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.

Data-stream bridging for sensor transitions is described. A first data stream of glucose measurements is received from a first glucose sensor worn by a user. A termination event for the first glucose sensor is detected when production and/or communication of the first glucose measurements via the first data stream ceases. Next, a second data stream of glucose measurements is received from a second glucose sensor worn by the user that replaces the first glucose sensor. During a warmup period for the second glucose sensor, estimated glucose values are output for the user based on both the first data stream of glucose measurements received from the first glucose sensor prior to the termination event and the second data stream of glucose measurements received from the second glucose sensor.

A motion data processing method and a motion monitoring system provided in the present disclosure may process an electromyography (EMG) signal in the frequency domain or time domain to identify an abnormal signal in the EMG signal, such as an abrupt signal, a missing signal, a saturation signal, an oscillation signal, etc. caused by a high-pass filtering algorithm. The motion data processing method and the motion monitoring system may further perform a data sampling operation on the EMG signal through a data sampling algorithm, and predict data corresponding to the time point when the abnormal signal appears based on the sampling data, so as to obtain prediction data, and replace the abnormal signal by using the prediction data to correct the abnormal signal. The motion data processing method and the motion monitoring system may not merely accurately identify the abnormal signal, but further correct the abnormal signal, so that the corrected data may be more in line with an actual motion of a user, thereby improving user experience.

A mental and physical condition estimation system according to the present disclosure includes: a heart rate information acquisition unit for acquiring heart rate information that is information related to a heart rate of a subject person; a heart rate variability calculation unit for calculating heart rate variability of a very low frequency component (VLF) from the acquired heart rate information; and a mental and physical condition estimation unit for estimating a concentration and effort state of the subject person from a calculated value of the heart rate variability.

A method for estimating a measure of cardiovascular health of a subject comprises: receiving (106) time-based sequences of at least a first and a second artery signal, each representative of pressure pulse wave propagation in an artery and representing pressure pulse wave propagation in positions displaced in relation to each other in the artery; fitting (110) a first and a second waveform to a portion of the time-based sequences to form a first and a second waveform of the first artery signal and a first and a second waveform of the second artery signal, wherein the first waveforms represent a forward propagating wave and the second waveforms represent a backward propagating wave; and determining (112) at least one parameter based on the fitting, wherein the at least one parameter comprises a forward velocity of the pressure pulse wave propagation as a representation of local pulse wave velocity in the artery.

A bed comprises substrate support members, each including a load bearing and a base configured to provide contact with a floor. The load bearing member is configured to move vertically relative to the base, while the base and the load bearing member are configured to fit together to maintain lateral alignment of the base and the load bearing member. A load sensor is positioned between the base and the load bearing member, the load bearing member configured to transmit a load from the substrate to the load sensor. A printed circuit board is in communication with the load sensor. A controller is in communication with the printed circuit board of each substrate support member and is configured to receive and process data output by the printed circuit boards.

A non-invasive method and apparatus utilizing a single wavelength (800 nm, isobestic) for the instantaneous, reflective, non-pulsatile spatially resolved reflectance system, apparatus and mathematics that allows for the correct determination of critical photo-optical parameters in vivo. Transcutaneous blood constituent (analyte or drug level) measurements can be determined in real-time. The “closed-form” nature of the mathematics with inclusion of other wavelengths (660 nm and 1300 nm) and a non-invasive transmissive array allows for immediate calculation and real-time display of Hematocrit, Hemoglobin, fractional tissue blood volume (Xb), Hematocrit-Independent Oxygen Saturation, fractional tissue water content (Xw) and other pertinent blood/plasma values in a variety of handheld or other like devices.

A system for monitoring a patient includes an inflatable cuff configured to at least partially occlude an artery of the patient, and a sensor configured to determine a first parameter associated with the at least partially occluded artery and to generate an output signal indicative of the first parameter. The system also includes a processor configured to receive the output signal and information indicative of an occlusion efficiency of the cuff. The processor is configured to determine a hemodynamic parameter of the patient based on the output signal and the information.

The apparatus for calculating blood pressure using a digital ECG voltage coordinate value comprising an X coordinate of a time axis and a Y coordinate of a heart voltage signal intensity axis, the apparatus comprising an acquiring unit for acquiring a target digital ECG voltage coordinate value of the measurement subject, and an arithmetic unit for calculating a systolic blood pressure and a diastolic blood pressure by comparing previously stored reference digital ECG voltage coordinate values and acquired digital ECG voltage coordinate values, respectively. the acquired target digital ECG voltage coordinate value includes: a specific coordinate value (Q.sub.PT value) representing an inflection point of a Q waveform; a specific coordinate value (R.sub.PT value) representing an inflection point of an R waveform; a specific coordinate value (T.sub.PT value) representing an inflection point of a T waveform; and a specific coordinate value (S.sub.PT value) representing an inflection point of an S waveform.

An electronic device may include a housing and a PhotoPlethysmoGram (PPG) sensor disposed inside the housing. The PPG sensor may include a first Light Emitting Diode (LED) configured to generate light in a first wavelength band, a second LED configured to generate light in a second wavelength band, a third LED configured to generate light in a third wavelength band, a fourth LED configured to generate light in a fourth wavelength band, and a light receiving module including at least one photo diode. The electronic device may include a processor operatively coupled with the PPG sensor and a memory operatively coupled with the processor. The memory may include instructions that, when executed, cause the processor to measure optical densities of the light generated by the first LED to the fourth LED, and calculate a blood glucose value based at least in part on the measured optical densities.