Embodiments of devices and methods for evaluating tissue are disclosed. In one embodiment, a method for measuring a characteristic of a tissue may include passing a current through the tissue, measuring a signal corresponding to the voltage resulting from passing the current through the tissue, analyzing current passed through the tissue and resulting voltage to determine the electrical characteristics of the tissue; and analyzing the electrical characteristics of the tissue to determine a status of the tissue. Methods for achieving relatively constant sensor application pressure are disclosed.

Detecting user contact with one or more electrodes of a physiological signal sensor can be used to ensure physiological signals measured by the physiological signal sensor meet waveform characteristics (e.g., of a clinically accurate physiological signal). In some examples, a mobile and/or wearable device can comprise sensing circuitry, stimulation circuitry, and processing circuitry. The stimulation circuit can drive one or more stimulation signals on one or more electrodes, the resulting signal(s) can be measured (e.g., by the sensing circuitry), and the processing circuitry can determine whether a user is in contact with the electrode(s). Additionally or alternatively, in some examples, mobile and/or wearable device can comprise saturation detection circuitry, and the processing circuitry can determine whether the sensing circuitry is saturated.

The exemplified methods and systems (e.g., machine-learned systems) facilitate the use of respiration rate-related features, or parameters, in a model or classifier to estimate metrics associated with the physiological state of a subject, including for the presence or non-presence of a disease, medical condition, or indication of either. The estimated metric may be used to assist a physician or other healthcare provider in diagnosing the presence or non-presence and/or severity and/or localization of diseases, medical conditions, or indication of either or in the treatment of said diseases or indicating conditions. In some cases, such respiration rate-related features are generated from a synthetic respiration waveform that represents, and is used as a proxy to, the true respiration waveform. The synthetic respiration waveform may be used in its own independent diagnostic and/or control applications in some embodiments.

Systems and methods are provided for detecting and analyzing changes in a body. For example, a system includes an electric field generator configured to produce an electric field. The system includes an external sensor device configured to detect physical changes in the electric field, where the physical changes affect amplitude and frequency of the electric field. The system includes a quadrature demodulator configured to detect changes of the frequency of the output of the electric field generator. The system includes an amplitude reference source and an amplitude comparison switch configured to detect changes of the amplitude of the output of the electric field generator. The system includes a signal processor configured to analyze the changes of the amplitude and frequency of the output of the electric field generator.

Disclosed herein is a method and apparatus for determining a parameter of a gas present in an exhaled gas flow comprising: providing an apparatus gas flow with a time-varying parameter to a patient, measuring a parameter of the gas present in a composite gas outflow from the patient, and determining the parameter of the gas present in the exhaled gas flow using the measured parameter of the gas present in the composite gas outflow and the time-varying parameter.

The method for improving measurement accuracy of a measurement system includes: emitting, by a light-emitting unit, at least one light signal to penetrate a human tissue; receiving, by a photoelectric conversion unit, the at least one light signal emitted by the light-emitting unit after penetrating the human tissue, and converting the at least one light signal into an electrical signal; converting, by a analog-to-digital conversion unit, the electrical signal into a digital signal; optimizing, by a signal-to-noise ratio optimization module, a signal-to-noise ratio of the digital signal by establishing at least one of a plurality of logic strategies; adjusting, by the driving adjustment unit, an magnitude of a driving current of the light-emitting unit base on the adjustment coefficient; and performing, by an algorithm processing unit, a physiological parameter conversion and calculation based on the digital signal processed by the at least one logic strategy.

The present invention discloses a brain activity analysis method and apparatus, which is based on a nonlinear waveform decomposition technology, wherein the changes of the intrinsic features in brain waves are decomposed and demodulated to extract the modulation signals of the components, including the frequency-modulation signals and the amplitude-modulation signals. The present invention further uses a feature mask to determine whether to proceed further decomposition and demodulation of the extracted modulation signals. If not, the multidimensional changes of the intrinsic features are obtained according to the feature mask. Then, quantitation and identification is performed to obtain the status of brain function. The present invention not only effectively increases the accuracy of the identification but also uses the feature mask to obviously reduce the complexity and the load of computation.

The present invention provides a system for extension of dynamic range and contrast of a video capture under fluorescence imaging conditions using a single detector. For this purpose, the system (100) comprises of a light engine (107) which sequentially switches between a high-intensity fluorescence excitation light mode (107A), a low-intensity fluorescence excitation light mode (107B) and NIR reflectance light (107C). Correspondingly, a detector (103) captures three data streams—High Intensity Fluorescence Data (105A), Low Intensity Fluorescence Data (105B) and NIR Reflectance Data (105D). A scene processing unit (105) then processes the three data streams and generate two additional data streams—a Wide Dynamic Range Fluorescence Data Stream (105C) and an Enhanced Vascular Index Data Stream (105E). The system also uses a Selective Visualization Unit (106) to allow the user to visualize any of five data streams.

The present disclosure provides a vital sign measuring device and method that may measure a heart rate signal of a living body in a motion state. The method comprises detecting two different signals, using an adaptive noise removal algorithm for removing noise from the two signals, and obtaining a more accurate heat rate signal after a certain operation.

According to the present invention, in a configuration in which a biological signal is received from an attachment-type device including one or more light emitting means and two or more light receiving means, information on a living body is acquired with high accuracy. A modulation unit (110) dims the one or more light emitting means with a specific frequency, a receiving unit (120) receives a biological signal based on the light received from a living body through the two or more light receiving means, and an adjusting unit (130) adjusts the intensity of the biological signal acquired from each light receiving means on the basis of the component of a specific frequency of the biological signal.