al. | May 2014 | A1 |
20140148718 | Stickney et al. | May 2014 | A1 |
20140180027 | Buller | Jun 2014 | A1 |
20140189928 | Oleson et al. | Jul 2014 | A1 |
20140194760 | Albert | Jul 2014 | A1 |
20140206977 | Bahney et al. | Jul 2014 | A1 |
20140213937 | Bianchi et al. | Jul 2014 | A1 |
20140214134 | Peterson | Jul 2014 | A1 |
20140215246 | Lee et al. | Jul 2014 | A1 |
20140249852 | Proud | Sep 2014 | A1 |
20140296651 | Stone | Oct 2014 | A1 |
20140297310 | Collins | Oct 2014 | A1 |
20140318699 | Longinotti-Buitoni et al. | Oct 2014 | A1 |
20140330147 | Ousdigian et al. | Nov 2014 | A1 |
20140343390 | Berzowska et al. | Nov 2014 | A1 |
20140358193 | Lyons et al. | Dec 2014 | A1 |
20140364756 | Brockway et al. | Dec 2014 | A1 |
20150018660 | Thomson et al. | Jan 2015 | A1 |
20150048836 | Guthrie et al. | Feb 2015 | A1 |
20150051472 | Wang et al. | Feb 2015 | A1 |
20150065842 | Lee et al. | Mar 2015 | A1 |
20150094558 | Russell | Apr 2015 | A1 |
20150142090 | Duijsens et al. | May 2015 | A1 |
20150164349 | Gopalakrishnan et al. | Jun 2015 | A1 |
20150165211 | Naqvi et al. | Jun 2015 | A1 |
20150177175 | Elder et al. | Jun 2015 | A1 |
20150202351 | Kaplan et al. | Jul 2015 | A1 |
20150250422 | Bay | Sep 2015 | A1 |
20150257670 | Ortega et al. | Sep 2015 | A1 |
20150305676 | Shoshani | Nov 2015 | A1 |
20150324690 | Chilimbi et al. | Nov 2015 | A1 |
20150335285 | Poon et al. | Nov 2015 | A1 |
20150359489 | Baudenbacher et al. | Dec 2015 | A1 |
20160135746 | Kumar et al. | May 2016 | A1 |
20160144190 | Cao et al. | May 2016 | A1 |
20160144192 | Sanghera et al. | May 2016 | A1 |
20160150982 | Roy | Jun 2016 | A1 |
20160196479 | Chertok et al. | Jul 2016 | A1 |
20160217369 | Annapureddy et al. | Jul 2016 | A1 |
20160217691 | Kadobayashi et al. | Jul 2016 | A1 |
20160235318 | Sarkar | Aug 2016 | A1 |
20170056650 | Cohen et al. | Mar 2017 | A1 |
20170065207 | Landherr et al. | Mar 2017 | A1 |
20170112399 | Brisben et al. | Apr 2017 | A1 |
20170112401 | Rapin et al. | Apr 2017 | A1 |
20170127964 | Moorman | May 2017 | A1 |
20170156592 | Fu | Jun 2017 | A1 |
20170032221 | Wu et al. | Jul 2017 | A1 |
20180020931 | Shusterman | Jan 2018 | A1 |
20180116537 | Sullivan et al. | May 2018 | A1 |
20180192965 | Rose et al. | Jul 2018 | A1 |
20190021671 | Kumar et al. | Jan 2019 | A1 |
20190117068 | Thomson et al. | Apr 2019 | A1 |
Number | Date | Country |
---|---|---|
19955211 | May 2001 | DE |
1859833 | Nov 2007 | EP |
2438851 | Apr 2012 | EP |
2438852 | Apr 2012 | EP |
2465415 | Jun 2012 | EP |
2589333 | May 2013 | EP |
H06319711 | Nov 1994 | JP |
H11188015 | Jul 1999 | JP |
2004129788 | Apr 2004 | JP |
2007082938 | Apr 2007 | JP |
2009219554 | Oct 2009 | JP |
199852463 | Nov 1998 | WO |
0078213 | Dec 2000 | WO |
2003032192 | Apr 2003 | WO |
2006009767 | Jan 2006 | WO |
2006014806 | Feb 2006 | WO |
2007066270 | Jun 2007 | WO |
2007092543 | Aug 2007 | WO |
2008010216 | Jan 2008 | WO |
2008057884 | May 2008 | WO |
2008092098 | Jul 2008 | WO |
