Abstract: A monitor recorder-implemented method for electrocardiography data compression and an electrocardiography monitor recorder with integral data compression are provided. A series of data items are obtained, each of the data items associated with a magnitude of an ECG signal sensed by a monitor recorder. A range is set for an initial one of the data items in the series. Each of the data items remaining in the series is processed, including: obtaining an estimation of probabilities of the data items appearing next to that data item in the series; dividing the further range into sub-ranges, each sub-range representing a fraction of the further range proportional to the probabilities of the next data items; selecting the sub-range corresponding to the data item next to that data item in the series; and representing the next data item by the selected sub-range in a non-volatile memory.

Abstract: In one embodiment, an ambulatory encoding monitor recorder optimized for rescalable encoding and a method of use are provided. The monitor recorder includes a memory configured to store a plurality of codes and a plurality of electrocardiographic values associated with each of the codes; and a micro-processor configured to obtain electrocardiographic values during a sequence of temporal windows and to process the electrocardiographic values within each of the windows, the processing including: perform a mathematical operation on two of the electrocardiographic values; analyze a result of each of the mathematical operations; based on the analysis, adjust the plurality of the electrocardiographic values associated with each of the codes; encode each of the electrocardiography values within that window with one of the codes based on the adjusted plurality of the electrocardiographic values associated with that code; and write each of the codes into a sequence in the memory.

Abstract: An electrocardiography monitor configured for self-optimizing ECG data compression is provided. ECG waveform characteristics are rarely identical in patients with cardiac disease making this innovation crucial for the long-term data storage and analysis of complex cardiac rhythm disorders. The monitor includes a memory and a micro-controller operable to execute under a micro-programmable control and configured to: obtain a series of electrode voltage values; select one or more of a plurality of compression algorithms for compressing the electrode voltage series; apply one or more of the selected compression algorithms to the electrode voltage series; evaluate a degree of compression of the electrode voltage series achieved using the application of the selected algorithms; apply one or more of the compression algorithms to the compressed electrode voltage series upon the degree of compression not meeting a predefined threshold; and store the compressed electrode voltage series within the memory.

Abstract: A system and method for classifier-based atrial fibrillation detection with the aid of a digital computer are provided. Electrocardiography (ECG) features and annotated patterns of the features are maintained in a database, at least some of the patterns associated with atrial fibrillation. A classifier is trained based on the annotated patterns. A representation of an ECG signal recorded by one or more ambulatory monitors is received. ECG features in the representation falling within each of the temporal windows are detected. The trained classifier is used to identify patterns of the ECG features. At least one matrix with weights for the patterns are generated. A value indicative of whether portions of the representation are associated the patient experiencing atrial fibrillation is calculated. That one or more of the portions are associated with the patient experiencing atrial fibrillation is determined. An action is taken based on one or more of the determinations.

Abstract: A system for secure physiological data acquisition and delivery is provided. The system includes a monitoring patch that includes a flexible backing; a pair of electrocardiographic electrodes included on a contact surface of each end of the flexible backing; a receptacle affixed to a non-contacting surface of the flexible backing and including an electro-mechanical docking interface for interfacing with a monitor recorder; a pair of flexible circuit traces affixed at each end of the flexible backing with each circuit trace connecting one of the electrocardiographic electrodes to the electro-mechanical docking interface; and a circuit operable to store an identifier associated with the patch and an encrypted password necessary to access physiological monitoring data obtained using the patch identified by that identifier, the circuit configured to provide via the electro-mechanical docking interface the password and the identifier to the monitor recorder.

Abstract: A system and method for facilitating a cardiac rhythm disorder diagnosis based on subcutaneous cardiac monitoring data with the aid of a digital computer are provided. Cutaneous action potentials of a patient are recorded as electrocardiogram (EGC) data over a set time period using a subcutaneous insertable cardiac monitor. A set of R-wave peaks is identified within the ECG data and an R-R interval plot is constructed. A difference between recording times of successive pairs of the R-wave peaks in the set is determined. A heart rate associated with each difference is also determined. The pairs of the R-wave peaks and associated heart rate are plotted as the R-R interval plot. A diagnosis of cardiac disorder is facilitated based on patterns of the plotted pairs of the R-wave peaks and the associated heart rates in the R-R interval plot.

