Abstract: Methods, devices and program products are provided for under control of one or more processors within an implantable medical device (IMD). Sensing near field (NF) and far field (FF) signals are between first and second combinations of electrodes coupled to the IMD. The method applies an arrhythmia detection algorithm to the NF signals for identifying events within the NF signal and designates events marker based thereon and monitors the event markers to detect a candidate arrhythmia condition in the NF signals. The candidate under-detected condition comprises at least one of an under-detected arrhythmia or over-sensing. In response to detection of the candidate arrhythmia condition, the method analyzes the FF signals for a presence of an under-detected arrhythmia indicator. The method delivers an arrhythmia therapy based on the presence of the under-detected arrhythmia indicator in the FF signals and the candidate under-detected arrhythmia condition in the NF signals.

Abstract: Cardiac activity can be mapped by receiving an electrogram, transforming the electrogram into the wavelet domain (e.g., using a continuous wavelet transformation) to create a scalogram of the electrogram, computing at least one energy function of the scalogram, and computing at least one metric of the electrogram using the at least one energy function. The metrics of the electrogram can include, without limitation: a QRS activity duration for the electrogram; a near-field component duration for the electrogram; a far-field component duration for the electrogram; a number of multiple components for the electrogram; a slope of a sharpest component of the electrogram; a scalogram width; an energy ratio in the electrogram; and a cycle-length based metric of the electrogram.

Abstract: A method includes estimating, by a consumer electronic device, an atrial fibrillation (AF) burden of a subject based on multiple measurements passively collected by at least one sensor associated with the consumer electronic device while the subject is in a free-living environment. The method also includes outputting, by the consumer electronic device, an AF burden notification associated with the subject based on the estimated AF burden. The method further includes outputting, by the consumer electronic device, an AF burden recommendation based on the estimated AF burden.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: Systems, methods, and devices are provided for determining an early battery depletion (EBD) condition of an implantable medical device that includes a memory storing program instructions and a processor executing the program instructions. Circuitry is electrically coupled to the processor, and the circuitry and processor perform one or more tasks related to at least one of collecting signals indicative of physiologic activity, analyzing collected signals, delivering therapy, or communicating with an external device. A battery supplies energy to the circuitry and processor. A monitoring circuit coupled to the battery measures actual energy usage from the battery representing at least one of a current draw from the battery during corresponding tasks or a voltage measurement across the battery. Circuitry and processor calculate projected energy usage from the battery in connection with the corresponding tasks, and determine when an EBD condition exists based on projected energy usage and actual energy usage.

Abstract: A wearable cardioverter defibrillator system includes a support structure that a patient can wear. The system also includes electrodes that contact the patient, and define two or more channels from which ECG signals are sensed. A processor may evaluate the channels by analyzing their respective ECG signals, to determine which contains less noise than the other(s). The analysis can be by extracting statistics from the ECG signals, optionally after first processing them, and then by comparing these statistics. These statistics may include tall peak counts, amplitudes of peaks compared to historical peak amplitudes, signal baseline shift, dwell time near a baseline, narrow peak counts, zero crossings counts, determined heart rates, and so on. Once the less noisy signal is identified, its channel can be followed preferentially or to the exclusion of other channels, for continuing monitoring and/or determining whether to shock the patient.

Abstract: A wearable defibrillator for use in monitoring patient movement and cardiac activity and treating a patient includes a garment configured to be worn by the patient, treatment electrodes configured to apply an electric current to the patient, and an alarm module configured to provide audio, visual, and haptic notifications. The notifications are configured to indicate that an electric current will be administered imminently and prompt the patient to provide a response input. The wearable defibrillator includes a motion sensor configured to detect motion and body position of a patient, and a controller in electrical communication with the alarm module and the motion sensor. The controller is configured to monitor for the response input after the prompt, determine, based on the detected motion and body position, whether the patient is sleeping, and cause a change in one or more characteristics of the prompt on determining that the patient is sleeping.

