The present application provides a method and apparatus for detecting an ECG signal and an electronic device. According to an example of the method, an ECG signal with a set time length is segmented to obtain a first set number of single heartbeats; feature data corresponding to each of the first set number of single heartbeats is determined to obtain a first set number of feature data; and a pathological category of the ECG signal with the set time length is determined based on the ECG signal with the set time length and the first set number of feature data.

The present application provides a method and apparatus for detecting an ECG signal and an electronic device. According to an example of the method, an ECG signal with a set time length is segmented to obtain a first set number of single heartbeats; feature data corresponding to each of the first set number of single heartbeats is determined to obtain a first set number of feature data; and a pathological category of the ECG signal with the set time length is determined based on the ECG signal with the set time length and the first set number of feature data.

A method of detecting abnormalities in ECG signals by providing an ECG signal to a neural network, performing a first series of convolution operations to a first subset of layers and in a final layer, and determining a plurality of preliminary classification estimates, each preliminary classification estimate corresponding with a time segment of the ECG signal. Furthermore, determining input data for a second subset of layers of the neural network by concatenating the preliminary classification with the output of a layer of the first subset of layers that precedes the final layer of the first subset of layers. Within the second subset of layers of the neural network, performing a second series of convolution operations. In a final layer of the second subset, determining plurality of final classification estimates, each final classification estimate corresponding with a time segment of the ECG signal.

A physiological signal monitoring system includes a single set of sensing electrodes to provide conditioned physiological signals to a primary monitoring device and a secondary monitoring device. The monitoring system includes pre-processing circuitry configured to receive a raw physiological signal. The pre-processing circuitry is configured to produce a primary physiological signal and a secondary physiological signal. Each of the primary and secondary physiological signals are conditioned. The primary conditioned physiological signal is directed to a primary monitoring device such as a hospital wearable defibrillator device. The secondary conditioned physiological signal is directed to telemetry modeling circuitry where it is further processed to output one or more telemetry signals. The one or more telemetry signals are output to a secondary monitoring device such as a three lead ECG monitoring device. Thus, a single set of sensing electrodes can provide physiological signals to multiple monitoring devices.

A physiological signal monitoring system includes a single set of sensing electrodes to provide conditioned physiological signals to a primary monitoring device and a secondary monitoring device. The monitoring system includes pre-processing circuitry configured to receive a raw physiological signal. The pre-processing circuitry is configured to produce a primary physiological signal and a secondary physiological signal. Each of the primary and secondary physiological signals are conditioned. The primary conditioned physiological signal is directed to a primary monitoring device such as a hospital wearable defibrillator device. The secondary conditioned physiological signal is directed to telemetry modeling circuitry where it is further processed to output one or more telemetry signals. The one or more telemetry signals are output to a secondary monitoring device such as a three lead ECG monitoring device. Thus, a single set of sensing electrodes can provide physiological signals to multiple monitoring devices.

A system includes a collar that is worn around a neck of the user. A stimulator is coupled to the collar such that the stimulator is positioned adjacent to an airway of the user. The sensor is coupled to the collar and configured to generate data associated with the airway of the user. The memory is coupled to the collar and storing machine-readable instructions. The control system is coupled to the collar and includes one or more processors configured to execute the machine-readable instructions to determine, based at least on an analysis of the generated data, that the user is currently experiencing an apnea event. In response to the determination, the control system causes the stimulator to provide electrical stimulation, at a first intensity level, to one or more muscles of the user that are adjacent to the airway to aid in stopping the apnea event.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to estimate the action potential wave propagation in a patient's heart, and subsequently to detect at least one location or type of at least one source of, or rotational phenomenon associated with, at least one cardiac rhythm disorder using intracardiac electrodes and a modified multi-frame Horn-Schunck algorithm to generate a map corresponding to a spatial map, the map being configured to reveal on a monitor or display to a user the at least one location of the at least one source of the at least one cardiac rhythm disorder.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to estimate the action potential wave propagation in a patient's heart, and subsequently to detect at least one location or type of at least one source of, or rotational phenomenon associated with, at least one cardiac rhythm disorder using intracardiac electrodes and a modified multi-frame Horn-Schunck algorithm to generate a map corresponding to a spatial map, the map being configured to reveal on a monitor or display to a user the at least one location of the at least one source of the at least one cardiac rhythm disorder.

The detection and diagnosis of a variety of cardiovascular disorders and levels of heart condition, using a novel method and system, according to a comprehensive analysis of cardiac electrical signal via the frequency domain, time domain, spatial domain.

The detection and diagnosis of a variety of cardiovascular disorders and levels of heart condition, using a novel method and system, according to a comprehensive analysis of cardiac electrical signal via the frequency domain, time domain, spatial domain.