2009036306 | Mar 2009 | WO |
2009036313 | Mar 2009 | WO |
2009036327 | Mar 2009 | WO |
2009112976 | Sep 2009 | WO |
2009112978 | Sep 2009 | WO |
2009112979 | Sep 2009 | WO |
2009142975 | Nov 2009 | WO |
2010066507 | Jun 2010 | WO |
2010105045 | Jun 2010 | WO |
2010104952 | Sep 2010 | WO |
2011047207 | Apr 2011 | WO |
2012040487 | Mar 2012 | WO |
2012112407 | Aug 2012 | WO |
2012140559 | Oct 2012 | WO |
2012146957 | Nov 2012 | WO |
2017072250 | May 2017 | WO |
Entry |
---|
15 of the Hottest Wearable Gadgets, URL <http://thehottestgadgets.com/2008/09/the-15-hottest-wearable-gadgets-001253> (Web page cached on Sep. 27, 2008). |
Alivecor, URL <http://www.businesswire.com/news/home/20121203005545/en/AliveCor%E2%80%99s-Heart-Monitor-Phone-Receives-FDA-Clearance#.U7rtq7FVTyF> (Dec. 3, 2012). |
Bharadwaj et al., Techniques for Accurate ECG signal processing, EE Times, URL <www.eetimes.com/document.asp?doc_id=1278571 > (Feb. 14, 2011). |
Chen et al. “Monitoring Body Temperature of Newborn Infants at Neonatal Intensive Care Units Using Wearable Sensors,” BodyNets2010, Corfu Island, Greece. Sep. 10-12, 1210. |
Epstein, Andrew E. et al.; ACC/AHA/HRS 2008 Guidelines for Device-Based Therapy of Cardiac Rhythm Abnormalities. J. Am. Coll. Cardiol. 2008; 51; eI-e62, 66 Pgs. |
Fitbit Tracker, URL <http://www.fitbit.com/> (Web page cached on Sep. 10, 2008.). |
Smith, Jawbone Up, URL <http://www.businessinsider.com/fitbit-flex-vs-jawbone-up-2013-5?op=1> (Jun. 1, 2013). |
Kligfield, Paul et al., Recommendations for the Standardization and Interpretation of the Electrocardiogram: Part I. J.Am.Coll. Cardiol; 2007; 49; 1109-27, 75 Pgs. |
Lauren Gravitz, “When Your Diet Needs a Band-Aid, ”Technology Review, MIT. (May 1, 2009). |
Lieberman, Jonathan, “How Telemedicine Is Aiding Prompt ECG Diagnosis in Primary Care,” British Journal of Community Nursing, vol. 13, No. 3, Mar. 1, 2008 (Mar. 1, 2008), pp. 123-126, XP009155082, ISSN: 1462-4753. |
McManus et al., “A Novel Application for the Detection of an Irregular Pulse using an iPhone 4S in Patients with Atrial Fibrillation,” vol. 10(3), pp. 315-319 (Mar. 2013.). |
Nike+ Fuel Band, URL <http://www.nike.com/us/en_us/c/nikeplus-fuelband> (Web page cached on Jan. 11, 2013.). |
P. Libby et al.,“Braunwald's Heart Disease—a Textbook of Cardiovascular Medicine,” Chs. 11, pp. 125-148 and 12, pp. 149-193 (8th ed. 2008), American Heart Association. |
Initial hands-on with Polar Loop activity tracker, URL <http://www.dcrainmaker.com/2013/09/polar-loop-firstlook.html> (Sep. 17, 2013). |
Seifert, Dan, Samsung dives into fitness wearable with the Gear Fit/ The Verge, URL <http://www.theverge.com/2014/2/24/5440310/samsung-dives-into-fitness-wearables-with-the-gear-fit> (Feb. 24, 2014). |
Soper, Taylor, Samsung's new Galaxy S5 flagship phone has fingerprint reader, heart rate monitor, URL <http://www.geekwire.com/2014/samsung-galaxy-s5-fingerprint> (Feb. 24, 2014). |
