Abstract: A passive tracking device, a processor configured to receive information from the tracking device, and a database accessible by the processor, among other elements, are disclosed. A first activity unit having a first start time corresponding to detection of engagement is monitored. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit. The classification of the first activity unit is output to a display of a computing device, and the classification of the first activity unit is stored in the database. A revised classification is output to a display of a computing device, the revised classification is stored in the database.

Abstract: A unique health score computation method is disclosed which masks underlying health statistics, yet provides a benchmark for a variety of applications. A system and method for collecting health related information, processing the information into a composite numerical value, and publishing the value is provided. The system includes a computer having a processor, memory, and code modules executing in the processor for implementation of the method. Information concerning a plurality of intrinsic and extrinsic parameters of a user is collected. Weighting factors are applied to the parameter in order control the relative affect each parameter has on the user's calculated numerical. The health score is computed using the processor by combining the weighted parameters in accordance with an algorithm. The numerical value is published to a designated group via a portal, while the underlying parameters remain private. In one implementation, the portal is an internet based information sharing forum.

Abstract: A unique health score computation method is disclosed which masks underlying health statistics, yet provides a benchmark for a variety of applications. A system and method for collecting health related information, processing the information into a composite numerical value, and publishing the value is provided. The system includes a computer having a processor, memory, and code modules executing in the processor for implementation of the method. Information concerning a plurality of intrinsic and extrinsic parameters of a user is collected. Weighting factors are applied to the parameter in order control the relative affect each parameter has on the user's calculated numerical. The health score is computed using the processor by combining the weighted parameters in accordance with an algorithm. The numerical value is published to a designated group via a portal, while the underlying parameters remain private. In one implementation, the portal is an internet based information sharing forum.

Abstract: Modulated output from each of a plurality of models is integrated to quantify factors and generate a plurality of values, each within a continuous distribution. A respective discrete category is associated with some of the values to represent a likelihood of future occurrence. Values are received from a first, second, and third data model. The values are modulated to scale a value representing aspect(s) associated with the likelihood of the future occurrence. The modulating is based on at least one factor derived from at least one of the first data model, the second data model, and the third data model. Thereafter, the values are integrated as a function artificial intelligence comprised in the at least one computing device, and a respective discrete category associated with the integrated values is selected, wherein each of the integrated values and the selected category represent the likelihood of a future occurrence.

Abstract: A passive tracking device, a processor configured to receive information from the tracking device, and a database accessible by the processor, among other elements, are disclosed. A first activity unit having a first start time corresponding to detection of engagement is monitored. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit. The classification of the first activity unit is output to a display of a computing device, and the classification of the first activity unit is stored in the database. A revised classification is output to a display of a computing device, the revised classification is stored in the database.

Abstract: A passive tracking device, a processor configured to receive information from the tracking device, and a database accessible by the processor, among other elements, are disclosed. A first activity unit having a first start time corresponding to detection of engagement is monitored. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit. The classification of the first activity unit is output to a display of a computing device, and the classification of the first activity unit is stored in the database. A revised classification is output to a display of a computing device, the revised classification is stored in the database.

Abstract: Dynamic tracking of user-based activity is provided as a function of information received from a plurality of data sources. Tracking of user activity information via a first application occurs correlated to steps taken by a user over a period of time. A health score associated with the user is presented in a GUI. Further, communication with a second application occurs during gameplay. Moreover, the at least one computing device is configured to combine, using the first application, the tracked user activity information with at least a portion of the user interaction information into an activity value. The computing device updates the health score using the activity value. Still further, the computing device is configured to store the updated health score in association with a record concerning the user, and to cause a notification on the mobile computing device of the updated health score when the first application is not executing.

Abstract: In one or more implementations, the present application includes a system and method to classify user activity. A passive tracking device, a processor configured to receive information from the tracking device, and a database are disclosed, in which the database is accessible by the processor and stores tracking device information, user profile information and external information. The processor is configured to execute instructions that cause the processor to perform various steps, such as to define a first activity unit having a first start time that corresponds to detection of the user being engaged in an activity, and monitor the tracking device information, the external information or both. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit.

