Abstract: A wearable device can include one or more sensors including one or more motion sensors. The data from the one or more motion sensors can include an indication of respiration, and the data can be processed to enable screening for physiological events, such as breathing disturbances associated with apnea/hypopnea events. In some examples, one or more features are extracted from the data. In some examples, to improve performance, one or more masks can be applied to the data from the one or more sensors. For example, the one or more masks can be used to perform processing on data from the one or more sensors when a user is determined to be sleeping and when the data from the one or more sensors is determined to be indicative of a quality respiration signal.

Abstract: The present disclosure presents arrhythmia analysis systems and methods. One such method comprises processing an acquired ECG waveform signal to remove noise artifacts and form a denoised ECG waveform signal; processing the denoised ECG waveform signal to remove low quality segments and form a high quality ECG waveform signal; analyzing the high quality ECG waveform to detect a presence of a beat-independent ventricular arrhythmia; processing the denoised ECG signal to extract beat (R-peak) locations corresponding to QRS complexes from the denoised ECG signal; analyzing the denoised ECG signal to detect a presence of a beat-dependent ventricular arrhythmia based on the extracted beat (R-peak) locations; analyzing the denoised ECG signal to detect a presence of one or more supraventricular arrhythmias based on the extracted beat locations of the ECG signal; and outputting a report containing one or more arrhythmias detected by the analyzing steps. Other methods/systems are also provided.

Abstract: The present disclosure presents arrhythmia analysis systems and methods. One such method comprises processing an acquired ECG waveform signal to remove noise artifacts and form a denoised ECG waveform signal; processing the denoised ECG waveform signal to remove low quality segments and form a high quality ECG waveform signal; analyzing the high quality ECG waveform to detect a presence of a beat-independent ventricular arrhythmia; processing the denoised ECG signal to extract beat (R-peak) locations corresponding to QRS complexes from the denoised ECG signal; analyzing the denoised ECG signal to detect a presence of a beat-dependent ventricular arrhythmia based on the extracted beat (R-peak) locations; analyzing the denoised ECG signal to detect a presence of one or more supraventricular arrhythmias based on the extracted beat locations of the ECG signal; and outputting a report containing one or more arrhythmias detected by the analyzing steps. Other methods/systems are also provided.

Abstract: A wearable device including a motion-tracking sensor can be used for tracking sleep. The data from the motion-tracking sensor can be to estimate/classify the sleep state for multiple periods and/or to determine sleep intervals. In some examples, to improve performance, sleep state classification can be performed on data within a sleep tracking session. The start of the sleep tracking session can be defined by detecting a rest state and the end of the sleep tracking session can be defined by an activity state. In some examples, to improve performance, the classified sleep states for the multiple periods can be filtered and/or smoothed. In some examples, a signal quality check can be performed for the data from the motion-tracking sensor. In some examples, the classification of the sleep states and/or the display of the results of sleep tracking can be subject to passing one or more signal quality checks.

Abstract: The present disclosure presents arrhythmia analysis systems and methods. One such method comprises processing an acquired ECG waveform signal to remove noise artifacts and form a denoised ECG waveform signal; processing the denoised ECG waveform signal to remove low quality segments and form a high quality ECG waveform signal; analyzing the high quality ECG waveform to detect a presence of a beat-independent ventricular arrhythmia; processing the denoised ECG signal to extract beat (R-peak) locations corresponding to QRS complexes from the denoised ECG signal; analyzing the denoised ECG signal to detect a presence of a beat-dependent ventricular arrhythmia based on the extracted beat (R-peak) locations; analyzing the denoised ECG signal to detect a presence of one or more supraventricular arrhythmias based on the extracted beat locations of the ECG signal; and outputting a report containing one or more arrhythmias detected by the analyzing steps. Other methods/systems are also provided.