Dolcourt, See the Samsung Galaxy S5's Heart rate monitor in action, URL <http://www.cnet.com/news/see-the-samsung-galaxy-s5s-heart-rate-monitor-in-action> (Feb. 25, 2014). |
Sittig et al., “A Computer-Based Outpatient Clinical Referral System,” International Journal of Medical Informatics, Shannon, IR, vol. 55, No. 2, Aug. 1, 1999, pp. 149-158, XO004262434, ISSN: 1386-5056(99)00027-1. |
Sleepview, URL <http://www.clevemed.com/sleepview/overview.shtml> (Web page cached on Sep. 4, 2013.). |
Actigraphy/ Circadian Rhythm SOMNOwatch, URL <http://www.somnomedics.eu/news-events/publications/somnowatchtm.html> (Web page cached on Jan. 23, 2010). |
Zio Event Card, URL <http://www.irhythmtech.com/zio-solution/zio-event/> (Web page cached on Mar. 11, 2013.). |
Zio Patch System, URL <http://www.irhythmtech.com/zio-solution/zio-system/index.html> (Web page cached on Sep. 8, 2013.). |
Saadi et al. “Heart Rhythm Analysis Using ECG Recorded With a Novel Sternum Based Patch Technology—a Pilot Study.” Cardio technix 2013—Proceedings of the International Congress on Cardiovascular Technologies, Sep. 20, 2013. |
Anonymous. Omegawave Launches Consumer App 2.0 in U.S. “Endurance Sportswire—Endurance Sportswire.” Jul. 11, 2013. URL:http://endurancesportswire.com/omegawave-launches-consumer-app-2-0-in-u-s/. |
Chan et al. “Wireless Patch Sensor for Remote Monitoring of Heart Rate, Respiration, Activity, and Falls.” pp. 6115-6118. 2013 35th Annual International Conference of the IEEE Engineering in Medical and Biology Society. |
Wei et al. “A Stretchable and Flexible System for Skin-Mounted Measurement of Motion Tracking and Physiological Signals.” pp. 5772-5775. 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Aug. 26, 2014. |
Daoud et al. “Fall Detection Using Shimmer Technology and Multiresolution Analysis.” Aug. 2, 2013. URL: https://decibel.ni.com/content/docs/DOC-26652. |
Libbus. “Adherent Cardiac Monitor With Wireless Fall Detection for Patients With Unexplained Syncope.” Abstracts of the First AMA-IEEE Medical Technology Conference on Individualized Healthcare. May 22, 2010. |
Duttweiler et al., “Probability Estimation in Arithmetic and Adaptive-Huffman Entropy Coders,” IEEE Transactions on Image Processing. vol. 4, No. 3, Mar. 1, 1995, pp. 237-246. |
Gupta et al., “An ECG Compression Technique for Telecardiology Application,” India Conference (INDICON), 2011 Annual IEEE, Dec. 16, 2011, pp. 1-4. |
Nave et al., “ECG Compression Using Long-Term Prediction,” IEEE Transactions on Biomedical Engineering, IEEE Service Center, NY, USA, vol. 40, No. 9, Sep. 1, 1993, pp. 877-885. |
Skretting et al., “Improved Huffman Coding Using Recursive Splitting,” NORSIG, Jan. 1, 1999. |
A Voss et al., “Linear and Nonlinear Methods for Analyses of Cardiovascular Variability in Bipolar Disorders,” Bipolar Disorders, votl. 8, No. 5p1, Oct. 1, 2006, pp. 441-452, XP55273826, DK ISSN: 1398-5647, DOI: 10.1111/i.1399-5618.2006.00364.x. |