Abstract: Systems and methods for classifying a cardiac arrhythmia are discussed. An exemplary system includes a correlator circuit to generate autocorrelation sequences using information of cardiac activity of a subject, including signal segments taken from a cardiac signal at respective elapsed time with respect to reference time. The correlator circuit can generate a correlation image using the autocorrelation sequences. The correlation image may be constructed by stacking the autocorrelation sequences according to the elapsed time of signal segments. An arrhythmia classifier circuit can classify the cardiac activity of the subject as one of arrhythmia types using the correlation image.

Abstract: A system and method for Brugada syndrome epicardial ablation comprising preparing an endocardial duration map; preparing a baseline epicardial duration map comprising at least one or more areas of delimination; and when some of the areas of delimination are greater than 200 ms, performing epicardial ablation of the areas of delimination greater than 200 ms. The method may further comprise preparing an updated epicardial duration map after performing epicardial ablation, and determining whether or not a BrS pattern appears in the updated epicardial duration map; and when the BrS pattern appears, performing epicardial ablation. The method may further comprise preparing an updated epicardial duration map after performing epicardial ablation, and determining whether or not an abnormal EGM exists in the updated epicardial duration map; and when the abnormal EGM exists, performing epicardial ablation.

Abstract: A system and method for identifying and treating a disease in a patient collects one or more data streams from sensors configured to detect biological signals generated within a patient's tissue over time. Patient data elements including one or more of demographic, clinical, laboratory, pathology, chemical, image, historical, genetic, and activity data for the patient is collected and processed with the data streams to generate a personalized digital phenotype (PDP). The PDP is compared to a digital taxonomy comprising prior data to classify the patient into one or more quantitative disease classifications to guide personalized intervention for treating the patient.

Abstract: A medical device is configured to receive sensed cardiac event data including a value of a feature determined from each one of a plurality of cardiac events sensed from a cardiac signal according to a first setting of a sensing control parameter. The medical device is configured to classify each value of the feature of each one of the sensed cardiac events as either a predicted sensed event or a predicted undersensed event according to a second setting of the sensing control parameter that is less sensitive to sensing cardiac events than the first setting. The medical device is configured to determine a predicted sensed event interval between each consecutive pair of the predicted sensed events and predict that an arrhythmia is detected or not detected based on the predicted sensed event intervals.

Abstract: In one example, a cardiac monitoring system, comprises a processor to receive a segment of an electrocardiogram (ECG) signal of a patient, and a memory to store the segment of the ECG. The processor is configured to identify QRS complexes in the segment of the ECG signal, compare the QRS complexes in the segment to the other QRS complexes in the segment to identify a main template QRS complex, identify the QRS complexes in the segment that are similar to the main template, determine RR intervals between consecutive similar QRS complexes to calculate RR variability in the RR intervals, and detect atrial fibrillation (AF) in the segment when RR variability is greater than a threshold value. Other examples and related methods are also disclosed herein.

Abstract: Methods, systems, and media are disclosed for reconstructing bioelectronic lead placement. In some embodiments, the disclosed system can include a processor configured to determine relationships between EP signals of one or more pairs of a plurality of electrodes over one or more sampling time periods, wherein the plurality electrodes are separately placed on a patient's body for collecting the EP signals, and to reconstruct geometry of the plurality of electrodes based on the relationships between the EP signals.

Abstract: A guide system for indicating an activator of a defibrillator to a user including a motion detection circuit which determines motion of the defibrillator and generates at least one defibrillator motion mode signal, and a guide circuit which receives the defibrillator motion mode signal and causes the activator to be indicated to the user of the defibrillator.

