Systems and methods for measuring a state parameter

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 method of making software for an apparatus for measuring a state parameter of an individual, comprising:
 providing a first sensor device, said first sensor device receiving a plurality of signals from at least two sensors;   using said first sensor device to create a first function and one or more second functions, each of said one or more second functions having an output, said first function utilizing a first set of signals based on one or more of said plurality of sensor signals to determine how a second set of signals based on one or more of said plurality of sensor signals is utilized in said one or more second functions, wherein one or more of said outputs are used to predict said state parameter of said individual; and   creating said software including instructions for:
 (i) receiving a second plurality of signals collected by a second sensor device substantially structurally identical to said first sensor device for a period of time; 
 (ii) utilizing a third set of signals based on one or more of said second plurality of sensor signals in said first function to determine how a fourth set of signals based on one or more of said second plurality of sensor signals is utilized in said one or more second functions; and 
 (iii) utilizing said one or more outputs produced by said one or more second functions from said fourth set of signals to predict said state parameter of said individual. 
   
     
     
         3 . A method according to  claim 2 , said apparatus comprising said second sensor device, said method further comprising storing said software in said second sensor device, said second sensor device having a processor for executing said software. 
     
     
         4 . A method according to  claim 2 , said apparatus comprising said second sensor device and a computing device in electronic communication with said second sensor device for receiving said second plurality of signals from said second sensor device, said method further comprising storing said software in a computer readable medium for subsequent transfer to said computing device, said computing device having a processor for executing said software. 
     
     
         5 . A method according to  claim 2 , wherein said step of using said sensor device to create said first function and said one or more second functions includes gathering a first set of said plurality of signals under conditions where said state parameter is present, contemporaneously gathering gold standard data relating to said state parameter, and using one or more machine learning techniques to generate said first function and said one or more second functions from said first set of said plurality of signals and said gold standard data. 
     
     
         6 . A method according to  claim 2 , said at least two sensors being included in said first sensor device. 
     
     
         7 . A method according to  claim 2 , at least one of said at least two sensors being located separately from said first sensor device. 
     
     
         8 . A method according to  claim 2 , wherein said first function recognizes one or more contexts based on said first set of signals, wherein one or more of said second functions is chosen based on said one or more recognized contexts, and wherein said outputs of said chosen second functions are used to predict said state parameter of said individual. 
     
     
         9 . A method according to  claim 2 , wherein said first function recognizes each of a plurality of contexts based on said first set of signals, wherein each of said one or more second functions corresponds to one of said contexts, wherein said first function assigns a weight to each of said one or more second functions based on a recognition probability associated with the corresponding context, and wherein said outputs of said one or more second functions and said weights are used to predict said state parameter of said individual. 
     
     
         10 . A method according to  claim 2 , said utilizing instruction comprising combining said outputs produced by said one or more second functions from said fourth set of signals in a post processing step to predict said state parameter. 
     
     
         11 . A method according to  claim 2 , wherein said second functions are regression algorithms. 
     
     
         12 . A method according to  claim 11 , wherein said state parameter is caloric expenditure of said individual. 
     
     
         13 . A method according to  claim 12 , wherein said contexts comprise rest and active. 
     
     
         14 . A method according to  claim 13 , said first function comprising a naïve Bayesian classifier. 
     
     
         15 . A method according to  claim 13 , said at least two sensors comprising a body motion sensor, a heat flux sensor and a skin conductance sensor. 
     
     
         16 . A method according to  claim 14 , said body motion sensor being an accelerometer and said skin conductance sensor being a GSR sensor. 
     