Varicrad-Kardi Software User's Manual Rev. 1.1, Jul. 8, 2009 (Jul. 8, 2009), XP002757888, retrieved from the Internet: URL:http://www.ehrlich.tv/KARDiVAR-Software.pdf [retrieved on May 20, 2016]. |
Vedapulse UK, Jan. 1, 2014 (Jan. 1, 2014), XP002757887, Retrieved from the Internet: URL:http://www.vedapulseuk.com/diagnostic/ [retrieved on May 19, 2016]. |
http://www.originlab.com/origin#Data_Exploration 2015. |
https://web.archive.org/web/20130831204020/http://www.biopac.com/research.asp?CatID=37&Main=Software (Aug. 2013). |
http://www.gtec.at/Products/Software/g.BSanalyze-Specs-Features (2014). |
ADINSTRUMENTS:ECG Analysis Module for LabChart & PowerLab, 2008. |
BIOPAC Systems, Inc. #AS148—Automated ECG Analysis , Mar. 24, 2006. |
Health Research—Hexoskin Biometric Shirt | Hexoskin URL:http://www.hexoskin.com/pages/health-research (Web page cached on Dec. 2, 2014). |
Jacob Kastrenakes, “Apple Watch uses four sensors to detect your pulse,” Sep. 9, 2014. URL: http://www.theverge.com/2014/9/9/6126991/apple-watch-four-back-sensors-detect-activity. |
Nicole Lee, “Samsung Gear S review: an ambitious and painfully flawed smartwatch,” Dec. 1, 2014. URL: http://www.engadget.com/2014/12/01/samsung-gear-s-review/. |
G. G. Ivanov, “HRV Analysis Under the Usage of Different Electrocardiopraphy Systems,” Apr. 15, 2008 (Apr. 15, 2008), XP55511209, Retrieved from the Internet: URL:http://www.drkucera.eu/upload_doc/hrv_analysis_(methodical_recommendations).pdf [retrieved on Oct. 1, 2018]. |
May 24, 2022 Letter to Opposing Counsel. 1:22-cv-00351-CFC. May 24, 2022. |
Complaint from Case No. 1:22-cv-00351-UNA, Bardy Diagnostics, Inc. (Plaintiff) v. Vital Connect, Inc. (Defendant), Filed: Mar. 18, 2022, 182 pages. |
Defendant's Opening Brief in Support of Its Motion to Dismiss for Failure to State a Claim from Case No. 1:22-ov-00351-CFC, Bardy Diagnostics, Inc. (Plaintiff) v. Vital Connect, Inc. (Defendant), Filed: May 25, 2022, 18 pages. |
Defendant's Answer, Defenses, and Counterclaim from Case No. 1:22-cv-00351-CFC, Bardy Diagnostics, Inc. (Plaintiff) v. Vital Connect, Inc. (Defendant), Filed: May 25, 2022, 132 pages. |
Plaintiffs Answering Brief in Opposition to Defendant's Motion to Dismiss for Failure to State a Claim from Case No. 1:22-cv-00351-CFC, Bardy Diagnostics, Inc. (Plaintiff) v. Vital Connect, Inc. (Defendant), Filed: Jun. 8, 2022, 25 pages. |
Plaintiffs Answer to Defendant's Counterclaim from Case No. 1:22-cv-00351-CFC, Bardy Diagnostics, Inc. (Plaintiff) v. Vital Connect, Inc. (Defendant), Filed: Jun. 15, 2022, 5 pages. |
Defendant's Reply Brief in Support of Its Motion to Dismiss for Failure to State a Claim from Case No. 1:22-cv-00351-CFC, Bardy Diagnostics, Inc. (Plaintiff) v. Vital Connect, Inc. (Defendant), Filed: Jun. 15, 2022, 93 pages. |
Dwayne C. Leonard, a Framework for the Creation of a Unified Electronic Medical Record Using Biometrics, Data Fusion and Belief Theory, 2007, https://dialog.proquest.com/professional/docview/304852676/17AEEF1F9382EF1C4E5/6?accountid=131444 (last visited Aig 27, 2021) (Year: 2007). |
