Abstract: A method for continuous data transfer is provided. Data blocks are generated from a continuous data stream captured via a physiological monitoring device by segmenting data from the continuous data stream into the data blocks. A time at which the data associated with each data block occurs is determined and a sample number is associated with each data block. The data blocks are transmitted from the physiological monitoring device to a server. The data blocks are ordered on the server based on the time and the sample number associated with each data block.

Abstract: A system and method for physiological data classification for use in facilitating diagnosis is provided. A physiological monitor includes a feedback button and physiological data obtained via the physiological monitor is stored in a database. The physiological data is divided into segments and one or more data segments are classified as noise. A determination is made that at least one of the data segments classified as noise includes a marker indicating a press of the feedback button on the physiological monitor. A set of the physiological data including and surrounding the physiological data occurring during the press of the feedback button is identified within the data segment classified as noise. The identified set of physiological data is provided with the data segments classified as valid for analysis.

Abstract: A method for continuous data transfer is provided. Data blocks are generated from a continuous data stream captured via a physiological monitoring device by segmenting data from the continuous data stream into the data blocks. A time at which the data associated with each data block occurs is determined and a sample number is associated with each data block. The data blocks are transmitted from the physiological monitoring device to a server. The data blocks are ordered on the server based on the time and the sample number associated with each data block.

Abstract: A system and method for physiological data classification for use in facilitating diagnosis is provided. A physiological monitor includes a feedback button and physiological data obtained via the physiological monitor is stored in a database. The physiological data is divided into segments and one or more data segments are classified as noise. A determination is made that at least one of the data segments classified as noise includes a marker indicating a press of the feedback button on the physiological monitor. A set of the physiological data including and surrounding the physiological data occurring during the press of the feedback button is identified within the data segment classified as noise. The identified set of physiological data is provided with the data segments classified as valid for analysis.

Abstract: A system and method for atrial fibrillation detection in non-noise ECG data 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, the classifier implemented by a convolutional neural network. A representation of an ECG signal recorded by one or more ambulatory monitors is received. Noise is detected in the representations and ECG features in the representation falling within each of the non-noise temporal windows are detected. The trained classifier is used to identify patterns of the ECG features. 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.

Abstract: A system and method for remote ECG data streaming in real-time is provided. A continuous connection is established between a cloud-based server and a physiological monitor. The physiological monitor includes at least two electrodes and is affixed to a chest of a patient or implanted within the patient. ECG data is collected via one or more of the electrodes and encrypted via a wireless interface on the physiological monitor using a secret key stored on the physiological monitor. The encrypted ECG data is transmitted from the cloud-based server and received on a computing device in real-time.

Abstract: A subcutaneous and cutaneous electrocardiography monitor configured for self-optimizing ECG data compression is provided. The monitors include a housing, an electrocardiographic front end circuit, a memory, and a micro-controller configured to: obtain a series of electrode voltage values based on the sensed electrocardiographic signals; use a plurality of selection schemes to choose one or more of a plurality of compression algorithms associated with each of the selection scheme for testing; test the selected compression algorithms including applying the compression algorithms chosen using each of the selection schemes to a segment of the electrode voltage series; analyze results of the testing; select one or more compression algorithms chosen using one of the selection schemes for compressing at least a portion of the electrode voltage series based on the analysis; obtain a compression of at least the portion of the electrode voltage series; and store the compression within the memory.

Abstract: A system and method for display of subcutaneous cardiac monitoring data are provided. Cutaneous action potentials of a patient and other sensed data associated with the 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, the associated heart rates in the R-R interval plot, and background data based on the other sensed data.

Abstract: A system for facilitating a cardiac rhythm disorder diagnosis is provided. A download station is adapted to retrieve cutaneous action potentials of a patient recorded as ECG data. A plot of R-R interval data is generated based on the ECG data and displayed. A presentation of the R-R interval data in the display is changed by identifying a section of the R-R interval data and removing portions of the R-R interval data associated with an earlier recordation time than the R-R interval data in the section and a later recordation time than the R-R interval data in the section. The R-R interval data remaining in the display is provided in greater detail. Report strips are generated from the remaining R-R interval data and classified with a cardiac condition of the patient.

Abstract: A system and method for facilitating a cardiac rhythm disorder diagnosis with the aid of a digital computer is provided. 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.

Abstract: A subcutaneous and cutaneous electrocardiography monitor configured for self-optimizing ECG data compression is provided. The monitors include a housing, an electrocardiographic front end circuit, a memory, and a micro-controller configured to: obtain a series of electrode voltage values based on the sensed electrocardiographic signals; use a plurality of selection schemes to choose one or more of a plurality of compression algorithms associated with each of the selection scheme for testing; test the selected compression algorithms including applying the compression algorithms chosen using each of the selection schemes to a segment of the electrode voltage series; analyze results of the testing; select one or more compression algorithms chosen using one of the selection schemes for compressing at least a portion of the electrode voltage series based on the analysis; obtain a compression of at least the portion of the electrode voltage series; and store the compression within the memory.

Abstract: A system and method for atrial fibrillation detection in non-noise ECG data 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, the classifier implemented by a convolutional neural network. A representation of an ECG signal recorded by one or more ambulatory monitors is received. Noise is detected in the representations and ECG features in the representation falling within each of the non-noise temporal windows are detected. The trained classifier is used to identify patterns of the ECG features. 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.

Abstract: A system and method for display of subcutaneous cardiac monitoring data are provided. Cutaneous action potentials of a patient and other sensed data associated with the 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, the associated heart rates in the R-R interval plot, and background data based on the other sensed data.

Abstract: A system and method for neural-network-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, the classifier implemented by a convolutional neural network. 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.

Abstract: A subcutaneous 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: An ambulatory electrocardiography monitor is provided. The monitor includes a housing adapted to couple to a monitoring patch that includes electrocardiographic electrodes; and electronic circuitry provided within the housing. The electronic circuitry includes an electrocardiographic front end circuit; the microcontroller configured to: execute a power up sequence upon the housing coupling to the patch; after the execution of the power-up sequence, retrieve from the monitoring patch an identifier associated with the patch and a password for accessing results of a physiological monitoring conducted using the patch; read samples of the electrocardiographic signals, buffer the samples of the electrocardiographic signals, compress the buffered samples of the electrocardiographic signals, buffer the compressed samples of the electrocardiographic signals, and write-the buffered samples into a memory in association with the password and the identifier; and the memory electrically interfaced with the microcontroller.

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: 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: A method for continuous data transfer is provided. Data blocks are generated from a continuous data stream captured via a physiological monitoring device by segmenting data from the continuous data stream into the data blocks. A time at which the data associated with each data block occurs is determined and a sample number is associated with each data block. The data blocks are transmitted from the physiological monitoring device to a server. The data blocks are ordered on the server based on the time and the sample number associated with each data block.

Abstract: An ambulatory electrocardiography monitor is provided. The monitor includes a housing adapted to couple to a monitoring patch that includes electrocardiographic electrodes; and electronic circuitry provided within the housing. The electronic circuitry includes an electrocardiographic front end circuit; the microcontroller configured to: execute a power up sequence upon the housing coupling to the patch; after the execution of the power-up sequence, retrieve from the monitoring patch an identifier associated with the patch and a password for accessing results of a physiological monitoring conducted using the patch; read samples of the electrocardiographic signals, buffer the samples of the electrocardiographic signals, compress the buffered samples of the electrocardiographic signals, buffer the compressed samples of the electrocardiographic signals, and write-the buffered samples into a memory in association with the password and the identifier; and the memory electrically interfaced with the microcontroller.