Abstract: Aspects of the present disclosure are directed to apparatuses and methods for monitoring vital signs from a human being. Various such aspects involve an apparatus or method involving the monitoring of vital signs in a manner that facilitates enhanced characterization of physiological conditions. In many embodiments, two or more such vital signs are monitored. A signal acquisition, digitization, and computing module removing noise, extracts information useful for diagnosing a health or fitness characteristic of the human being, and/or compresses information to reduce data volume. A wireless communications circuit transmits the vital signs to a receiver.

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: Aspects of the present disclosure are directed to detecting Atrial Fibrillation (AF). As may be implemented in accordance with one or more embodiments, a time series of inter-beat intervals is computed from a recording of activity of a beating heart. The time series is decomposed into subcomponents, and an envelope of at least one of the subcomponents is computed. The presence of atrial fibrillation (AF) is detected based upon characteristics of the envelope that are indicative of AF.

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 process the digitized ECG signals (e.g., by removing noise).

Abstract: Aspects of the present disclosure are directed to detecting Atrial Fibrillation (AF). As may be implemented in accordance with one or more embodiments, a time series of inter-beat intervals is computed from a recording of activity of a beating heart. The time series is decomposed into subcomponents, and an envelope of at least one of the subcomponents is computed. The presence of atrial fibrillation (AF) is detected based upon characteristics of the envelope that are indicative of AF.

Abstract: Aspects of the disclosure are directed to detecting physiological and/or other characteristics of subjects. As may be implemented in accordance with one or more embodiments, a time series of cardiac intervals is computed from a recording of activity of a beating heart of a subject, and the time series is decomposed into subcomponents. An envelope of at least one of the subcomponents is computed, and the presence and/or degree of a depressive or stressed mental state of the subject is detected based upon characteristics of the envelope.

Abstract: Aspects of the present disclosure are directed to processing ECG signals from a subject. As may be implemented in accordance with one or more embodiments, respective electrodes sense ECG signals from a subject, and the ECG signals are digitized and processed, such as to remove noise, detect a QRS complex, evaluate quality, detect arrhythmia and/or to store the signals. In response to an input from the subject, one or more of the ECG signals is recorded along with sound from the user, such as to concurrently record the user's voice for describing conditions in connection with the recording of the ECG signals. This approach can be carried out in an enclosed housing, operated adjacent the subject's thorax. The processed digitized ECG signals and the audio signals are then communicated for receipt by an external device.

Abstract: Monitoring of physiological signals is effected. In accordance with one or more embodiments, an apparatus, system and/or method is directed to sensing physiological signals such as ECG signals. A skin-contacting electrode apparatus includes an electrically conductive sheet having a conductive surface configured and arranged to contact a subject's skin, and conductive flexible microfibers extending from the conductive surface and configured and arranged to protrude into skin pores and sense an ECG signal.

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: Various aspects are directed to identifying a region of interest in a physiological signal. As may be consistent with one or more embodiments, the physiological signal is decomposed into subcomponents, and a subset of the subcomponents is selected based upon overlap of spectral energy with expected spectral energy of the region of interest, in at least one of the subcomponents. At least two of the subcomponents in the subset are combined and compared to a threshold, with the comparison being used to identify the location of the region of interest.

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: Aspects of the present disclosure are directed to detecting Atrial Fibrillation (AF). As may be implemented in accordance with one or more embodiments, a time series of inter-beat intervals is computed from a recording of activity of a beating heart. The time series is decomposed into subcomponents, and an envelope of at least one of the subcomponents is computed. The presence of atrial fibrillation (AF) is detected based upon characteristics of the envelope that are indicative of AF.

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: 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.

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 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: 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: 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.