A seizure early-warning method and a system thereof, relating to a technical field of artificial intelligence. The method includes: acquiring health data of a user (S110); extracting first feature parameters from the acquired health data (S120); inputting the extracted first feature parameters into a preset seizure probability estimation model, so as to obtain a seizure probability (S130), wherein the seizure probability estimation model being generated by training a classification model by means of historical health data of a plurality of patients, and the historical health data of the patients including health data of the patients before the seizure; and determining, according to the seizure probability, whether to issue a seizure early-warning notification (S140). The system is a system configured to execute the method. The described technical solution can implement seizure early-warning.

The present disclosure relates generally to a system and method for detecting or indicating a state of impairment of a test subject or user due to drugs or alcohol, and more particularly to a method, system and application or software program configured to creating a virtual-reality (“VR”) environment that implements drug and alcohol impairment tests, and which utilizes eye tracking technology to detect or indicate impairment.

A contactless system for assessing and/or determining hemodynamic parameters and/or vital signs is featured. The system includes one or more contactless light sources configured to emit light incident on a moving living subject at one more wavelengths absorbed by one or more chromophores associated with spontaneous hemodynamic oscillations in a predetermined area of the living subject. The system includes a camera subsystem including one or more cameras configured to receive reflected light from the predetermined area of the moving living subject and configured to track motion of the predetermined area of the living subject within a field of view of the camera subsystem and configured to generate a time sequence of images of the predetermined area of the living subject. A controller is coupled the one or more light sources and the camera subsystem and is configured to acquire the time sequence of images and configured to generate one or more non-contact PPG waveforms and to assess and/or and determine one or hemodynamic parameters and/or vital signs from the one or more non-contact PPG waveforms. One or more polarizers are preferably each coupled to one of the one or more light sources are preferably configured to polarize the light to a polarized state such that the polarized light in the polarized state diffuses into the tissue in the predetermined area at a predetermined depth range and the polarized light is maintained in the polarized state at the predetermined depth range. A detector polarizer is preferably coupled to each of the one or more cameras and is configured to discriminate the light maintained in the polarized state and at the predetermined depth range and configured to generate the time sequence of images of the predetermined area with improved signal quality of the resulting non-contact PPG waveform.

Medical devices coupled to a sensor, and systems including such devices, can generate data and analysis based on that data, which may be used to identify and/or address problems associated with the implanted medical device, including incorrect placement of the device, unanticipated degradation of the device, and undesired movement of the device. Also provided are medical devices coupled to a sensor, and devices and methods to address problems that have been identified with an implanted medical device.

Systems and methods for systems and platforms that receive data from and send data to wearable devices, receive data from environmental sensors, and visualization which collectively creates a kinematic chain to allow for input from individuals, groups, third party information and interfaces with historical data as well as predictive modeling systems. Systems that include data from interoperable wearables in conjunction with one or more sensors and measuring devices may be used. Furthermore, the interoperability of one or more sensors and communication modules could be networked with one or more physical entities and objects creating an interactive communication network. Wearable platforms could include but are not limited to all wearables (inter- and intra- and proximity-wearables), smart devices, IT networks, virtual systems and secure information processes. In addition, the platforms and networks could also include real-time biological interoperability based on various synchronized and/or asynchronized data inputs, information and media.

Audio of a user speaking is gathered while spatial data of the face of the user is gathered. Positions of elements of the face of are identified, wherein relative positions of the elements cause a plurality of qualities of the user voice. A subset of positions of the elements are identified to have caused a detected first quality of the user voice during the period of time. Alternate positions of the one or more elements are identified that are determined to cause the user voice to have a second quality rather than the first quality. A graphical representation of the face that depicts one or more adjustments from the subset of the positions to the alternate positions is provided to the user.

A method, a structure, and a computer system for assessing user mobility. The exemplary embodiments may include collecting mobility data corresponding to a user and extracting one or more low level features from the mobility data. The exemplary embodiments may further include extracting one or more clinical level features from the low level features and assessing one or more health conditions of the user based on applying one or more models to the one or more clinical level features.

The invention provides a gait evaluating system and a gait evaluating method. The gait evaluation system includes a gait evaluating device configured to: obtain, from a pressure detection device, a plurality of pressure values of a user walking on the pressure detection device; obtain a plurality of step feature values of the user based on the pressure values; obtain a plurality of walking limb feature values when the user walks on the pressure detection device based on a sensing data provided by a limb sensing device; and evaluate a gait of the user based on the step feature values and the walking limb feature values.

Methods and apparatuses for recognizing a gait task, that may detect a gait pattern of a user based on sensed data, generate a gait feature of the gait pattern based on similarities between the gait pattern and similar gait data extracted from each of a plurality of databases, and estimate a gait task corresponding to the gait pattern by applying the gait feature to a desired learning model, may be provided.

Surgical robotic systems including a user console for controlling a robotic arm or a surgical robotic tool are described. The user console includes components designed to automatically adapt to anthropometric characteristics of a user. A processor of the surgical robotic system is configured to receive anthropometric inputs corresponding to the anthropometric characteristics and to generate an initial console configuration of the user console based on the inputs using a machine learning model. Actuators automatically adjust a seat, a display, or one or more pedals of the user console to the initial console configuration. The initial console configuration establishes a comfortable relative position between the user and the console components. Other embodiments are described and claimed.