Disclosed is a graph model-based brain functional alignment method. The method includes: mapping high-dimensional functional brain imaging data to a two-dimensional time-series matrix by taking brain functional activity signals of a subject under a specific cognitive function state as input , constructing a model based on graph convolutional networks to distinguish different cognitive function states, generating a brain activation distribution priori graph by a meta analysis method to assist in predicting a specific brain function activation mode of each subject, combining the two to map functional brain imaging data of each subject to a shared representation space applicable to a large-scale group, and finally achieving accurate brain function alignment between subjects. According to the method, graph representation information generated in the shared representation space can also be used for accurately predicting the brain function state and behavioral index of the subjects.

Various techniques are disclosed to provide for improved detection of elevated human body temperatures. In one example, a method includes receiving a thermal image. The method also includes processing the thermal image to detect a person's face and a characteristic associated with the person. The method also includes selecting a circadian rhythm model associated with the detected characteristic.

The method also includes determining an expected body temperature using the circadian rhythm model. The method also includes extracting a temperature associated with the person's face from the thermal image. The method also includes comparing the extracted temperature with the expected body temperature to detect an elevated body temperature condition. Additional methods and systems are also provided.

A method of controlling operation of a neurostimulation device comprises receiving, by the neurostimulation device, an indication of a physiological search area of a subject for delivering electrical neurostimulation and a prioritized search list of neurostimulation parameters for neurostimulation therapy delivered to the search area; delivering the neurostimulation therapy to the search area and varying the neurostimulation parameters according to the parameter priority, wherein a highest priority parameter is varied first while lower priority parameters are held constant; determining the optimum value of the highest priority parameter; delivering neurostimulation to the search area using the determined optimum value of the highest priority parameter and varying one or more lower priority parameters according to the parameter priority; and determining optimum lower priority parameters for the neurostimulation.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A method for measuring a high-accuracy and real-time heart rate based on a continuous-wave radar is provided. The method includes receiving an in-phase (I) signal and a quadrature (Q) signal for a receive signal received through the continuous-wave radar, selecting any one signal by comparing magnitudes of the received I signal and the received Q signal, performing frequency transform of each of bases respectively having predetermined phases with respect to the any one selected signal, and determining a heart rate based on a magnitude response of each of the bases by the frequency transform.

Disclosed is a method for the generation of a consciousness indicator for a non-communicating subject, including the steps of generating an auditory stimulation, receiving an electrocardiographic signal of the subject obtained from a recording during the generation of the auditory stimulation, extracting at least one feature from the electrocardiographic signal and deducing a consciousness indicator from an analysis of the electrocardiographic feature.

For training for and performance of patient modeling from surface data in a medical system, a progressive multi-task model is used. Different tasks for scanning are provided, such as landmark estimation and patient pose estimation. One or more features learned for one task are used as fixed or constant features in the other task. This progressive approach based on shared features increases efficiency while avoiding reductions in accuracy for any given task.

Described herein are systems and methods for the detection and monitoring of delirium in a subject. Other neurological conditions may also be detected and monitored. The systems may include a data module configured to obtain a plurality of electroencephalography (EEG) signals collected from a subject. The systems may also include a processing module in communication with the data module. The processing module may be configured to process the data to detect and monitor delirium and/or one or more other neurological conditions that the subject is experiencing or likely to experience. The processing module may also generate indications or assessments for delirium and/or for each neurological condition at an individual level, or optionally, between two or more related neurological conditions.

A personal impact monitoring system is described herein comprising a monitoring station that receives impact events sent from personal impact monitors using a monitoring station receiver. The impact events which specify impact parameters associated with the impact events are stored in a data storage location associated with the monitoring station. Software operating on the operating station is configured to receive the impact events from the data storage location and to perform calculations based on the impact events to identify notable impact events.

A computer-implemented method for direct photoplethysmography or direct PPG comprises obtaining during a time interval plural PPG signals for respective sensors in a wearable device; and combining the plural PPG signals to thereby obtain a multi-sensor PPG signal.