US2014214874A1PendingUtilityA1

Predicted type and contexts in assessments

Assignee: BODYMEDIA INCPriority: Feb 16, 2007Filed: Nov 17, 2013Published: Jul 31, 2014
Est. expiryFeb 16, 2027(~0.6 yrs left)· nominal 20-yr term from priority
A61B 5/1123A61B 5/72A61B 5/021G16B 99/00A61B 5/4818G06Q 30/0277A61M 21/02A61B 5/6802A61M 2021/0027G06Q 30/0271G06N 5/04A61M 21/00G16H 50/50G06Q 30/0251A61M 2021/005G06F 16/38G16H 10/60A61B 5/168G06F 16/90344G06F 16/248G16H 50/70A61B 5/1118G06Q 30/0242G16H 50/20A61B 5/746A61B 5/742A61B 5/4815G06N 20/00G06F 16/25G06Q 40/08G09B 19/00G06Q 30/0269A61B 5/6801G06F 16/285A61B 5/7475A61B 5/7278G09B 5/00A61B 5/4833A61B 5/7275A61B 5/747A61B 5/4812A61B 5/7282A61B 5/4806A61B 5/4836G06F 16/24575A61B 5/0826G16B 40/00G16B 50/00G16H 40/63G16H 50/30G06F 17/30289
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Claims

Abstract

The methods and systems described herein may involve determining at least one lifeotype of at least one individual, analyzing the at least one lifeotype, and delivering content to at least one individual based on the analysis. The methods and systems described herein may involve providing a game, determining at least one lifeotype of at least one player of the game, analyzing the at least one lifeotype, and affecting the game play based on the analysis. The methods and systems described herein may involve providing an interactive space, determining at least one lifeotype of at least one individual in the space, analyzing the at least one lifeotype, and modifying at least one attribute of the space based on the analysis.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A computer-system-implemented method, the computer system having at least one programmed processor to implement the method, the method comprising:
 continuously collecting data components with respect to an individual from a wearable sensor device; and   collecting another set of data components with respect to the individual from a source separate from the wearable device;   the computer system—
 (i) assembling a data structure for the individual that includes at least one component from the collected data components from the wearable sensor device and at least one of said another set of data components; 
 (ii) determining a type for the individual based on at least one of a match and a similarity between the data structure for the individual and data components for at least one other individual; 
 (iii) determining the context of the individual based on at least one of data from the wearable sensor device and data from a contextual sensor, wherein the context is an activity level; and 
 (iv) based on the determined activity level context and the individual type, providing an input to an assessment process. 
   
     
     
         2 . The method of  claim 1 , wherein the context is determined based on the output of a plurality of sensors of the wearable sensor device. 
     
     
         3 . The method of  claim 1 , wherein the data structure includes data components selected from the group consisting of: derived data, analytical status data, contextual data, continuous data, discrete data, time series data, event data, raw data, processed data, metadata, third party data, physiological state data, psychological state data, survey data, medical data, genetic data, environmental data, transactional data, economic data, socioeconomic data, demographic data, psychographic data, sensed data, continuously monitored data, manually entered data, inputted data, continuous data and real-time data. 
     
     
         4 . The method of  claim 1 , wherein said set of data components from a wearable sensor device is selected from the group consisting of: derived data, analytical status data, contextual data, continuous data, discrete data, time series data, event data, raw data, processed data, metadata, third party data, physiological state data, psychological state data, survey data, medical data, genetic data, environmental data, transactional data, economic data, socioeconomic data, demographic data, psychographic data, sensed data, continuously monitored data, manually entered data, inputted data, continuous data and real-time data. 
     
     
         5 . The method of  claim 1 , wherein at least one data component collected from a wearable sensor device is a data component that is derived from a plurality of sensors that is distinct from the output of any single sensor. 
     
     
         6 . The method of  claim 1 , wherein the activity level is a sedentary activity level. 
     
     
         7 . The method of  claim 1 , wherein the activity level is an exercise activity level. 
     
     
         8 . The method of  claim 1 , wherein the activity level is a meditation activity level. 
     
     
         9 . The method of  claim 1 , wherein the activity level is a body position activity level. 
     
     
         10 . The method of  claim 1 , wherein the activity level is a travel activity level. 
     
     
         11 . The method of  claim 1 , wherein the activity level is a shopping activity level. 
     
     
         12 . The method of  claim 1 , wherein the activity level is an entertainment activity level. 
     
     
         13 . The method of  claim 1 , wherein the activity level is a location-based activity level. 
     
     
         14 . The method of  claim 1 , wherein the activity level is a miles driven as a passenger activity level. 
     
     
         15 . The method of  claim 1 , wherein the activity level is a miles driven activity level. 
     
     
         16 . The method of  claim 1 , wherein the activity level is a driven to destination-based activity level. 
     
     
         17 . The method of  claim 1 , wherein the activity level is a travel destination based activity level. 
     
     
         18 . The method of  claim 1 , wherein the activity level is a work type activity level. 
     
     
         19 . The method of  claim 1 , wherein the activity level is a work duration activity level. 
     
     
         20 . The method of  claim 1 , wherein the activity level is a sleeping activity level. 
     
     
         21 . The method of  claim 1 , wherein the activity level is a resting activity level. 
     
     
         22 . The method of  claim 1 , wherein the activity level is a conflict activity level. 
     
     
         23 . The method of  claim 22 , wherein the conflict activity level is an arguing activity level. 
     
     
         24 . The method of  claim 1 , wherein the assessment is a psychological assessment. 
     
     
         25 . The method of  claim 1 , wherein the assessment is a physiological assessment. 
     
     
         26 . The method of  claim 1 , wherein the assessment is a medical assessment. 
     
     
         27 . The method of  claim 1 , wherein the assessment is a sleep assessment. 
     
     
         28 . The method of  claim 1 , wherein the assessment is a fitness assessment.

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