A method for providing a personalized solution for improving an intestinal environment based on a postbiotic-based health index includes receiving registration of a kit for collecting a sample from a user device; calculating a postbiotic-based health index of at least one culture in which the sample is treated with at least one intestinal environment-improving candidate material; and recommending at least one product for improving an intestinal environment, including the at least one intestinal environment-improving candidate material based on the postbiotic-based health index of the at least one culture.

Systems and methods for remotely monitoring hospital patients are provided. Medical devices may capture biometric data associated with a patient positioned in an ICU environment, and a remote display device positioned external to the ICU environment may display an indication of the health of the patient based on the captured biometric data. The indication of the health of the patient may include a graph mapping normalized health statuses associated with the patient over time. Each normalized health status may be based on normalizing a particular type of biometric data based on a medical protocol, so each data point of the graph includes an indication of a normalized health status associated with the patient at a given time. The indication of the health of the patient may include an animated three-dimensional that is dynamically updated to reflect biometric data associated with the patient captured at a time selected by a user.

An eye test administered to a remote subject over a computer network, where sensors provide feedback through the computer network so that light source position, light source brightness and/or a display configuration and/or parameter setting related to a visual display that is used to implement the remote eye test.

Systems and methods for electronically creating and modifying a fitness plan are disclosed. The method may include receiving electronic user data, collecting electronic fitness data, and displaying a suggestion for a fitness activity based on the electronic user data and the electronic fitness data.

A method can include obtaining personal data of a user and generating, based at least in part on the personal data of the user, a taste profile of the user. The taste profile can include a set of food characteristics that corresponds to one or more food preferences of the user. The method can include obtaining contextual data that corresponds to a location of the user. The method can include generating, based at least in part on the taste profile and the contextual data, a food recommendation. The food recommendation can include a predicted food preference of the user. The method can include transmitting the food recommendation to the user.

A method can include obtaining personal data of a user and generating, based at least in part on the personal data of the user, a taste profile of the user. The taste profile can include a set of food characteristics that corresponds to one or more food preferences of the user. The method can include obtaining contextual data that corresponds to a location of the user. The method can include generating, based at least in part on the taste profile and the contextual data, a food recommendation. The food recommendation can include a predicted food preference of the user. The method can include transmitting the food recommendation to the user.

The present disclosure relates to a computer-implemented process for generating and providing simulated user absorption information pertaining to users and based on target profiles and target situations, thereby providing user targeted and situationally targeted content recommendations. It is an object of the present disclosure to provide a technological solution to the long felt need in small scale content recommendation systems caused by the technical problem of generating situationally targeted and user profile targeted content recommendations for users of an interactive electronic system.

The present disclosure relates to a computer-implemented process for generating and providing simulated user absorption information pertaining to users and based on target profiles and target situations, thereby providing user targeted and situationally targeted content recommendations. It is an object of the present disclosure to provide a technological solution to the long felt need in small scale content recommendation systems caused by the technical problem of generating situationally targeted and user profile targeted content recommendations for users of an interactive electronic system.

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 automated tracking and analysis system is described. In some instances, the system may collect data describing an attribute of a participant, predict interventions related to the attribute of the participant, and generate personalized tracks relating to the interventions, each of which may include an action. In some instances, the system may assess a performance metric indicating a level of performance of the participant in the personalized tracks, compute a participant score for the personalized tracks using the performance metric; and issue a reward to the participant based on one or more of the participant score and the performance metric.