     
         17 . A method of making software for an apparatus for automatically measuring a first state parameter of an individual, comprising:
 providing a first sensor device, said first sensor device receiving one or more signals from one or more sensors;   using said first sensor device to create a first function having a first output that predicts one or more second state parameters of said individual and either said first state parameter or an indicator of said first state parameter, wherein said first state parameter may be obtained from said indicator based on a first relationship between said first state parameter and said indicator, said first function taking as inputs one or more signal channels based on said one or more signals;   using said first sensor device to create a second function having a second output that predicts said one or more second state parameters but not said first state parameter or said indicator of said first state parameter, said second function taking as inputs said one or more signal channels; and   creating said software including instructions for:
 (i) receiving a second one or more signals collected by a second sensor device substantially structurally identical to said first sensor device for a period of time; 
 (ii) inputting a second one or more signal channels based on said second one or more signals into said first function and said second function for generating said first output and said second output, respectively; and 
 (iii) obtaining either said first state parameter or said indicator from said first and second outputs generated in said inputting step based on a second relationship between said first function and said second function, and, if said indicator is obtained, obtaining said first state parameter from said indicator based on said first relationship. 
   
     
     
         18 . A method according to  claim 17 , said apparatus comprising said second sensor device, said method further comprising storing said software in said second sensor device, said second sensor device having a processor for executing said software. 
     
     
         19 . A method according to  claim 17 , said apparatus comprising said second sensor device and a computing device in electronic communication with said second sensor device for receiving said second one or more signals from said second sensor device, said method further comprising storing said software in a computer readable medium for subsequent transfer to said computing device, said computing device having a processor for executing said software. 
     
     
         20 . A method according to  claim 17 , wherein said step of using said sensor device to create said first function includes gathering a first set of said one or more signals under conditions where said second state parameters and either said first state parameter or said indicator are present, contemporaneously gathering gold standard data relating to said second state parameters and either said first state parameter or said indicator, and using one or more machine learning techniques to generate said first function from said first set of one or more signals and said gold standard data, and wherein said step of using said sensor device to create said second function includes gathering a second set of said one or more signals under conditions where neither said first state parameter nor said indicator are present, contemporaneously gathering second gold standard data relating to said second state parameters but not said first state parameter or said indicator, and using one or more machine learning techniques to generate said second function from said second set of one or more signals and said second gold standard data. 
     
     
         21 . A method according to  claim 17 , said one or more sensors being included in said first sensor device. 
     
     
         22 . A method according to  claim 17 , at least one of said one or more sensors being located separately from said first sensor device. 
     
     
         23 . A method according to  claim 17 , said one or more sensors comprising at least two sensors and said one or more signals comprising of at least two signals. 
     
     
         24 . A method according to  claim 17 , said second relationship comprising a subtractive relationship. 
     
     
         25 . A method according to  claim 17 , said first state parameter being obtained from said indicator by dividing said indictor by a first factor. 
     
     
         26 . A method according to  claim 17 , said first state parameter comprising a number of calories consumed by said individual during said period of time. 
     
     
         27 . A method according to  claim 26 , said indicator comprising a first effect on the body of food consumed. 
     
     
         28 . A method according to  claim 27 , said indicator being thermic effect of food. 
     
     
         29 . A method according to  claim 28 , said first output comprising total energy expenditure, wherein said one or more second state parameters include basal metabolic rate, activity energy expenditure and adaptive thermogenesis. 
     
     
         30 . A method according to  claim 29 , said first state parameter being obtained from said indicator by dividing said indicator by a first amount. 
     
     
         31 . A method according to  claim 30 , said first amount being 0.1. 
     
     
         32 . A method according to  claim 26 , said software further including instructions for generating caloric expenditure data for said individual for said period of time from one or more of said second one or more signal channels and displaying information based on said caloric expenditure data and said number of calories consumed by said individual. 
     
     
         33 . A method according to  claim 26 , wherein said displayed information includes energy balance data. 
     
     
         34 . A method according to  claim 26 , wherein said displayed information includes a rate of weight loss or gain of said individual. 
     
     
         35 . A method according to  claim 26 , wherein said displayed information includes information relating to one or more goals of said individual, said goals relating to one or more of caloric consumption, caloric expenditure, energy balance and rate of weight loss or gain. 
     
     
         36 . A method according to  claim 35 , said at least two sensors including a body motion sensor, a heat flux sensor and a skin conductance sensor. 
     
     
         37 . A method according to  claim 36 , said one or more sensors selected from the group consisting of physiological sensors and contextual sensors.