Abstract: A medical device is configured to detect an alternating pattern of signal features determined from consecutive segments of a cardiac electrical signal and determine a gross morphology metric from at least one segment of the cardiac electrical signal. The device is configured to detect cardiac event oversensing in response to detecting the alternating pattern and the gross morphology metric not meeting tachyarrhythmia morphology criteria. The medical device may withhold detecting an arrhythmia in response to detecting the cardiac event oversensing.

Abstract: The present disclosure provides an event extraction method, an event extraction device and an electronic device, and it relates to the field of computer data processing, in particular to the field of knowledge graph. The event extraction method includes: acquiring text information; determining a plurality of pieces of question information ranked in a sequential order in accordance with the text information; and inputting vector information for each piece of question information into an extraction model in accordance with the sequential order to acquire extraction information for each piece of question information.

Abstract: A medical device processor is configured to receive a first cardiac electrical signal sensed from a first sensing electrode vector, receive a second cardiac electrical signal sensed from a second sensing electrode vector different than the first sensing electrode vector, and construct a third cardiac electrical signal from the first cardiac electrical signal and the second cardiac electrical signal. In some examples, the system determines sensed cardiac events according to at least one setting of a cardiac event sensing threshold control parameter from at least the third cardiac electrical signal and may determine at least one acceptable setting of a sensing control parameter based on the determined sensed cardiac events. The processor may generate an output representative of the determined sensed cardiac events.

Abstract: A medical device is configured to determine time intervals between consecutive cardiac events sensed from a cardiac electrical signal, increase a value of a tachyarrhythmia interval count in response to each of the determine time intervals detected as a tachyarrhythmia interval. The device is further configured to detect normal sinus rhythm events and the decrease the value of the tachyarrhythmia interval count in response to a threshold number of detected normal sinus rhythm events.

Abstract: An event argument extraction (EAE) method, an EAE apparatus and an electronic device, relates to the technical field of knowledge graphs. A specific implementation scheme includes acquiring a to-be-extracted event content; and performing argument extraction on the to-be-extracted event content based on a trained EAE model, to obtain a target argument of the to-be-extracted event content; where the trained EAE model is obtained by training a pre-trained model with event news annotation data and a weight of each argument annotated in the event news annotation data.

Abstract: A medical device is configured to sense event signals from a cardiac electrical signal and determine maximum amplitudes of cardiac electrical signal segments associated with sensed event signals. The medical device is configured to determine at least one tachyarrhythmia metric based on at least a greatest one of the determined maximum amplitudes. The medical device may determine when the at least one tachyarrhythmia metric does not meet true tachyarrhythmia evidence and, in response, determine when the maximum amplitudes meet suspected noise criteria. The medical device may withhold a tachyarrhythmia detection and tachyarrhythmia therapy when suspected noise criteria are met.

Abstract: A medical device processor is configured to receive a first cardiac electrical signal sensed from a first sensing electrode vector, receive a second cardiac electrical signal sensed from a second sensing electrode vector different than the first sensing electrode vector, and construct a third cardiac electrical signal from the first cardiac electrical signal and the second cardiac electrical signal. In some examples, the system determines sensed cardiac events according to at least one setting of a cardiac event sensing threshold control parameter from at least the third cardiac electrical signal and may determine at least one acceptable setting of a sensing control parameter based on the determined sensed cardiac events. The processor may generate an output representative of the determined sensed cardiac events.

Abstract: A medical device is configured to determine time intervals between consecutive cardiac events sensed from a cardiac electrical signal, increase a value of a tachyarrhythmia interval count in response to each of the determine time intervals detected as a tachyarrhythmia interval. The device is further configured to detect normal sinus rhythm events and the decrease the value of the tachyarrhythmia interval count in response to a threshold number of detected normal sinus rhythm events.

Abstract: A medical device is configured to sense event signals from a cardiac electrical signal and determine maximum amplitudes of cardiac electrical signal segments associated with sensed event signals. The medical device is configured to determine at least one tachyarrhythmia metric based on at least a greatest one of the determined maximum amplitudes. The medical device may determine when the at least one tachyarrhythmia metric does not meet true tachyarrhythmia evidence and, in response, determine when the maximum amplitudes meet suspected noise criteria. The medical device may withhold a tachyarrhythmia detection and tachyarrhythmia therapy when suspected noise criteria are met.

Abstract: A medical device is configured to sense an electrical signal and determine that signal to noise criteria are met based on electrical signal segments stored in response to sensed electrophysiological events. The medical device is configured to determine an increased gain signal segment from one of the stored electrical signal segments in response to determining that the signal to noise criteria are met. The medical device determines a noise metric from the increased gain signal segment. The stored electrical signal segment associated with the increased gain signal segment may be classified as a noise segment in response to the noise metric meeting noise detection criteria.

