The present disclosure relates to a device, method and system for calculating, estimating, or monitoring the blood pressure of a subject based on physiological features and personalized models. At least one processor, when executing instructions, may perform one or more of the following operations. A first signal representing a pulse wave relating to heart activity of a subject may be received. A plurality of second signals representing time-varying information on a pulse wave of the subject may be received. A personalized model for the subject may be designated. Effective physiological features of the subject based on the plurality of second signals may be determined. A blood pressure of the subject based on the effective physiological features and the designated model for the subject may be calculated.

Existing wearable device-based approaches to capture a_tremor signal have accuracy limitations due to usage of accelerometer sensor with inherent noisy nature. The method and system disclosed herein taps characteristics of the PPG sensor of being sensitive to the motion artifact, as an advantage, to capture tremor_signals present in the PPG sensor. The method disclosed herein describes an approach to extract tremor_signals of interest from the PPG signal by performing a Singular Spectrum Analysis (SSA) followed by spectrum density estimation. The SSA comprises performing embedding on the acquired PPG signal, performing Principal Component Analysis (PCA) on the embedded signal and reconstructing the rest tremor signal from the significant principal components identified post the PCA. Further, the spectrum density estimation detects a dominant frequency present in the principal components, which is the dominant frequency associated with the rest tremor.

Methods, apparatus and systems for enhanced wireless monitoring of vital signs are described. In one example, a described system comprises: a transmitter configured to transmit a wireless signal through a wireless channel of a venue; a receiver configured to receive the wireless signal through the wireless channel; and a processor. The received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue. The processor is configured for: obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition.

Systems and methods relating to bio-impedance analysis. The system eliminates the need for hardware phase measurements by using the K-K transform to extract the phase from the magnitude detected. The system has a magnitude detection sub-system that includes a signal generation block, a DC cancellation block, and an amplitude control block. An A/D converter converts the detected magnitude into a digital signal and signal processing is performed to extract the phase of the signal from the magnitude detected.

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).

In one aspect, a computer-implemented method includes receiving a signal corresponding to impedance across a patient's chest cavity; filtering the signal using one or more filters that reduce noise and center the signal around a zero baseline; adjusting an amplitude of the filtered signal based on a threshold value; separating the amplitude-adjusted signal into component signals, where each of the component signals represents a frequency-limited band; detecting a fractional phase transition of a component signal of the component signals; selecting a dominant component signal from the component signals based on amplitudes of the component signals at a time corresponding to the detected fractional phase transition; determining a frequency of the dominant component signal at the time corresponding to the detected fractional phase transition; and determining a respiratory rate of the patient based on the determined frequency.

The invention relates to a communication method for communicating monitoring data between a monitoring device (4) and processing means (6), wherein the monitoring device (4) is configured for receiving the monitoring data. The method comprises the steps of sending a byte frame to the processing means (6), storing the byte frame, ordering the byte frame by separating the frame into respiratory rate bytes, heart rate bytes and additional bytes, and repeating the previous steps with a predetermined frequency until the processing means have received a heart rate data set, a respiratory rate data set, and an additional data set. The processing means create heart rate information from the heart rate data set and create respiratory rate information from the respiratory rate data set and display them to a user.

A method for generating stimulation parameters, an electrical stimulation control apparatus and an electrical stimulation system are provided. After receiving a brainwave signal, the brainwave signal is decomposed to obtain a first sub-signal and a second sub-signal. Then, the first sub-signal is analyzed to obtain an intrinsic frequency series, and the second sub-signal is converted to a Boolean signal. Subsequently, the intrinsic frequency series and the Boolean signal, which serve as a set of stimulation parameters, are outputted to the stimulator, enabling the stimulator to generate a stimulus signal.

An electronic device for providing biometric information is provided. The electronic device includes a sensor module, a memory, and a processor electrically connected to the sensor module and the memory. The processor obtains a biometric signal from the sensor module at a predetermined time interval, determines whether a user is in a first state on the basis of the obtained biometric signal, in case the user is in a first state, obtains a representative value for a respective of the at least one biometric signal, defines the obtained representative value for the respective of the at least one biometric signal as a candidate reference value for a corresponding biometric signal, determines a candidate reference value satisfying a predetermined condition as a first reference value for the corresponding biometric signal, and updates a second reference value previously configured for the corresponding biometric signal on the basis of the first reference value.

Some systems, devices and methods detailed herein provide a system for use in determining metrics of a subject. The system can provide, as an output, a function-metric value determined based on a defined relationship between physiological measures and a chronological age.