Abstract: Methods, systems, and apparatuses are described for automated external defibrillation for determining shock/no-shock decisions based on ECG readings taken when a patient is undergoing cardiopulmonary resuscitation (CPR). A device may filter an ECG signal of a patient to reduce artifacts from the signal caused by CPR being performed on the patient. The device may use the filtered ECG signal to determine whether to deliver a therapeutic shock to a patient even if the patient is undergoing CPR.

Abstract: Methods, systems and apparatuses for determining oxygen toxicity in users is disclosed. Electrodermal activity (EDA) data from a sensor may be received. The EDA data may be indicative of one or more physiological signals derived from sweat gland activity of the user. Time-varying index values may be determined based on the EDA data. The time-varying index values may be compared to a threshold to determine if one or more of the values satisfies the threshold. Satisfying the threshold may indicate oxygen toxicity is occurring within the user. A notification may be caused to occur based on the time-varying index value satisfying the threshold. The notification may cause the user to take actions to reduce the potential for further oxygen toxicity.

Abstract: The present disclosure relates to techniques for the estimating anomalies within photoplethysmographic signals. The techniques may include use of instruments that include photoplethysmographic and acceleration sensors. Time-frequency spectra may be used to determine the anomalies. Corrupted signals may be detected and corrected through applications of machine learning and feature extraction.

Abstract: A pulse oximeter embedded with a motion and noise artifact (MNA) detection algorithm based on extraction of time-varying spectral features that are unique to the clean and corrupted components.

Abstract: A real-time arrhythmia discrimination method is used in smartphones, which can discriminate between NSR, AF, PACs and PVCs using pulsatile time series collected from a smartphone's camera. To increase the sensitivity of AF detection and add the new capabilities of PVC and PAC identification, the arrhythmia discrimination method of these teachings combines Root Mean Square of Successive RR Differences (RMSSD), Shannon Entropy (ShE) and turning point ratio (TPR), with the Poincare plot, and utilizes the features of pulse rise/fall time and amplitude for arrhythmia discrimination.

Abstract: A method and corresponding apparatus employ a time-varying spectral analysis approach for reconstructing a heart-related signal that includes motion artifacts. The motion artifacts are produced by motion of a biomedical sensor relative to a sensing location. By comparing time-varying spectra of the heart-related signal and a motion signal, those frequency peaks resulting from the motion artifacts may be suppressed in a time-varying spectrum of the heart-related signal. The time-varying spectral analysis based approach enables the heart-related signal to be reconstructed with accuracy by suppressing the motion artifacts. Example applications for the method and corresponding apparatus include training aids (e.g., runners' heart-rate monitors) and hospital patient heart-rate monitors.

Abstract: A real-time arrhythmia discrimination method is used in smartphones, which can discriminate between NSR, AF, PACs and PVCs using pulsatile time series collected from a smartphone's camera. To increase the sensitivity of AF detection and add the new capabilities of PVC and PAC identification, the arrhythmia discrimination method of these teachings combines Root Mean Square of Successive RR Differences (RMSSD), Shannon Entropy (ShE) and turning point ratio (TPR), with the Poincare plot, and utilizes the features of pulse rise/fall time and amplitude for arrhythmia discrimination.

Abstract: A real-time arrhythmia discrimination method is used in smartphones, which can discriminate between NSR, AF, PACs and PVCs using pulsatile time series collected from a smartphone's camera. To increase the sensitivity of AF detection and add the new capabilities of PVC and PAC identification, the arrhythmia discrimination method of these teachings combines Root Mean Square of Successive RR Differences (RMSSD), Shannon Entropy (ShE) and turning point ratio (TPR), with the Poincare plot, and utilizes the features of pulse rise/fall time and amplitude for arrhythmia discrimination.

Abstract: Accurate AR method for extracting respiratory rates directly from a pulse oximeter and accurate methods of extracting respiratory rates directly from a pulse oximeter under low signal-to-noise ratio (SNR) conditions.

Abstract: A method and corresponding apparatus employ a time-varying spectral analysis approach for reconstructing an electrocardiogram (ECG) signal that includes motion artifacts. The motion artifacts are produced by motion of an ECG sensor relative to a sensing location. The time-varying spectral analysis based approach enables the ECG signal to be reconstructed with accuracy by suppressing the motion artifacts. Example applications for the method and corresponding apparatus include ECG-based heart rate monitoring in wearable devices for fitness tracking and health monitoring even during intense physical activities.