Abstract: A medical device, such as an extra-cardiovascular implantable cardioverter defibrillator (ICD), senses R-waves from a first cardiac electrical signal by a first sensing channel and stores a time segment of a second cardiac electrical signal acquired by a second sensing channel in response to each sensed R-wave. The ICD determines morphology match scores from the stored time segments of the second cardiac electrical signal and, based on the morphology match scores, withholds detection of a tachyarrhythmia episode. In some examples, the ICD detects T-wave oversensing based on the morphology match scores and withholds detection of a tachyarrhythmia episode in response to detecting the T-wave oversensing.

Abstract: Systems and methods for detecting cardiac arrhythmia are discussed. An exemplary medical-device system includes an arrhythmia detector circuit that receives physiologic information, including respiration and heart beat information a patient, and determines whether a respiratory sinus arrhythmia (RSA) is present or absent using the respiration and the heart beat information. An indication of the presence or absence of RSA may be stored in a memory. The arrhythmia detector circuit can detect an AT episode using the indication of RSA.

Abstract: A method and medical device for detecting a cardiac event that includes sensing cardiac signals from a plurality of electrodes forming a first sensing vector sensing a first interval of the cardiac signal during a predetermined time period and a second sensing vector simultaneously sensing a second interval of the cardiac signal during the predetermined time period, identifying each of the first interval and the second interval as being one of shockable and not shockable in response to first processing of the first interval and the second interval and in response to second processing of one or both of the first interval and the second interval, the second processing being different from the first processing, and determining whether to deliver therapy for the cardiac event in response to identifying each of the first interval and the second interval as being one of shockable and not shockable in response to both the first processing and the second processing of the first interval and the second interval.

Abstract: Systems and methods for managing machine-generated alert notifications of medical events detected from one or more patients are described herein. An embodiment of a data management system may receive an adjudication of a medical event episode including an episode characterization. A storage unit stores an association between one or more episode characterizations and corresponding detection algorithms for detecting a medical event having respective episode characterizations. An episode management circuit may detect from a subsequent episode, using the stored association, a medical event having an episode characterization of at least one medical event episode presented for adjudication, and schedule presenting at least a portion of the subsequent episode based on the detection.

Abstract: A physiological information measurement apparatus includes a measuring section that acquires a physiological signal from a living body of a subject, a signal processor that produces a plurality of physiological signal waveforms based on the physiological signal acquired from the measuring section, and that identifies an arithmetic average waveform that is obtained by arithmetic averaging of the plurality of physiological signal waveforms, and information relating to arithmetic average dispersion, and a display that displays at least the information relating to the arithmetic average dispersion.

Abstract: Systems and methods are described herein for selection of a cardiac cycle, or heartbeat, from a plurality of cardiac cycles monitored over time. The cardiac cycle may be selected using various metrics including a single-cycle metric and a cycle-series metric. Further, the selected cardiac cycle may be used for further cardiac analysis (for example, to generate electrical activation times).

Abstract: A method, including receiving from mapping electrodes positioned at locations within a heart, signals indicating electrical activity in tissue contacting the electrodes, and processing the signals to identify, for each location, at least one corresponding LAT in a cycle of a heart. For each location, an earliest LAT in the cycle is identified, and an electroanatomical map including mapping points having respective locations and showing the earliest LAT at each location is generated and rendered. An input selecting a subset of the points is received, and a time range containing the earliest LAT of a majority of the points in the subset is identified. One or more outlying points in the subset are identified, and a second LAT, later than the earliest LAT in the cycle is found among the at least one identified LAT identified at the outlying points. The map is updated to display the found second LAT.

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 stand-alone continuous cardiac Doppler or acoustic pulse monitoring patch provides visual and auditory signals that a pulse or heartbeat is detected or not detected in a human subject. The invention is a small patch with a peel-away adhesive surface that is applied to the skin of the subject, preferably near a large artery. For the Doppler monitor, the patch includes a pad formed of a conductive medium to enhance transmission and reception of ultrasonic waves. For the acoustic monitor, the pad has a sound focusing portion that permits entry of sounds and focuses the sounds toward a microphone, and the pad also has a sound insulating portion surround the sound focusing portion. The patch includes an integral power source. The Doppler patch has transmitters and receivers to send and detect reflected ultrasonic waves and a transducer to convert the reflected waves into an electrical signal.

