Abstract: A health and fitness management system that employs an algorithm to determine suggested recommended actions for a user to improve their health and fitness. The system obtains a user's health indicating measurement from a respective acquisition device. The user is never informed of the acquired data. The health indicating measurement can include a heart/pulse rate, blood pressure measurement, weight, etc. Base line data (age, ideal age, initial weight, current weight, ideal weight, etc.) can be considered in the algorithm. Examples include the user's environment, sleep habits, exercise routines, medical records, and the like. The health index number is used to determine recommended actions, which can include changes to environments, routines, activities, etc. Data collection, the algorithm, and other features of the system can be provided by an Application operating on a portable computing device. Features of the portable computing device can be employed to automatically acquire data for the algorithm.

Abstract: A health and fitness management system that employs an algorithm to determine suggested recommended actions for a user to improve their health and fitness. The system obtains a user's health indicating measurement from a respective acquisition device. The user is never informed of the acquired data. The health indicating measurement can include a heart/pulse rate, blood pressure measurement, weight, etc. Base line data (age, ideal age, initial weight, current weight, ideal weight, etc.) can be considered in the algorithm. Examples include the user's environment, sleep habits, exercise routines, medical records, and the like. The health index number is used to determine recommended actions, which can include changes to environments, routines, activities, etc. Data collection, the algorithm, and other features of the system can be provided by an Application operating on a portable computing device. Features of the portable computing device can be employed to automatically acquire data for the algorithm.

Abstract: A health and fitness management system utilizing an algorithm to suggest actions to improve a user's health and fitness. The system obtains a user's health indicating measurement from a respective acquisition device. The user is never informed of the acquired data. The health indicating measurement can include a heart/pulse rate, blood pressure measurement, weight, blood sugar level, etc. Base line data (age, ideal age, initial weight, current weight, ideal weight, etc.) can be considered in the algorithm. Examples include the user's environment, sleep habits, exercise routines, medical records, and the like. The health index number is used to determine recommended actions, which can include changes to environments, routines, activities, etc. Data collection, the algorithm, and other features of the system can be provided by an Application operating on a portable computing device. Features of the portable computing device can be employed to automatically acquire data for the algorithm.

Abstract: A health and fitness management system that employs an algorithm to determine suggested recommended actions for a user to improve their health and fitness. The system obtains a user's health indicating measurement from a respective acquisition device. The user is never informed of the acquired data. The health indicating measurement can include a heart/pulse rate, blood pressure measurement, weight, etc. Base line data (age, ideal age, initial weight, current weight, ideal weight, etc.) can be considered in the algorithm. Examples include the user's environment, sleep habits, exercise routines, medical records, and the like. The health index number is used to determine recommended actions, which can include changes to environments, routines, activities, etc. Data collection, the algorithm, and other features of the system can be provided by an Application operating on a portable computing device. Features of the portable computing device can be employed to automatically acquire data for the algorithm.

Abstract: A health and fitness management system that employs an algorithm to determine suggested recommended actions for a user to improve their health and fitness. The system obtains a user's weight from a scale. The user is never informed of their weight. Other data can be collected and included when calculating a health index number. Base line data, such as age, ideal age, initial weight, current weight, ideal weight, etc. can be considered in the algorithm. Examples include the user's environment, sleep habits, exercise routines, medical records, and the like. The health index number is used to determine recommended actions, which can include changes to environments, routines, activities, etc. Data collection, the algorithm, and other features of the system can be provided by an Application operating on a portable computing device. Features of the portable computing device can be employed to automatically acquire data for the algorithm.

Abstract: A health and fitness management system that employs an algorithm to determine suggested recommended actions for a user to improve their health and fitness. The system obtains a user's weight from a scale. The user is never informed of their weight. Other data can be collected and included when calculating a health index number. Base line data, such as age, ideal age, initial weight, current weight, ideal weight, etc. can be considered in the algorithm. Examples include the user's environment, sleep habits, exercise routines, medical records, and the like. The health index number is used to determine recommended actions, which can include changes to environments, routines, activities, etc. Data collection, the algorithm, and other features of the system can be provided by an Application operating on a portable computing device. Features of the portable computing device can be employed to automatically acquire data for the algorithm.

Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing scheduling suggestions to a user. A collection of intention objects is accessed. Each of the intention objects is a data structure comprising a plurality of activity attributes of an intention of a user to undertake an activity. Calendar data from a calendar of the user is accessed and an available time slot on the calendar is determined. In response to determining the available time slot, a suggested intention object is selected from the collection of intention objects based on a plurality of activity attributes of the suggested intention object. A scheduling suggestion is then presented to the user. The scheduling suggestion may include a suggestion to schedule an activity associated with the suggested intention object in the available time slot.

Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing a collection of intention objects to a user. A collection of intention objects is accessed. Each of the intention objects comprises a data structure including a plurality of activity attributes of an intention of the user to undertake an activity. A relevancy rank for each of the collection of intention objects is determined based on the plurality of activity attributes corresponding to each intention object. The relevancy rank may provide a suggested order in which the user undertake each respective activity. One or more intention objects of the collection of intention objects with a relevancy rank above a predefined threshold are identified. A graphical representation of each of the identified intention objects is then presented in a free form spatial user interface.

Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for generating an intention object. Activity data defining activity attributes of an intention of a user to undertake an activity is obtained. The activity attributes may comprise at least one temporal attribute defining a time constraint relating to the activity and at least one contextual attribute identifying a context relating to the activity. One or more content items related to the activity are obtained. An intention object is then generated based on the activity attributes, the intention object comprising a data structure including the activity attributes and the one or more content items. An additional activity attribute is inferred based on the activity attributes and the one or more content items. The intention object is then updated to include the additional activity attribute.

Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing scheduling suggestions to a user. A collection of intention objects is accessed. Each of the intention objects is a data structure comprising a plurality of activity attributes of an intention of a user to undertake an activity. Calendar data from a calendar of the user is accessed and an available time slot on the calendar is determined. In response to determining the available time slot, a suggested intention object is selected from the collection of intention objects based on a plurality of activity attributes of the suggested intention object. A scheduling suggestion is then presented to the user. The scheduling suggestion may include a suggestion to schedule an activity associated with the suggested intention object in the available time slot.

Abstract: Apparatus and methods for supporting a budgeting process are provided. A method according to the invention may include operating an electronic information processing platform to receive an electronic confirmation of one of a purchase, a savings transaction, and an investment transaction. The method may further include performing a reevaluation of a future savings goal in response to the confirmation. The method may also include performing one of the following in response to the reevaluation: 1) presenting an alternative to the future savings goal and 2) auto-executing a process. The auto-executing may be based on pre-determined rules.

Abstract: Apparatus and methods for providing a budget envelope credit card are provided. An apparatus according to the invention may include a budget envelope credit card software engine and a rewards software engine that provides a reward scheme for use by the budget envelope credit card engine, the rewards scheme that defines a reward frequency.

Abstract: Implementing an online savings network includes creating a network account for an owner and associating an investment account to the network account. The investment account is associated with savings parameters and is owned by the owner. A first contributor is invited to join the online savings network and a condition is established in response to an input by the first contributor that, when satisfied, triggers an automatic contribution of financial assets to the investment account by the first contributor, wherein the financial assets have a value that is relative to a value of a contribution by the owner.

Abstract: Methods and apparatus for executing sales transactions in which products or services are offered for sale either at an established normal price or at one or more reduced prices charged in the event a chance event occurs. The chance event may select particular purchasers who are to be charged the reduced prices, or may select particular products or services for which reduced prices are charged. Potential purchasers are advised prior to the time of sale that they have a chance to receive products or services they elect to purchase at reduced prices. Preferably, the purchaser is given the opportunity to receive products they elect to purchase at no charge if the chance event occurs.

Abstract: An artificial neuron includes inputs and dendrites, a respective one of which is associated with a respective one of the inputs. Each dendrite includes a power series of weights, and each weight in a power series includes an associated count for the associated power. The power series of weights preferably is a base-two power series of weights, each weight in the base-two power series including an associated count that represents a bit position. The counts for the associated power preferably are statistical counts. More particularly, the dendrites preferably are sequentially ordered, and the power series of weights preferably includes a pair of first and second power series of weights. Each weight in the first power series includes a first count that is a function of associations of prior dendrites, and each weight of the second power series includes a second count that is a function of associations of next dendrites.