Disclosed is a bioimpedance measurement system: A stabilized high frequency current generator is connected to PadSet electrodes via a Patient Cable. Electrodes are connected to an adaptive circuit that conditions the resulting voltage signal and converts it to digital form. Firmware performs signal acquisition and relays data to the device.

A device, method and system for calculating, estimating, or monitoring the blood pressure of a subject. A first signal representing heart activity of a subject may be received. A plurality of second signals representing time-varying information on at least one pulse wave of the subject may be received from a plurality of body locations of the subject. A first feature of the first signal may be identified. For each of the plurality of second signals, a second feature may be identified. A pulse transit time based on a difference of the first feature and at least one of the second features may be computed. A blood pressure of the subject may be calculated according to a model based on the computed pulse transit time. The model may include a compensation term relating to the plurality of second signals or the second features thereof.

The present application provides a personal hand-held monitor for the measurement of a subject's blood pressure and, optionally, one or more other vital signs, comprising a housing located on a personal hand-held computing device or a hand-held component of a computing system; a blood flow occlusion means located in the housing; a pressure sensor adapted to provide an electrical signal indicative of the pressure applied; a means for detecting the flow of blood in the body part of the subject when pressure is applied; and means for receiving electrical signals from the pressure sensor and the blood flow detecting means and for transmitting electrical signals indicative of the pressure and blood flow to the processor of the personal hand-held computing device or the computing system, wherein the processor of the personal hand-held computing device or computing system provide at least a measurement of the blood pressure of a subject. The processor is further adapted to carry out a process to measure a diastolic blood pressure value and a systolic blood pressure value.

A system for performing at least one impedance measurement on a biological subject, the system including a measuring device having a signal generator that generates a drive signal, a sensor that measures a response signal and a measuring device processor that at least in part controls the at least one signal generator and receives an indication of a measured response signal from the at least one sensor, allowing the at least one impedance measurement to be performed. The system also includes a connectivity module having a connectivity module housing and electrodes that are provided in electrical contact with the subject in use. Respective first and second connectors are used to electrically connect the sensor and signal generator to the electrodes allowing a drive signal to be applied to the subject via first electrodes and allowing the response signal to be measured via second electrodes so that the at least one impedance measurement can be performed.

Certain exemplary embodiments can provide an apparatus wearable by a user. The apparatus can comprise a biometric sensor constructed to generate signals based upon measurements of the user. The apparatus can comprise a processor constructed to determine a significant detrimental change in the user via an algorithm based upon the signals.

Provided is an apparatus for estimating a target component, the apparatus including a temperature controller configured to modulate temperature of an object, a measurer configured to measure a spectrum for each temperature of the object that changes based on the modulation, and a processor configured to obtain effective optical pathlength vectors corresponding to a temperature change based on the spectrum for each temperature of the object, obtain a representative effective optical pathlength based on the obtained effective optical pathlength vectors, and obtain a target component estimation model based on the obtained representative effective optical pathlength.

The disclosed method may include receiving neuromuscular activity data over a first time series from a first sensor on a wearable device donned by a user receiving ground truth data over a second time series from a second sensor that indicates a body part state of a body part of the user, generating one or more training datasets by time-shifting at least a portion of the neuromuscular activity data over the first time series relative to the second time series, to associate the neuromuscular activity data with at least a portion of the ground truth data, and training one or more inferential models based on the one or more training datasets. Various other related methods and systems are also disclosed.

A gas analyzer for measuring a respiratory gas component includes an emitter that transmits infrared (IR) radiation through a measurement chamber containing respiration gas, and at least one IR detector configured to receive at least a portion of the IR radiation transmitted through the measurement chamber and to generate radiation measurement data based on the received IR radiation. A light source is configured to emit light onto a color indicator, wherein the color indicator is one of a predefined set of colors. A color detector is configured to detect light reflected by a color indicator so as to identify color information. The controllers configured to determine a respiratory gas component concentration within the measurement chamber based on the color information and the radiation measurement data.

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.

The present invention relates to a method for calibrating on-line a direct neural interface implementing a REW-NPLS regression between an output calibration tensor and an input calibration tensor. The REW-NPLS regression comprises a PARAFAC iterative decomposition of the cross covariance tensor between the input calibration tensor and the output calibration tensor, each PARAFAC iteration comprising a sequence of M elementary steps (240.sub.1, 240.sub.1, . . . 240.sub.M) of minimisation of a metric according to the alternating least squares method, each elementary minimisation step relating to a projector and considering the others as constant, said metric comprising a penalisation term that is a function of the norm of this projector, the elements of this projector not being subjected to a penalisation during a PARAFAC iteration f not being penalisable during following PARAFAC iterations. Said calibration method makes it possible to obtain a predictive model of which the non-zero coefficients are sparse blockwise.