Abstract: A method for extracting f wave from a single-lead electrocardiography signal is provided. The method includes: establishing a two-channel temporal convolutional neural network model, including two coding submodules, two mask estimation submodules, an information fusion module and two decoding submodules; constructing a training data set of ECG signals; training the two-channel temporal convolutional neural network model, and saving the trained model. The two-channel temporal convolution neural network encodes and decodes a QRST complex and the f wave respectively, and uses a mask of information fusion to estimate and construct regular items to restrict a distribution difference of QRST component coding features, so as to reduce the distortion of the QRST complex, select potential features of a QRST complex and f wave with high signal-to-noise ratio, and thus improve a detection accuracy of the f wave.

Abstract: A heart rate (HR) monitor for use in a medical device configurable to measure a patient's ECG such as, for example, a WCD system. Embodiments can include an ECG sensor and a processor configured with classification criteria to classify a received ECG signal into one of a plurality of ECG rhythm types each with a corresponding algorithm to determine the patient's heart rate. The processor uses the classification criteria to identify the ECG signal's type and determine a heart rate of the patient using the corresponding algorithm. The HR monitor is configurable to avoid overcounting of erroneous measurements of R-R intervals that can result from large T-waves and/or bigeminy by comparing the mean of even R-R intervals with the mean of odd R-R intervals. If the means are significantly different double counting or bigeminy is indicated and the HR calculation is adjusted accordingly.

Abstract: A method includes receiving an anatomical map of at least a portion of a heart. Positions and respective bipolar intracardiac electrogram (EGM) signals measured at the positions are received for at least a region of the anatomical map. Primary activations and secondary activations are identified in the bipolar intracardiac EGM signals. A surface representation of the bipolar intracardiac EGM signals over the region is derived, including the identified primary activations and secondary activations. The surface representation is presented overlaid on the anatomical map.

Abstract: Techniques for administering a care plan. Biometric data collected by a monitoring device is received at a care plan management system using a communication network. The biometric data includes a first event classified by a remote device as a first type of event. A relative processing priority for the first event is determined, at the care plan management system, based on the first type. The first event is processed, at the care plan management system, based on the relative processing priority. The processing includes re-classifying the first event as a second type of event. The re-classification is more computationally intensive than the classification by the remote device. At least one treatment task specified in the care plan is initiated, using a computer processor, and based on the re-classified first event.

Abstract: Systems and methods for detecting cardiac arrhythmias such as atrial tachyarrhythmia (AT) are discussed. An exemplary system includes a ventricular beat analyzer circuit to detect ventricular beats and assess ventricular activity, such as to evaluate a ventricular rate stability. The system includes an arrhythmia detector circuit to detect respective AT indications in distinct time periods using portions of received physiologic information during the distinct time periods. A control circuit can monitor the ventricular beats on a beat-by-beat basis, in response to the detected ventricular beats satisfying an instability condition, trigger AT detections during the distinct time periods and withhold AT detection in a subsequent time period if no AT is detected in the present time period. An AT characteristic may be generated using the detected AT indications. A therapy may be delivered in accordance with the AT characteristic.

Abstract: Systems and methods for facilitating display of cardiac information based on sensed electrical signals include a processing unit configured to receive a set of electrical signals; receive an indication of a measurement location corresponding to each electrical signal of the set of electrical signals; and generate an activation waveform corresponding to the set of electrical signals. Systems and methods disclosed herein may be configured to generate, based on the activation waveform, a representation of a cardiac electrical signal feature; and facilitate presentation, on a display device, of a cardiac map and the representation of the cardiac electrical signal feature.

