A computer apparatus and methods generate multi-parametric color composite images from multi-echo chemical shift encoded (CSE) MRI. Some embodiments use inherently co-registered images (i.e., image maps) that are combined into a single intuitive composite color image. The color (e.g., brightness, hue, and/or saturation) reflects in part the water and fat content, and other properties, particularly T2* relaxation (related to magnetic susceptibility) of the tissue.

The present disclosure provides systems and methods for predicting a disease state of a subject using ultrasound imaging and ancillary information to the ultrasound imaging. At least two quantitative measurements of a subject, including at least one measurement taken using ultrasound imaging, as part of quantified information can be identified. One of the quantitative measurements can be compared to a first predetermined standard, included as part of ancillary information to the quantified information, in order to identify a first initial value. Further, another of the quantitative measurements can be compared to a second predetermined standard, included as part of the ancillary information, in order to identify a second initial value. Subsequently, the quantitative information can be correlated with the ancillary information using the first initial value and the second initial value to determine a final value that is predictive of a disease state of the subject.

A non-invasive detection method and device, and a wearable apparatus for tissue element are provided. The method includes: acquiring, for a detected site of a detected object, a second light intensity measurement value for each predetermined wavelength of at least one predetermined wavelength at a measurement distance, and/or a second light intensity reference value for each predetermined wavelength of at least one predetermined wavelength at a reference distance, wherein the measurement distance is a source-detection distance corresponding to the first light intensity measurement value, and the reference distance is a source-detection distance corresponding to the first light intensity reference value; and determining a concentration of a tissue element to be detected according to the second light intensity measurement value of each predetermined wavelength and/or the second light intensity reference value for each predetermined wavelength.

Computer implemented biometric methods and systems incorporate sensing biophysical phenomena, translating the phenomena into digital data and transmitting the data to a series of servers operating in an open feedback loop to generate a module. A biometric networking system can include a biometric monitoring cloud computing platform with AI/machine learning augmented models are generated to make user assessments, programs and confidence scores to the healthcare provider systems. The AI/machine learning models can be used by the biometric monitoring network to generate health-related AI processes that analyze relationships treatment techniques and outcomes. AI techniques can be used to calculate movement modeling and confidence scoring including support vector machines, neural networks, and decision trees. The biophysical phenomena may include biometric parameters based on data, such as medical history, exertion, sleep, temperature, cardiovascular events, respiratory events, and muscle and blood pH.

An Internet of Thing (IoT) sport device includes a body with a processor, a camera and a wireless transceiver coupled to the processor.

A patient health management platform accesses a metabolic profile for a patient and biosignals recorded for the patient during a current time period comprising sensor data and/or lab test data collected for the patient. The platform receives patient data recorded during the current time period comprising food items consumed, medications taken, and symptoms experienced by the patient. The platform implements a machine-learned metabolic model to determine a metabolic state of the patient at a conclusion of the current time period by comparing a true representation of the metabolic state and a prediction of the metabolic state. The true representation and the prediction are determined based on the recorded biosignals and the recorded patient data, respectively. The platform generates a patient-specific treatment recommendation outlining instructions for the patient to improve their metabolic state and provides the patient-specific treatment recommendation to the patient device for display to the patient.

The present application provides a method and device for determining inner and outer sides of limbs, and relates to the field of wearable devices. The method comprises: acquiring first somatosensory information of a first side of a limb of a user, the first side being an inner side or an outer side of the limb; and determining whether the first side is the inner side of the limb according to the first somatosensory information and reference information. The method and device facilitate a device that the user wears to perform automatic setting according to an identification result, thereby enhancing user experience.

The present invention relates to a device, system and method for less obtrusively determining a tissue characteristic of a subject, the device comprises a first control unit (11) configured to control an electromechanical transducer (31) by a first control signal (21) to transfer mechanical waves varying in a frequency range or with varying frequency content to an exposed tissue area of the subject; a second control unit (12) configured to control an electromagnetic radiation emitter (32) by a second control signal (22) to emit electromagnetic radiation towards the exposed tissue area of the subject; a radiation signal input (13) configured to obtain a radiation signal (23) indicative of electromagnetic radiation reflected from the exposed tissue area of the subject; and a processor (14) configured to determine a tissue characteristic signal (24) indicative of a tissue characteristic of the exposed tissue area of the subject derived from a frequency response or a frequency transfer function obtained from the obtained radiation signal in said frequency range or for said varying frequency content.

An apparatus, method and computer program is described comprising: varying a magnetic field strength of a magnetic field applied to a subject; determining a rate of power loss of the magnetic field, wherein the rate of power loss is a function of the varying magnetic field strength; and providing an output signal based on the determined rate of power loss, wherein the output signal comprises information relating to a conductivity distribution of the subject.

The present subject matter discloses a system(s) and a method(s) for determining a health state of an individual. According to an embodiment, a method comprises measuring, by a heart rate sensor, a heart rate of the individual during operation within the environment. The method further comprises outputting, by a pressure sensing platform, pressure data of the individual. Further, the method comprises outputting, by an image capturing device, image data of the individual. The method further comprises inferring, by a processing unit, an amount of fat of the individual in the image data. The method further comprises updating, by the processing unit, the amount of fat of the individual using the pressure data. The method further comprises controlling, by the processing unit, a threshold for determining the health state of the individual, using the amount of fat and the heart rate of the individual.