May 2, 2022 Letter From Counsel. 1:22-cv-00351-CFC. May 2, 2022. |
Wallot et al., “Using Complexity Metrics With R-R Intervals and BPM Heart Rate Measures,” Frontiers in Physiology, vol. 4, Article 211, pp. 1-8, Aug. 13, 2013. 2013. |
https://www.meddeviceonline.com/doc/medtronic-launches-world-s-first-app-based-remote-monitoring-system-for-pacemakers-0001. Nov. 18, 2015. |
https://fccid.io/LF524950/User-Manual/User-Manual-1944573 © Medtronic, Inc. 2012. |
Dan Sapoznikov et al., “Comparison of Different Methodologies of Heart Rate Variability Analysis,” Department of Cardiology, Hadassah University Hospital, P.O.B. 12000, Ein Kerem, Jerusalem 91120, Israel (1993). |
Jeffrey J. Goldberger, MD, FHRS, et al., “Comparison of the Physiologic and Prognostic Implications of the Heart Rate Versus the RR Interval,” Heart Rhythm, Elseview, US, vol. 11, No. 11, Jul. 30, 2014 (Jul. 30, 2014), pp. 1925-1933, XP029082764, ISSN: 1547-5271, DOI: 10.1016/J.HRTHM.2014.07.037 (2014). |
Helmut Purerfellner et al.: “Miniaturized Reveal LINQ insertable cardiac monitoring system: First-in-human experience,” Heart Rhythm, vol. 12. No. 6, Jun. 1, 2015 (Jun. 1, 2015), pp. 1113-1119, XP055732303, US ISSN: 1547-5271, DOI: 10.1016/j.hrthm.2015.02.030. |
Oct. 17, 2022 Letter to Opposing Counsel, Bardy Diagnostics, Inc. v. Vital Connect, Inc., No. 22-cv-00351-CFC (D. Del.), Oct. 17, 2022. |
Nov. 11, 2022, Letter from Opposing Counsel, 1:22-cv-00351-CJB; Bardy Diagnostics, Inc. v. Vital Connect, Inc. (D. Del.), Nov. 11, 2022. |
Dec. 26, 2022 Letter from Opposing Counsel, 1:22-cv-00351-CJB; Bardy Diagnostics, Inc. v. Vital Connect, Inc. (D. Del.); and IPR2023-00381; Vital Connect, Inc. v. Bardy Diagnostics, Inc. (P.T.A B ), Dec. 26, 2022. |
First Amended Complaint for Patent Infringement, 1:22-cv-00351-CJB, Bardy Diagnostics, Inc. v. Vital Connect, Inc. (D. Del.), filed Jan. 10, 2023. |
Petition for Inter Partes Review of U.S. Pat. No. 11,051,743 Pursuant To 35 U.S.C. §§ 311-319 and 37 C.F.R. §42, Case No. IPR2023-00381, Vital Connect, Inc. v. Bardy Diagnostics, Inc. (P.T.A.B.), Dec. 21, 2022, 875 pages. |
Defendant's Answer to First Amended Complaint, Defenses, and Counterclaim, 1:22-cv-00351-CJB, Bardy Diagnostics, Inc. v. Vital Connect, Inc. (D. Del.), filed Jan. 24, 2023 (227 pages). |
Number | Date | Country | |
---|---|---|---|
20200367780 A1 | Nov 2020 | US |
Number | Date | Country | |
---|---|---|---|
62132497 | Mar 2015 | US | |
61882403 | Sep 2013 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 16102608 | Aug 2018 | US |
Child | 16989180 | US | |
Parent | 15231752 | Aug 2016 | US |
Child | 16102608 | US | |
Parent | 15066883 | Mar 2016 | US |
Child | 15231752 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 14997416 | Jan 2016 | US |
Child | 15066883 | US | |
Parent | 14614265 | Feb 2015 | US |
Child | 14997416 | US | |
Parent | 14488230 | Sep 2014 | US |
Child | 14614265 | US | |
Parent | 14080725 | Nov 2013 | US |
Child | 14488230 | US |