Abstract: A defibrillator and method for using a defibrillator which adopts an ECG analysis algorithm that can detect a cardiac arrhythmia in the presence of noise artifact induced by cardio pulmonary resuscitation (CPR) compressions. The apparatus and method offers guidance throughout a cardiac rescue protocol involving both defibrillation shocks and CPR that improves the effectiveness of the rescue, resulting in more CPR “hands-on” time, better treatment of refibrillation, and reduced transition times between CPR and electrotherapy.

Abstract: An ECG processing system for identifying noisy ECG data segments is provided. The ECG processing system includes a network interface and a processor. The network interface is configured to receive a first collection of ECG data segments from wearable medical devices associated with a plurality of patients, each wearable medical device of the wearable medical devices being configured to be continuously worn by a patient for an extended period of time. The processor is configured to produce a second collection of ECG data segments from the first collection of ECG data segments that excludes noisy ECG data segments.

Abstract: A medical device such as an external defibrillator delivers electrical therapy using a special pulse sequence. The special pulse sequence includes a defibrillation shock that is automatically followed by a quick succession of automatic post-shock anti-tachycardia (APSAT) pacing pulses. Because of the pacing pulses, the defibrillation shock can be of lesser energy than an equivalent defibrillation shock of a larger energy. Accordingly, the external defibrillator can be made physically smaller and weigh less, without sacrificing the therapeutic effect of a larger external defibrillator that would deliver a defibrillation shock of higher energy. As such, the defibrillator is easier to configure for transporting, handling, and even wearing.

Abstract: Anomalous sensors are detected using an apparatus including a processor and one or more computer readable mediums collectively including instructions that, when executed by the processor, cause the processor to obtain a plurality of healthy sensor data, wherein each of the healthy sensor data includes a plurality of sensed values of a corresponding sensor among a plurality of sensors in normal operation, generate a healthy data distribution of at least two sensors among the plurality of sensors based on the plurality of healthy sensor data, and generate a function of a parameter probability distribution of the plurality of sensors under a condition of sensor data of the plurality of sensors based on the healthy data distribution, each parameter indicating whether the corresponding sensor is healthy or anomalous.

Abstract: VfA cardiac therapy uses an implantable medical device or system. The implantable medical device includes a tissue-piercing electrode implanted in the basal and/or septal region of the left ventricular myocardium of the patient's heart from the triangle of Koch region of the right atrium through the right atrial endocardium and central fibrous body. The device may include a right atrial electrode, a right atrial motion detector, or both. The device may be implanted completely within the patient's heart or may use one or more leads to implant electrodes in the patient's heart. The device may be used to provide cardiac therapy, including single or multiple chamber pacing, atrioventricular synchronous pacing, asynchronous pacing, triggered pacing, cardiac resynchronization pacing, or tachycardia-related therapy. A separate medical device may be used to provide some functionality for cardiac therapy, such as sensing, pacing, or shock therapy.

Abstract: A charger including a class E power driver, a frequency-shift keying (“FSK”) module, and a processor. The processor can receive data relating to the operation of the class E power driver and can control the class E power driver based on the received data relating to the operation of the class E power driver. The processor can additionally control the FSK module to modulate the natural frequency of the class E power transformer to thereby allow the simultaneous recharging of an implantable device and the transmission of data to the implantable device. The processor can additionally compensate for propagation delays by adjusting switching times.

Abstract: The systems and methods provide for novel a triggering mode that allows the patient to trigger or initiate the delivery of a breath during ventilation on a ventilator. Further, the systems and methods provide for triggering ventilation utilizing a statistical trigger mode. Additionally, the systems and methods provide for analyzing and/or displaying information related to a potential change in a triggering threshold for a currently utilized breath type.

