A process for measuring heart beats fiducial points and classifying heart beats includes sampling a raw ECG signal,—providing a first filtered signal,—providing a second filtered signal, detecting left and right limits data for the beats in said second filtered signal, and receiving the first filtered signal and receiving said left and right limits data, sampling and storing ECG curve data of beats from said first filtered signal synchronized by said left and right limits data and extracting fiducial points of said beats from said ECG curve data, said fiducial points including at least the QRS points values of the beats, and classifying each of said beats in classes based on a correlation of its ECG curve data with respect to average ECG curves data of classes of previously averaged classified beats.

Various embodiments of a physiological waveform summarizing system of the present disclosure encompass a clinical physiological waveform (CPW) interface (20), and a physiological waveform summarizing monitor (30). In operation, the monitor (30) extracts a set of dominant physiological templates (41) from a clinical physiological waveform (CPW) communicated by the interface (20) to the monitor (30). The set of dominant physiological templates (41) represent a dominating major physiological rhythm (DMPR) of the clinical physiological waveform (CPW) temporally spanning over consecutive intervals of the clinical physiological waveform (CPW), and each dominant physiological template (41) is derived from a different interval of the consecutive intervals of the clinical physiological waveform (CPW). The monitor (30) may extract one or more secondary physiological templates (42) representative of secondary major physiological rhythm(s) (SMPR) present in the clinical physiological waveform (CPW), and provide a diagnostic major physiological rhythm log of the clinical physiological waveform (CPW) including a diagnostic plotting of the dominant physiological templates (41) and any secondary physiological template(s) (42).

A detection result output method, an electronic device, and a medium are provided. The detection result output method includes: obtaining first image information of a first object, where the first image information includes skin information of the first object; outputting a target detection result in a case that a matching degree between a first image and a target image meets a first preset condition; and outputting a first detection result in a case that the matching degree between the first image and the target image does not meet the first preset condition. The target detection result is a detection result corresponding to the target image, and the first detection result is a detection result corresponding to the first image.

Systems and methods to determine a risk factor related to dehydration and thermal stress of a subject are disclosed. Exemplary implementations may: generate output signals, by one or more sensors worn on a body of a subject, conveying information related to one or more of location of the subject, motion of the subject, temperature of the subject, cardiovascular parameters of the subject; store information related to the subject; obtain the output signals; determine in an ongoing manner, from the output signals, values of a water loss metric that correlates with estimated percentage of bodyweight of the subject lost in water; obtain heat index information for a contextual environment surrounding the subject; determine in an ongoing manner, from the output signals, values of an exertion metric that correlates with exertion of the subject due to work; and determine in an ongoing manner values for an aggregated risk factor of the subject.

The invention provides a system and method for determining a respiratory effort for a subject. The method comprises obtaining a relaxed signal representing a subject breathing in a relaxed manner and a forced signal representing a subject breathing in a forced manner. The relaxed signal is then smoothed over a first averaging window and the forced signal is smoothed over a second averaging window, wherein the first averaging window is longer than the second averaging window. Based on the smoothed relaxed signal and the smoothed forced signal, a respiratory effort can thus be determined.

Various methods and systems are provided for analyzing an electrocardiogram (ECG) in real-time using machine learning to identify heartbeats, calculate a cycle length for each heartbeat, and display the cycle length for each heartbeat at a user interface. Waveform morphology of ECG data is continuously learned to identify recurrent signals and generate templates based on recurrent signals, to which ECG data is compared to identify and display heartbeats. Generated templates are continuously updated to reflect changing waveform morphologies.

An ECG monitoring device includes a vibration meter sensor unit including at least one vibration meter sensor attached to an instrument at which a person to be observed is positioned, and configured to acquire a vibration signal by detecting a vibration transmitted through the instrument in a non-contact or non-invasive method, a filter unit configured to extract a seismocardiography signal (“SCG signal”) generated by a heart vibration of the person to be observed by receiving the vibration signal and filtering a predetermined frequency band from the received vibration signal, and an ECG waveform acquisition unit including an artificial neural network learned in advance and configured to generate an electrocardiogram signal (“ECG signal”) corresponding to the applied SCG signal according to a learned method.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

Method, device and system for providing consistent and reliable glucose response information to physiological changes and/or activities is provided to improve glycemic control and health management.

The present invention relates to a method and system for estimating blood pressure of a subject. In particular, but not exclusively, the method involves receiving a photoplethysmogram (PPG) signal from a light-based Pulse-Plethysmography sensor applied to the skin of a subject and reconstructing a pulse blood pressure waveform between systolic and diastolic blood pressure of the subject. Additionally, but not exclusively, the method involves processing the pulse blood pressure waveform and reconstructing an absolute blood pressure waveform of the subject.