System to determine stress of an individual

Abstract

Various methods and apparatuses for measuring a state parameter of an individual using signals based on one or more sensors are disclosed. In one embodiment, a first set of signals is used in a first function to determine how a second set of signals is used in one or more second functions to predict the state parameter. In another embodiment, first and second functions are used where the state parameter or an indicator of the state parameter may be obtained from a relationship between the first function and the second function. The state parameter may, for example, include calories consumed or calories burned by the individual. Various methods for making such apparatuses are also disclosed.

1 . (canceled) 
     
     
         2 . 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, the wearable device comprising a galvanic skin response sensor, a sensor to detect heart related parameters and a sensor to detection motion; and   the computer system—
 (i) using the data components for the individual from the wearable sensor device to derive that the individual is in a stress-related state; and 
 (ii) based on the determination of the stress-related state, providing a recommendation. 
   
     
     
         3 . The method of  claim 2 , wherein the stress-related state is determined at least in part based on the output of a plurality of sensors of the wearable sensor device. 
     
     
         4 . The method of  claim 2 , wherein the other data components include 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. 
     
     
         5 . The method of  claim 2 , 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 2 , wherein the recommendation is provided to the individual. 
     
     
         7 . The method of  claim 2 , wherein the recommendation is at least one of activity avoidance, situational avoidance, a meditation exercise, activity suggestion, situational suggestion, and medical treatment plan. 
     
     
         8 . The method of  claim 7 , wherein the medical treatment plan is taking a prescribed medication. 
     
     
         9 . The method of  claim 2 , wherein the anticipation that the individual will be under a stress-related state is further based on stored data indicating when a user has been stressed in the past. 
     
     
         10 . The method of  claim 2 , wherein the recommendation is provided to at least one other individual. 
     
     
         11 . The method of  claim 10 , wherein the recommendation is at least one of, activity avoidance, situational avoidance, suggested activity, suggested situation, conversation avoidance, suggested conversation, and medical treatment plan. 
     
     
         12 . The method of  claim 2 , wherein the stress-related state is at least one of a state of physical stress, a state of psychological stress, a state of fatigue, a state of sleep-related stress, a state of exposure to adverse environmental conditions, a stress-related state related to a relationship, a stress-related state related to a seasonal condition, and a stress-related state related to an individual's history.