Patent classifications
A61B5/352
Method and system to detect R-waves in cardiac activity signals
A computer implemented method and system for detecting arrhythmias in cardiac activity are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains far field cardiac activity (CA) signals and applies a direction related responsiveness (DRR) filter to the CA signals to produce DRR filtered signals. The method compares a current sample from the CA signals to a prior sample from the DRR filtered signals to identify a direction characteristic of the CA signals and defines the DRR filter based on a timing constant that is set based on the direction characteristic identified. The method analyzes the CA signals in connection with the DRR filtered signals to identify a peak characteristic of the CA signals and determines peak to peak intervals between successive peak characteristic. The method detects at least one of noise or an arrhythmia based on the peak to peak intervals and records results of the detecting.
Physiological data detection method and wearable device therefor
A physiological data detection method is provided. The physiological data detection method includes the following steps. Firstly, an ECG signal and a PPG signal are detected. Then, a plurality of RRI values is calculated according to the ECG signal, and a plurality of PPI values is calculated according to the PPG signal. Thereafter, wrong RRI values are excluded according to the RRI values and/or the PPI values. Then, whether an abnormal state occurs or not is determined by using the remaining RRI values. A wearable device therefor is also provided.
Physiological data detection method and wearable device therefor
A physiological data detection method is provided. The physiological data detection method includes the following steps. Firstly, an ECG signal and a PPG signal are detected. Then, a plurality of RRI values is calculated according to the ECG signal, and a plurality of PPI values is calculated according to the PPG signal. Thereafter, wrong RRI values are excluded according to the RRI values and/or the PPI values. Then, whether an abnormal state occurs or not is determined by using the remaining RRI values. A wearable device therefor is also provided.
Adaptive Correlation Methods for Heartbeat Detection
A method for detecting heart beats is disclosed. A plurality of sensors are configured to receive a cardiac signal and another cardiac signal or a signal correlated with a noise source. A processor is configured to detect candidate peaks in a cardiac signal and select a subset of the candidate peaks for temporal correlation with features, such as peaks, in another cardiac signal or noise correlated signal. This relationship is quantified by a correlation measure. The correlation measure, in turn, influences the likelihood that a particular peak or sequence corresponds to a heartbeat. Candidate peaks that were not part of the correlation process may then be added to a sequence or sequences associated with the peaks subject to the correlation analysis. Sequences are scored according to quality and a final sequence is selected as possible heartbeats.
Adaptive Correlation Methods for Heartbeat Detection
A method for detecting heart beats is disclosed. A plurality of sensors are configured to receive a cardiac signal and another cardiac signal or a signal correlated with a noise source. A processor is configured to detect candidate peaks in a cardiac signal and select a subset of the candidate peaks for temporal correlation with features, such as peaks, in another cardiac signal or noise correlated signal. This relationship is quantified by a correlation measure. The correlation measure, in turn, influences the likelihood that a particular peak or sequence corresponds to a heartbeat. Candidate peaks that were not part of the correlation process may then be added to a sequence or sequences associated with the peaks subject to the correlation analysis. Sequences are scored according to quality and a final sequence is selected as possible heartbeats.
Apparatus and method for four dimensional soft tissue navigation in endoscopic applications
A surgical instrument navigation system is provided that visually simulates a virtual volumetric scene of a body cavity of a patient from a point of view of a surgical instrument residing in the cavity of the patient. The surgical instrument navigation system includes: a surgical instrument; an imaging device which is operable to capture scan data representative of an internal region of interest within a given patient; a tracking subsystem that employs electro-magnetic sensing to capture in real-time position data indicative of the position of the surgical instrument; a data processor which is operable to render a volumetric, perspective image of the internal region of interest from a point of view of the surgical instrument; and a display which is operable to display the volumetric perspective image of the patient.
Apparatus and method for four dimensional soft tissue navigation in endoscopic applications
A surgical instrument navigation system is provided that visually simulates a virtual volumetric scene of a body cavity of a patient from a point of view of a surgical instrument residing in the cavity of the patient. The surgical instrument navigation system includes: a surgical instrument; an imaging device which is operable to capture scan data representative of an internal region of interest within a given patient; a tracking subsystem that employs electro-magnetic sensing to capture in real-time position data indicative of the position of the surgical instrument; a data processor which is operable to render a volumetric, perspective image of the internal region of interest from a point of view of the surgical instrument; and a display which is operable to display the volumetric perspective image of the patient.
Classifying ECG signals
A method, including receiving a bipolar signal from a pair of electrodes in proximity to a myocardium of a human subject, and receiving a unipolar signal from a selected one of the pair of electrodes. The method further includes delineating a window of interest (WOI) for the unipolar and bipolar signals, within the WOI computing local unipolar minimum derivatives of the unipolar signal, and times of occurrence of the local unipolar minimum derivatives, and within the WOI computing bipolar derivatives of the bipolar signal at the times of occurrence. The method also includes evaluating ratios of the bipolar derivatives to the local unipolar minimum derivatives, and when the ratios are greater than a preset threshold ratio value, assigning the times of occurrence as times of activation of the myocardium, counting a number of the times of activation; and classifying the unipolar signal according to the number.
Classifying ECG signals
A method, including receiving a bipolar signal from a pair of electrodes in proximity to a myocardium of a human subject, and receiving a unipolar signal from a selected one of the pair of electrodes. The method further includes delineating a window of interest (WOI) for the unipolar and bipolar signals, within the WOI computing local unipolar minimum derivatives of the unipolar signal, and times of occurrence of the local unipolar minimum derivatives, and within the WOI computing bipolar derivatives of the bipolar signal at the times of occurrence. The method also includes evaluating ratios of the bipolar derivatives to the local unipolar minimum derivatives, and when the ratios are greater than a preset threshold ratio value, assigning the times of occurrence as times of activation of the myocardium, counting a number of the times of activation; and classifying the unipolar signal according to the number.
Method and apparatus for monitoring respiratory distress based on autonomic imbalance
An example of a system for monitoring and treating respiratory distress in a patient may include signal inputs, a signal processing circuit, and a respiratory distress analyzer. The signal inputs may be configured to receive patient condition signals indicative of autonomic balance of the patient. The signal processing circuit may be configured to process the patient condition signals and to generate patient condition parameters indicative of the autonomic balance using the processed patient condition signals. The respiratory distress analyzer may be configured to determine a state of the respiratory distress using the patient condition parameters, and may include a parameter analysis circuit configured to analyze the autonomic balance of the patient and to determine the state of the respiratory distress using an outcome of the analysis.