A wearable device according to the present disclosure includes: a communication portion; a body fluid sensor configured to measure conductivity in body fluid; and a controller configured to control the communication portion to transmit conductivity data to an external device in response to the frequency of rapid change in the conductivity.

A wearable device according to the present disclosure includes: a communication portion; a body fluid sensor configured to measure conductivity in body fluid; and a controller configured to control the communication portion to transmit conductivity data to an external device in response to the frequency of rapid change in the conductivity.

A hemodynamic parameter (Hdp) monitoring system for diagnosing a health condition of a patient and for establishing Hdp marker values or Hdp surrogate marker values for purposes of comparison with Hdp values of a patient is provided. An Hdp monitor senses, measures, and records Hdp values exhibited by the patient during a basal or non-exposure period and furthermore Hdp values exhibited by the patient during or after an exposure period during which the patient is exposed to low-energy electromagnetic output signals. An electrically-powered generator is adapted to be actuated to generate said low-energy electromagnetic carrier output signals for exposing or applying to the patient such output signals during said exposure period.

A hemodynamic parameter (Hdp) monitoring system for diagnosing a health condition of a patient and for establishing Hdp marker values or Hdp surrogate marker values for purposes of comparison with Hdp values of a patient is provided. An Hdp monitor senses, measures, and records Hdp values exhibited by the patient during a basal or non-exposure period and furthermore Hdp values exhibited by the patient during or after an exposure period during which the patient is exposed to low-energy electromagnetic output signals. An electrically-powered generator is adapted to be actuated to generate said low-energy electromagnetic carrier output signals for exposing or applying to the patient such output signals during said exposure period.

Methods for calculating a MetaKG signal are provided. The method including illuminating a region of interest in a sample with a near-infrared (NIR) light source and/or a visible light source. The region of interest includes a sample portion and background portion, each having a different set of optical characteristics. Images of the region of interest are acquired and processed to obtain metadata associated with the acquired images. MetaKG signals are calculated for the region of interest and for the background. The MetaKG signal for the background is used to adjust the MetaKG signal for the region of interest to provide a final adjusted MetaKG signal for the region of interest.

Methods for calculating a MetaKG signal are provided. The method including illuminating a region of interest in a sample with a near-infrared (NIR) light source and/or a visible light source. The region of interest includes a sample portion and background portion, each having a different set of optical characteristics. Images of the region of interest are acquired and processed to obtain metadata associated with the acquired images. MetaKG signals are calculated for the region of interest and for the background. The MetaKG signal for the background is used to adjust the MetaKG signal for the region of interest to provide a final adjusted MetaKG signal for the region of interest.

A device including an array of electrodes generates one or more electrical signals from a user, extracts one or more noise signals, and generates one or more de-noised electrical signals upon processing the electrical signal(s) with the noise signal(s). The array of electrodes is coupled to a surface of the device, where the device also includes force sensors in mechanical communication with the surface for detecting user weight and other forces. The device can be configured to generate electrical signals from different subportions of the array of electrodes and to extract noise signals from different subportions of the array of electrodes, where the subportion(s) for electrical signal generation may or may not overlap with the subportion(s) of electrodes for noise signal extraction.

The present disclosure provides a system and method for image data acquisition. The method may include acquiring physiological data of a subject. The physiological data may correspond to a motion of the subject over time. The method may include obtaining a trained machine learning model configured to detect feature data represented in the physiological data. The method may include determining, based on the physiological data, an output result of the trained machine learning model that is generated based on the feature data. The method may include acquiring, based on the output result, image data of the subject using an imaging device.

A portable electrocardiographic device configured to measure an electrocardiographic waveform using a plurality of types of lead systems includes an electrode unit configured to be brought into contact with a subject's body and measure an electrocardiographic waveform, an analysis unit configured to analyze the electrocardiographic waveform measured by the electrode unit in accordance with a lead system at a time of measurement of the electrocardiographic waveform, a storage unit configured to store the electrocardiographic waveform measured at the electrode unit, the lead system, and an analysis result of the electrocardiographic waveform analyzed by the analysis unit in association with one another, and a remeasurement facilitating unit configured to prompt a user, when the analysis result or a state of the measured electrocardiographic waveform satisfies a predetermined condition, for remeasurement in a predetermined lead system different from the lead system at the time of the measurement of the electrocardiographic waveform.

A smart hardware security engine using biometric features and hardware-specific features is provided. The smart security engine can combine one or more entropy sources, including individually distinguishable biometric features, and hardware-specific features to perform secret key generation for user registration and authentication. Such hybrid signatures may be distinct from person-to-person (e.g., due to the biometric features) and from device-to-device (e.g., due to the hardware-specific features) while varying over time. Thus, embodiments described herein can be used for personal device authentication as well as secret random key generation, significantly reducing the scope of an attack.