Abstract: Physiological signals are denoised. In accordance with an example embodiment, a denoised physiological signal is generated from an input signal including a desired physiological signal and noise. The input signal is decomposed from a first domain into subcomponents in a second domain of higher dimension than the first domain. Target subcomponents of the input signal that are associated with the desired physiological signal are identified, based upon the spatial distribution of the subcomponents. A denoised physiological signal is constructed in the first domain from at least one of the identified target subcomponents.

Abstract: Physiological signals such as ECG signals are obtained from a patient. In accordance with one or more embodiments, an apparatus, system and/or method is directed to at least two ECG sensing electrodes that adhere to remote locations on a patient and sense ECG signals from the patient. An amplifier circuit amplifies the sensed ECG signals to provide amplified ECG signals, and a digitizing circuit digitizes the amplified ECG. A computing circuit processes the digitized ECG signals (e.g., by removing noise). A battery powers the aforesaid circuits, and a housing houses the battery and aforesaid circuit. A fastener mechanically fastens and electrically couples the housing to one of the electrodes, and the other electrodes are coupled to the amplifier via a flexible insulated lead wire.

Abstract: Various embodiments are directed to signal processing. In accordance with example embodiments, methods and apparatuses involve using at least two electrodes that sense an ECG signal. A denoising module is communicatively coupled to the at least two electrodes, and receives the ECG signal sensed by the sensing electrodes. The denoising module includes circuitry that conditions and digitizes the ECG signal, and a computing circuit that processes the digitized ECG signal to denoise the ECG signal. A communications circuit generates a communication including the denoised ECG signal for access by a remote device.

Abstract: A parameter value is computed for a segment of a cardiac-related signal. In accordance with various example embodiments, a system includes a computer circuit configured to identify cardiac cycles within a segment of a cardiac-related signal, such as an ECG. At least one feature point is identified within the cardiac cycles. For each identified feature point, a signal-to-noise ratio (SNR) representative of the ratio of signal energy to noise energy is computed for a cardiac cycle subsegment containing the identified feature point. A validity characteristic of the feature point is determined based upon the signal-to-noise ratio, and a parameter value is computed by combining feature points contained within the segment, based upon the determined validity characteristics of the feature points.

Abstract: A cardiac-based metric is computed based upon characteristics of a subject's cardiac function. In accordance with one or more embodiments, the end of a mechanical systole is identified for each of a plurality of cardiac cycles of a subject, based upon an acoustical vibration associated with closure of an aortic valve during the cardiac cycle. The end of an electrical systole of an electrocardiogram (ECG) signal for each cardiac cycle is also identified. A cardiac-based metric is computed, based upon a time difference between the end of the electrical systole and the end of the mechanical systole, for the respective cardiac cycles.

Abstract: A T-wave offset point of an ECG signal is provided. In accordance with various example embodiments, a location of a QRS complex in the ECG signal is identified and used to determine a first time window of the ECG signal in which to search for a T-wave offset point. The T-wave offset point is identified within the first time window, and the identified T-wave offset point is provided as an output based upon a noise characteristic of the ECG signal in a second time window that includes at least a portion of the T-wave.