An apparatus for measuring the size of an electrocardiography signal using a Hilbert transform, according to one embodiment of the present invention, may comprise: a receiving unit for receiving a measured electrocardiography signal; a transform unit for Hilbert-transforming the received electrocardiography signal; and a measurement unit for obtaining the size of the electrocardiography signal on the basis of the Hilbert-transformed electrocardiography signal.

An apparatus yields signals that are equivalent to ECG signals and allow determination of a heartbeat interval or heart rate from bio-vibration signals including vibrations derived from heartbeats. An ECG meter acquires ECG signals of a sample, and a piezoelectric sensor acquires bio-vibration signals of the sample simultaneously. The bio-vibration signals include beating vibration signals derived from heartbeats. A learning unit of a prediction modeling apparatus establishes a prediction model by machine learning in which ECG signals are used as teaching data, and model input signals obtained by performing a specified processing on the bio-vibration signals are input. The learning unit delivers the prediction model to a prediction unit of a signal processing apparatus. The prediction model predicts and outputs pECG signals upon input of model input signals obtained by performing a specified processing on bio-vibration signals acquired from a subject under prediction with a piezoelectric sensor.

A catheter assembly including a catheter and a stylet disposed within a lumen of the catheter, the lumen having a closed distal end. The stylet includes a sensor at the distal end of the stylet and the sensor is located within a sensor pocket at the closed distal end of the lumen. An aperture extending through a luminal wall between the sensor pocket and the exterior of the catheter defines an electrical pathway between the sensor and the patient vasculature. A tapered distal portion of the catheter extends away from the distal end of the catheter and the sensor pocket is disposed along the tapered distal portion. A fluid opening extending between the lumen and the exterior of the catheter is disposed proximal the sensor pocket. A coated portion of the stylet includes an electrically insulative coating and the coated portion is disposed adjacent the fluid opening.

A method comprises identifying P-waves within a cardiac signal stored by a medical device for a cardiac episode detected by the medical device, and calculating a gain factor for display of the cardiac signal based on the identified P-waves.

In one example, an apparatus of a wearable cardioverter defibrillator (WCD) system comprises a support structure wearable by a patient, a plurality of electrocardiogram (ECG) electrodes to obtain an ECG signal, a processor to receive and analyze the ECG signal of the patient, wherein the processor is configured to monitor four or more channels of the ECG signal, a high voltage subsystem coupled with defibrillation electrodes configured to be coupled with patient, wherein the processor is configured to cause the high voltage subsystem to apply a therapeutic shock to the patient through the defibrillation electrodes in response to a shockable event detected by the processor from the ECG signal. The processor measures a peak-to-peak amplitude of QRS complexes of the ECG signal, and detects asystole in the patient when the peak-to-peak amplitude of one or more QRS complexes is less than an asystole threshold. Other examples and related methods are disclosed herein.

Provided are a monitoring device, a method for setting reference baseline and a readable storage medium. Whether the monitoring device has a system error is determined due to at least one event, according to at least one of the moving state of the target object, the connection state of the target object and the signal acquisition device, the environmental information where the target object is located, and the analysis result of the monitoring device. When the monitoring device has a system error, the current reference baseline of the monitoring device is updated according to the preset rules, and then the monitoring is continued based on the new reference baseline. In this way, the current reference baseline of the monitoring device can be adjusted in time, false alarms and missed alarms caused by the system error can be avoided and the accuracy of the monitoring device can be improved.

Provided are a monitoring device, a method for setting reference baseline and a readable storage medium. Whether the monitoring device has a system error is determined due to at least one event, according to at least one of the moving state of the target object, the connection state of the target object and the signal acquisition device, the environmental information where the target object is located, and the analysis result of the monitoring device. When the monitoring device has a system error, the current reference baseline of the monitoring device is updated according to the preset rules, and then the monitoring is continued based on the new reference baseline. In this way, the current reference baseline of the monitoring device can be adjusted in time, false alarms and missed alarms caused by the system error can be avoided and the accuracy of the monitoring device can be improved.

Systems and methods for detecting atrial tachyarrhythmias (AT) such as atrial fibrillation (AF) are disclosed. A medical system can include a cardiac signal sensor circuit to sense a cardiac electrical signal and a heart sound (HS) sensor to sense heart a HS signal A cardiac electrical signal metric, including a cycle length variability or a detection of atrial electrical activity, can be generated from the cardiac electrical signal A HS metric can be generated from the HS signal, including a status of detection of S4 heart sound or a S4 heart sound intensity indicator. The system can include an AT detector circuit that can detect an AT event, such as an AF event, using the cardiac electrical signal metric and the HS metric. The system can additionally classify the detected AT event as an AF or an atrial flutter event.

An auscultation device includes an electrocardiogram (ECG) device, a sound receiver device, a synchronization device and a processor. The ECG device is configured to receive an ECG signal. The sound receiver device is configured to receive a heart sound signal. The synchronization device is configured to transmit a synchronization signal to the

ECG device and the sound receiver device, so that the ECG device starts to receive the ECG signal and the sound receiver device starts to receive the heart sound signal in time synchronization. Moreover, the processor is configured to generate an ECG according to the ECG signal, generate a heart sound diagram according to the heart sound signal, and generate a synchronization timing diagram according to the ECG and the heart sound diagram.

A computer implemented method and device for providing dual chamber sensing with a single chamber leadless implantable medical device (LIMD) are provided. The method is under control of one or more processors in the LIMD configured with specific executable instructions. The method obtains a far field (FF) cardiac activity (CA) signals for activity in a remote chamber of a heart and compares the far field CA signals to a P-wave template to identify an event of interest associated with the remote chamber. The method sets an atrial-ventricular (AV) delay based on the P-wave identified and delivers pacing pulses at a pacing site of interest to a local chamber based on the AV delay.