A device for measuring a plurality of parameters of a patient subject to a treatment with radiopharmaceuticals includes a main body constrained to the patient's body in such a way that the measurement device is of wearable type. The device includes a plurality of measurement modules, for example a first module and a second module, each of which is equipped with a respective sensor, configured to measure a predetermined parameter of the patient. The device is also equipped with a microprocessor configured to process a plurality of data measured by the plurality of sensors, obtaining a plurality of processed data. Furthermore, a transmission means is provided of wireless type arranged to send via wireless communication the data processed by the microprocessor to a remote control unit.

An electronic device for providing health information or assistance includes an input configured to receive at least one type of signal selected from sound signals, verbal signals, non-verbal signals, and combinations thereof, a communication module configured to send information related to the at least one user and his/her environment to a remote device, including the sound signals, non-verbal signals, and verbal signals, the remote device being configured to analyze a condition of the at least one user and communicate condition signals to the electronic device, a processing module configured to receive the condition signals and to cause the electronic device to engage in a passive monitoring mode or an active engagement and monitoring mode, the active engagement and monitoring mode including, but not limited to, verbal communication with the at least one user, and an output configured to engage the at least one user in verbal communication.

Highblood levels of very low density lipoprotein lipids (VLDLs) and glycoprotein acyl (Glyc A) are known to increase risk of diabetes, cardiovascular diseases, inflammations, cognitive impairments, cancers and premature deaths in sedentary persons. The invention determines physical activity thresholds of daily steps and accelerations to reduce plasma concentrations of VLDLs and Glyc A. The method and device is an accelerometer recording and classifying numbers of steps and accelerations and comparing the person's steps and accelerations with those shown to reduce VLDLs and Gly A. The invention is characterized in that if the daily number of accleration maxima exceeds the given en threshold of 2980 steps in the acceleration range 1.3-1.7 g, the person has performed physical activity, typically known to reduce circulating VLDLs and Glyc A.

A health diagnostics system includes an interne-of-things (IoT) toilet device adapted to be mounted on or within a toilet bowl. The IoT toilet device comprises one or more sensors for collecting measurements of human excrement residing within the toilet bowl and also includes an excrement analysis module stored in memory and executable by a processor to infer a property of a human bowel movement based on the collected measurements, where the inferred property includes at least one of color, volume, mass, consistency, and frequency

Disclosed are a non-contact fatigue detection method and system. The method comprises: sending a millimeter-wave (mmWave) radar signal to a person being detected, receiving an echo signal reflected from the person, and determining a time-frequency domain feature, a non-linear feature and a time-series feature of a vital sign signal; acquiring a facial video image of the person, and performing facial detection and alignment on the basis of the facial video image, for extracting a time domain feature and a spatial domain feature of the person's face; fusing the determined vital sign signal with the time domain feature and the spatial domain feature of the person's face, for obtaining a fused feature; and determining whether the person is in a fatigued state by the fused feature. By fusing the two detection techniques, the method effectively suppressing the interference of subjective and objective factors, and improving the accuracy of fatigue detection.

Systems and methods of measuring feet and designing and creating orthopedic inserts are described. A leg length discrepancy of a user is measured and this data, along with foot size are input into a computer. The computer then creates a computer model of a custom shoe insert based on this information. The computer model is then sent to a 3D printer to print the insert. The insert consists of a base insert with partial correction, and several additional layers that are added successively over time until a full correction is obtained. This eliminates any pain associated with a fully corrective insert, and allows the body to adjust gradually to the correction.

In some examples, an apparatus configured to be worn by a patient for cardiac defibrillation comprises sensing electrodes configured to sense a cardiac signal of the patient, defibrillation electrodes, therapy delivery circuitry configured to deliver defibrillation therapy to the patient via the defibrillation electrodes, communication circuitry configured to receive data of at least one physiological signal of the patient from at least one sensing device separate from the apparatus, a memory configured to store the data, the cardiac signal, and a machine learning algorithm, and processing circuitry configured to apply the machine learning algorithm to the data and the cardiac signal to probabilistically-determine at least one state of the patient and determine whether to control delivery of the defibrillation therapy based on the at least one probabilistically-determined patient state.

A worker management apparatus includes: a work performance information generation unit generating work performance information representing a performance state of work by a worker; an acquisition unit acquiring physical information representing a physical condition relating to the worker; an estimation unit estimating an influence of the physical condition upon the performance state, based on the work performance information, the physical information, and information representing a characteristic of the worker; and an improvement measure generation unit generating improvement measure information representing a measure to improve the performance state relating to the worker, according to an estimation result by the estimation unit, thereby presenting a suitable measure to improve the work performance of the worker by managing with high precision the work performance state and physical condition relating to the worker.

Some embodiments relate to methods of treating hyperbilirubinemia comprising administrating a therapeutic amount of a metalloporphyrin to an infant. Administration may occur when the infant's measured total serum bilirubin levels are at or below about the level suggested by the AAP nomogram for initiating phototherapy, when the infant's measured total serum bilirubin levels are at about the level suggested for initiating phototherapy in an infant, or when the infant's measured total serum bilirubin levels are at about the level suggested for initiating phototherapy. Administration may occur without regard to the total serum bilirubin level of the infant. In some embodiments, administration of the metalloporphyrin does not cause QT prolongation.

A system for reversing inflammation in a user, wherein the system further comprises a computing device further designed and configured to receive a physiological extraction of a user, wherein the physiological extraction contains at least an inflammation marker, generate, using an inflammation machine-learning model and the user physiological extraction input, a first inflammation metric of a user, wherein generating the first inflammation metric further comprises training an inflammation machine-learning model as a function of inflammation metric training data, wherein the inflammation metric training data includes a plurality of entries, and each entry correlates user physiological extraction data to at least an inflammation metric that quantitates hallmarks of inflammation in the user, identify, using an alimentary element machine-learning process and the first inflammation metric, at least an alimentary element for reversing inflammation in the user, and provide, to the user, the at least an alimentary element for reversing inflammation.