Abstract: A passive tracking device, a processor configured to receive information from the tracking device, and a database accessible by the processor, among other elements, are disclosed. A first activity unit having a first start time corresponding to detection of engagement is monitored. The processor is further configured to establish a first end time of the first activity unit using the monitored information, and automatically ascribe a classification of the first activity unit. The classification of the first activity unit is output to a display of a computing device, and the classification of the first activity unit is stored in the database. A revised classification is output to a display of a computing device, the revised classification is stored in the database.

Abstract: There is shown and described a computer implemented system and method for analyzing an individual's personal stress level and providing a stress-score representing the individual's personal stress level. A plurality of parameters are received into a memory from at least one computing device and each of the parameters respectively represents a factor of the individual's life that contributes to a level of stress for the individual. The received parameter data is processed by executing code in a processor that configures the processor to normalize the parameter data by assigning, for each of the received parameters, a respective parameter score that represents a relative value of the parameter. The individual's stress-score is calculated as a function of the normalized parameter data, the stress-score is automatically transmitted to the at least one computing device, using code executing in the processor and free of human intervention.

Abstract: A unique health score computation method is disclosed which masks underlying health statistics, yet provides a benchmark for a variety of applications. A system and method for collecting health related information, processing the information into a composite numerical value, and publishing the value is provided. The system includes a computer having a processor, memory, and code modules executing in the processor for implementation of the method. Information concerning a plurality of intrinsic and extrinsic parameters of a user is collected. Weighting factors are applied to the parameter in order control the relative affect each parameter has on the user's calculated numerical. The health score is computed using the processor by combining the weighted parameters in accordance with an algorithm. The numerical value is published to a designated group via a portal, while the underlying parameters remain private. In one implementation, the portal is an internet based information sharing forum.

Abstract: A unique health score computation method is disclosed which masks underlying health statistics, yet provides a benchmark for a variety of applications. A system and method for collecting health related information, processing the information into a composite numerical value, and publishing the value is provided. The system includes a computer having a processor, memory, and code modules executing in the processor for implementation of the method. Information concerning a plurality of intrinsic and extrinsic parameters of a user is collected. Weighting factors are applied to the parameter in order control the relative affect each parameter has on the user's calculated numerical. The health score is computed using the processor by combining the weighted parameters in accordance with an algorithm. The numerical value is published to a designated group via a portal, while the underlying parameters remain private. In one implementation, the portal is an internet based information sharing forum.

Abstract: A unique health score computation method is disclosed which masks underlying health statistics, yet provides a benchmark for a variety of applications. A system and method for collecting health related information, processing the information into a composite numerical value, and publishing the value is provided. The system includes a computer having a processor, memory, and code modules executing in the processor for implementation of the method. Information concerning a plurality of intrinsic and extrinsic parameters of a user is collected. Weighting factors are applied to the parameter in order control the relative affect each parameter has on the user's calculated numerical. The health score is computed using the processor by combining the weighted parameters in accordance with an algorithm. The numerical value is published to a designated group via a portal, while the underlying parameters remain private. In one implementation, the portal is an internet based information sharing forum.

Abstract: There is shown and described a computer implemented system and method for analyzing an individual's personal stress level and providing a stress-score representing the individual's personal stress level. A plurality of parameters are received into a memory from at least one computing device and each of the parameters respectively represents a factor of the individual's life that contributes to a level of stress for the individual. The received parameter data is processed by executing code in a processor that configures the processor to normalize the parameter data by assigning, for each of the received parameters, a respective parameter score that represents a relative value of the parameter. The individual's stress-score is calculated as a function of the normalized parameter data, the stress-score is automatically transmitted to the at least one computing device, using code executing in the processor and free of human intervention.

Abstract: A method and apparatus are provided for measuring selected patient heartbeat parameters such as heartrates and amplitude variations, for processing the measured parameters to place them in more usable form and for analyzing measured and processed heartbeat parameters to obtain certain useful information concerning the condition of the patient's cardiac function. Measurement preferably involves detection and storage of at least two of the P, R and T pulses for each heartbeat and the conversion of such information into time series for selective heartrates. Indicators .delta..sub.j are computed for selected ones of the time series for selected values of j and the computed .delta..sub.j 's are then compared against stored .delta..sub.j values to obtain a measure of the state of cardiac function. The time series are preferably notched, detrended and normalized prior to being analyzed.