Abstract: A system includes an electrical interface and a processor configured to receive, via the electrical interface, a signal sensed by at least one electrode in contact with tissue of a subject's heart, the signal spanning successive time periods that are each of length T1 and including multiple signal points, to calculate respective thresholds for the time periods, to select a set of points that includes, for each of the time periods, a signal point of greatest magnitude in the time period, provided that the greatest magnitude is greater than the threshold for the time period, to remove, from the set, one of any pair of the selected points that are within an interval T2 of one another, T2 being less than T1, and to generate, subsequently to the removing, an output that is based on the points remaining in the set corresponding to respective electrical activations of the tissue.

Abstract: Methods and systems are provided for detecting arrhythmias in cardiac activity. The methods and systems declare a current beat, from the CA signals, to be a candidate beat or an ineligible beat based on whether the current beat satisfies the rate based selection criteria. The determining and declaring operations are repeated for multiple beats to form an ensemble of candidate beats. The method and system calculate a P-wave segment ensemble from the ensemble of candidate beats, perform a morphology-based comparison between the P-wave segment ensemble and at least one of a monophasic or biphasic template, declare a valid P-wave to be present within the CA signals based on the morphology-based comparison, and utilize the valid P-wave in an arrhythmia detection process to determine at least one of an arrhythmia entry, arrhythmia presence or arrhythmia exit.

Abstract: A medical device, such as an extra-cardiovascular implantable cardioverter defibrillator (ICD), senses R-waves from a first cardiac electrical signal by a first sensing channel and stores a time segment of a second cardiac electrical signal acquired by a second sensing channel in response to each sensed R-wave. The ICD determines morphology match scores from the stored time segments of the second cardiac electrical signal and, based on the morphology match scores, withholds detection of a tachyarrhythmia episode. In some examples, the ICD detects T-wave oversensing based on the morphology match scores and withholds detection of a tachyarrhythmia episode in response to detecting the T-wave oversensing.

Abstract: Devices and methods for single therapy pulse (STP) therapy for tacharrythmia are disclosed. The STP therapy can be delivered from a far-field position to allow a “global” capture approach to pacing. Due to the global capture in STP, a series of pulses, which is indicative of conventional anti-tachycardia pacing (ATP) delivered by transvenous systems, becomes unnecessary. One to four pulses at most are needed for STP, and after delivery of the one to four pulses, therapy delivery can be interrupted to determine whether the previously delivered therapy has been successful.

Abstract: A method of determining a likelihood of an occurrence of a cardiac arrhythmia in a patient includes receiving three-dimensional imaging data of said patient's heart, constructing a whole-heart model for simulating at least one of electrophysiological activity or electromechanical activity of the patient's heart using the three-dimensional imaging data, simulating a response of the patient's heart to each of a plurality of stimulations to a corresponding plurality of different locations within the patient's heart using the whole-heart model, classifying each simulation outcome for each stimulation as one of a normal heart rhythm or a cardiac arrhythmia, calculating a likelihood index based on results of the classifying, and determining the likelihood of the occurrence of the cardiac arrhythmia in the patient based on the likelihood index. Software and data processing systems that implement the above methods are also provided.

Abstract: An apparatus includes a network interface and a processor. The network interface is configured to communicate over a communication network. The processor is configured to receive (i) data, including a medical parameter acquired as a function of time, and (ii) a selection of one or more time intervals of interest within the time period. The processor is further configured to compress a first portion of the data, which is within the selected time intervals, at a first resolution, and compress a second portion of the data, which is outside the selected time intervals, at a second resolution, which is coarser than the first resolution. The processor is additionally configured to transmit the compressed first and second portions of the data, via the network interface, over the communication network.

Abstract: A computer implemented method and system for confirming a device documented arrhythmia in cardiac activity are provided. The method is under control of one or more processors configured with executable instructions. The method obtains a cardiac activity (CA) data set that includes CA signals for a series of cardiac events and includes device documented (DD) markers within the series of cardiac events. The device documented markers are indicative of atrial fibrillation (AF) detected by the ICM utilizing an on-board R-R interval irregularity (ORI) process to analyze the CA signals. The method applies a feature enhancement function to the CA signals to form modified CA signals with enhanced sinus features and analyzes the enhanced sinus features in the modified CA signals. The method utilized a confirmatory feature detection process to identify false AF detection by the ORI process. The method records a result of the analysis identifying false AF detection by the ORI process.