Abstract: A system and method for applying a uniform dynamic gain over cardiac data with the aid of a digital computer is provided. A time series of a plurality of voltage values that comprises a digital representation of a raw electrocardiography (“ECG”) signal recorded by an ambulatory monitor recorder is obtained by an least one computer processor, the time series including segments of noise and segments of non-noise. The segments of non-noise are analyzed by the at least one computer processor and a single gain factor for all of the values in the analyzed non-noise segments is determined by the at least one computer processor based on the analysis. The single gain factor to all of the values in the non-noise segments is applied by the at least one computer processor.

Abstract: A system for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer is provided. A download station retrieves cutaneous action potentials of a patient recorded over a time by an ECG device as ECG data. An R-R interval plot of the ECG data includes R-R intervals plotted along an x-axis of the plot and heart rates associated with the R-R intervals plotted along a y-axis. The R-R intervals are calculated as a difference between recording times of successive pairs of R-wave peaks. Each heart rate is associated with each time difference. One or more portions of the R-R intervals are identified in the plot. Each portion of the R-R intervals includes a cardiac event. Report strips are generated and each includes one portion of the R-R intervals and a portion of the ECG data. The report strips are included in a cardiac report for the patient.

Abstract: A system and method for machine-learning based atrial fibrillation detection are provided. A database is maintained that is operable to maintain a plurality of ECG features and annotated patterns of the features. At least one server is configured to: train a classifier based on the annotated patterns in the database; receive a representation of an ECG signal recorded by an ambulatory monitor recorder during a plurality of temporal windows; detect a plurality of the ECG features in at least some of the portions of the representation falling within each of the temporal windows; use the trained classifier to identify patterns of the ECG features within one or more of the portions of the ECG signal; for each of the portions, calculate a score indicative of whether the portion of the representation within that ECG signal is associated the patient experiencing atrial fibrillation; and take an action based on the score.

Abstract: A method for secure physiological data acquisition and storage is provided. An identifier of a physiological monitoring device that is configured to store the identifier within a cryptographic circuit is obtained by a programming wand. A password for accessing physiological monitoring data collected using that device is generated based on at least a portion of the identifier. The password is encrypted using a secret key, and password is loaded into the cryptographic circuit. The secret key is loaded into a monitor recorder, wherein the monitor recorder retrieves the identifier and the password from the device, decodes the password, and offloads the physiological monitoring data together with the identifier and the decoded password. The identifier and the password are reported to at least one server. The offloaded physiological monitoring data is stored using the identifier. Access to the data is granted upon receipt of the decoded password from a user.

Abstract: A system and method for facilitating a cardiac rhythm disorder diagnosis based on subcutaneous cardiac monitoring data with the aid of a digital computer are provided. Cutaneous action potentials of a patient are recorded as electrocardiogram (EGC) data over a set time period using a subcutaneous insertable cardiac monitor. A set of R-wave peaks is identified within the ECG data and an R-R interval plot is constructed. A difference between recording times of successive pairs of the R-wave peaks in the set is determined. A heart rate associated with each difference is also determined. The pairs of the R-wave peaks and associated heart rate are plotted as the R-R interval plot. A diagnosis of cardiac disorder is facilitated based on patterns of the plotted pairs of the R-wave peaks and the associated heart rates in the R-R interval plot.

Abstract: A method for secure physiological data acquisition and storage is provided. An identifier of a physiological monitoring device that is configured to store the identifier within a cryptographic circuit is obtained by a programming wand. A password for accessing physiological monitoring data collected using that device is generated based on at least a portion of the identifier. The password is encrypted using a secret key, and password is loaded into the cryptographic circuit. The secret key is loaded into a monitor recorder, wherein the monitor recorder retrieves the identifier and the password from the device, decodes the password, and offloads the physiological monitoring data together with the identifier and the decoded password. The identifier and the password are reported to at least one server. The offloaded physiological monitoring data is stored using the identifier. Access to the data is granted upon receipt of the decoded password from a user.

Abstract: A system and method for ECG data classification for use in facilitating diagnosis of cardiac rhythm disorders is provided. ECG data is obtained via an electrocardiography monitor shaped for placement on a patient's chest. The ECG data is divided into segments and noise detection analysis is applied to the ECG data segments. A noise classification or a valid classification is assigned to each segment of the ECG data. At least one ECG data segment assigned the noise classification and that includes ECG data that corresponds with feedback from the patient via the electrocardiography monitor is identified. The ECG data that corresponds with the patient feedback is removed from the identified ECG data segment with the noise classification. The ECG data segments assigned the noise classification are removed from further analysis.