Abstract: A medical device is configured to determine tachyarrhythmia evidence in a cardiac signal segment received from a cardiac electrical signal sensed during a pacing escape interval started to schedule a pending cardiac pacing pulse. The medical device may delay the pending cardiac pacing pulse in response to determining the tachyarrhythmia evidence during the pacing escape interval.

Abstract: A medical device is configured to determine an amplitude metric from a cardiac signal segment sensed over a predetermined time interval and determine if the amplitude metric meets an amplitude threshold. The medical device is configured to perform a first analysis of the cardiac electrical signal segment for detecting a first arrhythmia when the amplitude metric does not meet the amplitude threshold and perform a second analysis of the cardiac electrical signal segment for detecting a second arrhythmia different than the first arrhythmia in response to the amplitude metric meeting the amplitude threshold.

Abstract: A medical device is configured to receive cardiac electrical signals and sense ventricular event signals from the cardiac electrical signals. The medical device may start a validation window in response to sensing a ventricular event signal and determine if the ventricular event signal is a valid event signal or an invalid event signal based on processing of a different cardiac electrical signal than the cardiac electrical signal from which the ventricular event signal was sensed.

Abstract: A medical device is configured to sense an electrical signal and determine that signal to noise criteria are met based on electrical signal segments stored in response to sensed electrophysiological events. The medical device is configured to determine an increased gain signal segment from one of the stored electrical signal segments in response to determining that the signal to noise criteria are met. The medical device determines a noise metric from the increased gain signal segment. The stored electrical signal segment associated with the increased gain signal segment may be classified as a noise segment in response to the noise metric meeting noise detection criteria.

Abstract: A medical device is configured to sense first ventricular event signals from a first cardiac electrical signal and sense second ventricular event signals from a second cardiac electrical signal. The medical device is configured to determine sensed event data in response to the first ventricular event signals and the second ventricular event signals. The medical device may select one of the first cardiac electrical signal or the second cardiac electrical signal for providing input for tachyarrhythmia detection based on the sensed event data.

Abstract: A question answering method based on a knowledge graph are disclosed, including: After obtaining a first natural query statement including a first query entity and first entity characteristic information, the terminal queries the knowledge graph based on the first query entity and the first entity characteristic information, to obtain a first result. The terminal obtains a second natural query statement after outputting the first result. The terminal determines a missing part in the second natural query statement based on the first query entity or the first entity characteristic information. The terminal queries the knowledge graph based on the missing part in the second natural query statement to obtain a second result, and outputs the second result.

Abstract: A medical device processor is configured to receive a first cardiac electrical signal sensed from a first sensing electrode vector, receive a second cardiac electrical signal sensed from a second sensing electrode vector different than the first sensing electrode vector, and construct a third cardiac electrical signal from the first cardiac electrical signal and the second cardiac electrical signal. In some examples, the system determines sensed cardiac events according to at least one setting of a cardiac event sensing threshold control parameter from at least the third cardiac electrical signal and may determine at least one acceptable setting of a sensing control parameter based on the determined sensed cardiac events. The processor may generate an output representative of the determined sensed cardiac events.

Abstract: A medical device is configured to sense event signals from a cardiac electrical signal and determine maximum amplitudes of cardiac electrical signal segments associated with sensed event signals. The medical device is configured to determine at least one tachyarrhythmia metric based on at least a greatest one of the determined maximum amplitudes. The medical device may determine when the at least one tachyarrhythmia metric does not meet true tachyarrhythmia evidence and, in response, determine when the maximum amplitudes meet suspected noise criteria. The medical device may withhold a tachyarrhythmia detection and tachyarrhythmia therapy when suspected noise criteria are met.

Abstract: An event argument extraction (EAE) method, an EAE apparatus and an electronic device, relates to the technical field of knowledge graphs. A specific implementation scheme includes acquiring a to-be-extracted event content; and performing argument extraction on the to-be-extracted event content based on a trained EAE model, to obtain a target argument of the to-be-extracted event content; where the trained EAE model is obtained by training a pre-trained model with event news annotation data and a weight of each argument annotated in the event news annotation data.

Abstract: The present disclosure provides an event extraction method, an event extraction device and an electronic device, and it relates to the field of computer data processing, in particular to the field of knowledge graph. The event extraction method includes: acquiring text information; determining a plurality of pieces of question information ranked in a sequential order in accordance with the text information; and inputting vector information for each piece of question information into an extraction model in accordance with the sequential order to acquire extraction information for each piece of question information.