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: A system that detects heartbeats includes a sensor or a transducer and algorithms based on deep learning. The algorithms employ techniques of artificial intelligence that enable the system to extract heartbeat features under low signal-to-noise-ratio (SNR) conditions when a user is exercising. The algorithms can be applied to various technologies for heart rate monitoring such as ultrasound Doppler, photoplethysmogram (PPG), electrocardiogram (EKG), acoustic, pressure/force sensing and laser/RF Doppler, among other types of sensing methods.

Abstract: Embodiments of the present disclosure relate generally to the use of spectral sensors during a cardiac arrest event. More specifically, the present disclosure relates to the use of spectral sensors for measuring changes in pH and muscle oxygen saturation to estimate subject down time and evaluating the effectiveness of the clinical treatment administered during a cardiac arrest event. Given the narrow window of time in which emergency treatment must be administered, as well as the lack of information concerning the subject's condition, there is a need for a fast and accurate method of estimating the onset of the cardiac arrest emergency and evaluating the effectiveness of the emergency treatment being administered.

Abstract: An apparatus includes a sensing circuit configured to generate a sensed physiological signal representative of cardiac activity of a subject, an arrhythmia detection circuit, a control circuit, and a memory. The arrhythmia detection circuit detects an episode of atrial fibrillation (AF) in the sensed cardiac signal using a first AF detection criterion, and detects the episode of AF using a second AF detection criterion. The first AF detection criterion has greater sensitivity to AF detection than the second AF detection criterion, and the second AF detection criterion has greater specificity to AF detection than the first AF detection criterion. The control circuit initiates storing of sampled values of a segment of the cardiac signal that includes the episode of AF when the episode of AF is detected by both the first AF detection criterion and the second AF detection criterion.

Abstract: We disclose herein a method of detecting abnormalities in electrocardiogram (ECG) signals, the method comprising receiving a set of ECG signals from an ECG device; amplifying only the peaks of at least some of the set of ECG signals to produce ECG beat markings from which a heart rate is derivable to detect an irregular rhythm between at least two ECG beats; extracting a single ECG beat from the set of ECG signals from the ECG device by using said ECG beat markings; feeding the extracted single ECG beat into a first neural network; producing, at the first neural network, a compact representation of the extracted single ECG signal so as to generate a feature extraction output; and using, at a second neural network, the feature extraction output from the first neural network to generate a score associated with the abnormalities in the ECG signals.

Abstract: A method of detecting atrial fibrillation includes detecting a pulse signal to obtain a time pulse waveform and converting it to an energy spectrum waveform via Fast Fourier Transform. The energy spectrum waveform includes a first frequency region, a second frequency region, and a third frequency region. The number of spikes in each frequency region was calculated and the heart indexes of the first, second, and third frequency regions were obtained, which were the first heart index, the second heart index, and the third heart index. And by the sum of the three heart index values and the first heart index to determine the possibility of atrial fibrillation. An apparatus for detecting atrial fibrillation is also provided, whereby the user can determine the possibility and predicting atrial fibrillation by simple measurement of blood pressure at home.

Abstract: A method and system for mapping an anatomical structure includes sensing activation signals of intrinsic physiological activity with a plurality of mapping electrodes disposed in or near the anatomical structure, each of the plurality of mapping electrodes having an electrode location. A vector field map which represents a direction of propagation of the activation signals at each electrode location is generated to identify a signature pattern and a location in the vector field map according to at least one vector field template. A target location of the identified signature pattern is identified according to a corresponding electrode location.