Abstract: A system and method for secure physiological data acquisition and storage. An identifier of a physiological monitoring patch is obtained by a programming wand, the patch configured to store the identifier within a cryptographic circuit. A password for accessing physiological monitoring data collected using that patch is generated based on at least a portion of the identifier, the password is encrypted using a secret key, and the encrypted password is loaded into the cryptographic circuit. The key is loaded onto a monitor recorder that couples with the patch and obtains the physiological monitoring data using the patch, wherein the monitor recorder offloads the data together with the identifier and the decoded password. The identifier and the password are reported to a server that stores the offloaded physiological monitoring data using the identifier within a secure database and grants access to the data upon receipt of the decoded password.

Abstract: Electronic medical records (EMRs) with the results of the monitoring can be stored in a cloud-computing environment. All communications with the cloud-computing environment are performed via a secure connection. Each of the EMRs can be associated with an identifier that is provided with the results of the monitoring data. The EMRs can be created, viewed, and modified using a mobile application. The mobile application can use a scanner in the mobile device on which the application executes to obtain an identifier and uses the identifier to direct actions of the user towards the appropriate EMR. The mobile application can further provide additional user access verification. Alerts can further be provided through the mobile application. The mobile application deletes from the mobile device all information that has been transmitted or received from the cloud-computing environment once the information is no longer used.

Abstract: A system and method for ECG data classification for use in facilitating diagnosis of cardiac rhythm disorders is provided. ECG data is obtained via an electrocardiography monitor with a patient button. A press of the patient button is identified within the ECG data. A button window with a segment of data prior to and after the button press is defined within the ECG data. The ECG data is divided into blocks. Noise detection analysis is applied to the data blocks. A classification of noise or valid data is assigned to each data block based on the noise detection analysis. At least one data block that overlaps the button window is assigned the noise classification. The at least one data block is trimmed to align with one of the start and end of the button window. The trimmed blocks assigned with the noise classification are removed from the data.

Abstract: A system and method for machine-learning based atrial fibrillation detection are provided. A database is maintained that is operable to maintain a plurality of ECG features and annotated patterns of the features. At least one server is configured to: train a classifier based on the annotated patterns in the database; receive a representation of an ECG signal recorded by an ambulatory monitor recorder during a plurality of temporal windows; detect a plurality of the ECG features in at least some of the portions of the representation falling within each of the temporal windows; use the trained classifier to identify patterns of the ECG features within one or more of the portions of the ECG signal; for each of the portions, calculate a score indicative of whether the portion of the representation within that ECG signal is associated the patient experiencing atrial fibrillation; and take an action based on the score.

Abstract: A system and method for facilitating a cardiac rhythm disorder diagnosis based on subcutaneous cardiac monitoring data with the aid of a digital computer are provided. Cutaneous action potentials of a patient are recorded as electrocardiogram (EGC) data over a set time period using a subcutaneous insertable cardiac monitor. A set of R-wave peaks is identified within the ECG data and an R-R interval plot is constructed. A difference between recording times of successive pairs of the R-wave peaks in the set is determined. A heart rate associated with each difference is also determined. The pairs of the R-wave peaks and associated heart rate are plotted as the R-R interval plot. A diagnosis of cardiac disorder is facilitated based on patterns of the plotted pairs of the R-wave peaks and the associated heart rates in the R-R interval plot.

Abstract: A system and method for applying a uniform dynamic gain over cardiac data with the aid of a digital computer is provided. A time series of a plurality of voltage values that comprises a digital representation of a raw electrocardiography (“ECG”) signal recorded by an ambulatory monitor recorder is obtained by an least one computer processor, the time series including segments of noise and segments of non-noise. The segments of non-noise are analyzed by the at least one computer processor and a single gain factor for all of the values in the analyzed non-noise segments is determined by the at least one computer processor based on the analysis. The single gain factor to all of the values in the non-noise segments is applied by the at least one computer processor.

Abstract: A system and method for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer is provided. A plurality of R-wave peaks are identified in a set of ECG data and a difference between recording times of successive pairs of the R-wave peaks are calculated as R-R intervals. A heart rate associated with each time difference is determined. An R-R interval plot of the ECG data is formed. The R-R intervals are plotted along an x-axis of the R-R interval plot and the heart rates associated with the R-R intervals are plotted along a y-axis of the R-R interval plot. A diagnostic composite plot is generated, including the R-R interval plot, a near field view of a portion of the ECG data, and an intermediate field view of a different portion of the ECG data for diagnosis of a cardiac event.