Abstract: Systems and methods that enable physiological monitoring with a mobile communication device and that allow detection of motion artifacts so that the results reported are of acceptable quality are disclosed.

Abstract: A method and corresponding apparatus for monitoring breathing computes a calibration signal from a first sequence of images of a user's chest to produce a calibration model.. The calibration signal is representative of movement of the user's chest during a first time period during which the user is using an incentive spirometer a commercially-available (IS). The first sequence of images corresponds to the first time period. A method and corresponding apparatus employ the calibration model to produce a breathing information estimate about the user's breathing from a second sequence of images of the user's chest corresponding to a second time period during which the user is not using the a commercially-available IS. Example applications for the method and corresponding apparatus include vital sign applications for personalized healthcare through use of a smartphone.

Abstract: Systems and methods that can distinguish clean from corrupted PPG signals under various types of motions and reconstruct the MNA contaminated data segments, such that biological parameters, e.g., heart rates and SpO2 values, can be accurately estimated, are disclosed.

Abstract: A method and corresponding apparatus employ a time-varying spectral analysis approach for reconstructing an electrocardiogram (ECG) signal that includes motion artifacts. The motion artifacts are produced by motion of an ECG sensor relative to a sensing location. The time-varying spectral analysis based approach enables the ECG signal to be reconstructed with accuracy by suppressing the motion artifacts.

Abstract: A method and corresponding apparatus employ a time-varying spectral analysis approach for reconstructing a heart-related signal that includes motion artifacts. The motion artifacts are produced by motion of a biomedical sensor relative to a sensing location. By comparing time-varying spectra of the heart-related signal and a motion signal, those frequency peaks resulting from the motion artifacts may be suppressed in a time-varying spectrum of the heart-related signal. The time-varying spectral analysis based approach enables the heart-related signal to be reconstructed with accuracy by suppressing the motion artifacts. Example applications for the method and corresponding apparatus include training aids (e.g., runners' heart-rate monitors) and hospital patient heart-rate monitors.

Abstract: An apparatus and method for non-invasive monitoring and detection of sudden changes in cardiovascular hemodynamics, in which a PPG signal is obtained from a patient, a time-frequency spectrum (TFS) is computed from the PPG signal, instantaneous modulations at a plurality of time points defining a curve of a prominent frequency of oscillation are extracted from the TFS, a peak power spectral density sequence is computed using the instantaneous modulations, and instantaneous peak values for following prominent frequency oscillations are monitored.

Abstract: Enhanced real-time realizable AF algorithm for accurate detection of, and discrimination between, NSR, AF, PVC, and PAC. The method of these teachings includes an AF detection method having a modified Poincare approach in order to differentiate various patterns of PAC and PVC from NSR and AF. The method of these teachings can also apply to the Kullback-Leibler divergence or the Turning Point Ratio (TPR) to differentiate between various patterns of PAC and PVC from NSR and AF.

Abstract: A pulse oximeter embedded with a novel motion and noise artifact (MNA) detection algorithm based on extraction of time-varying spectral features that are unique to the clean and corrupted components.

Abstract: Provided are an apparatus and method for estimating a breathing rate using a microphone, which performs band filtering and noise filtering on tracheal and nasal sounds collected from the microphone, selects a processing region of preprocessed data, calculates similarity between pieces of data using an autocorrelation function, calculates a power spectrum density, detects multiple peaks including a highest peak through the power spectrum density, analyzes the multiple peaks to determine a breathing pattern, and calculates a breathing rate in consideration of a dynamic characteristic between inhalation and exhalation, nasal congestion detection, and noise reduction. Accordingly, it is possible to accurately estimate the breathing rate because calculation is performed in consideration of a dynamic characteristic of inhalation and exhalation, nasal congestion, and white noise.

Abstract: A real-time arrhythmia discrimination method is used in smartphones, which can discriminate between NSR, AF, PACs and PVCs using pulsatile time series collected from a smartphone's camera. To increase the sensitivity of AF detection and add the new capabilities of PVC and PAC identification, the arrhythmia discrimination method of these teachings combines Root Mean Square of Successive RR Differences (RMSSD), Shannon Entropy (ShE) and turning point ratio (TPR), with the Poincare plot, and utilizes the features of pulse rise/fall time and amplitude for arrhythmia discrimination.