User Friendly Vaginal Sensor System

Abstract

Embodiments of a vaginal temperature sensing apparatus, a visually sense-able battery power-on indicator ( 16 ), manufacturing with cure temperatures that protect a battery, substantially error-free, user-initiated device activation componentry ( 30 ) to start battery power, and a timer to automatically terminate flow of battery power. Data can by an automatic data transform recalculator ( 138 ) with body temperature dips in transformed and recalculated diurnal high body temperatures predict an ovulation event and provide an indication through a zenith based ovulation indicator ( 106 ). Systems can include neural network based artificial intelligence to automatically self-improve by using historical or even other, multi user data and user input and improve its indication result.

What is claimed is: 
     
         1 - 44 . (canceled) 
     
     
         45 . A process for analyzing transformed body temperature indications of a user to notify of an ovulation event comprising the steps of:
 periodically sensing actual internal body temperature values throughout at least a high temperature timeframe for said user;   storing a bracket of said actual internal body temperature values that include at least said high temperature timeframe for said user;   automatically computer transforming said bracket of actual internal body temperature values to recalculate a daily zenith value;   automatically generating a transformed estimated effective daily zenith created value;   storing said transformed estimated effective daily zenith created value;   automatically computer analyzing a succession of adjacent transformed estimated effective daily zenith created values to determine a dip in said transformed estimated effective daily zenith created values;   automatically computer generating a transformed ovulation prediction output based on said step of automatically computer analyzing a succession of adjacent transformed estimated   effective daily zenith created values to determine a dip in said transformed estimated effective daily zenith created values; and   providing an ovulation indication as a result of step of automatically computer generating a transformed ovulation prediction output.   
     
     
         46 . A process for analyzing transformed body temperature indications of a user to notify of an ovulation event as described in  claim 45  wherein said step of automatically computer transforming said bracket of actual internal body temperature values to recalculate a daily zenith value for said user active period comprises the step of automatically computer smoothing a bracket of internal body temperature values for said user active period. 
     
     
         47 . A process for analyzing transformed body temperature indications of a user to notify of an ovulation event as described in  claim 46  wherein said step of automatically computer smoothing a bracket of internal body temperature values comprises the steps of: automatically computer generating a frequency spectrum for said internal body temperature values; and automatically computer eliminating higher frequency compositions from said frequency spectrum for said internal body temperature values. 
     
     
         48 . A process for analyzing transformed body temperature indications of a user to notify of an ovulation event as described in  claim 47  wherein said step of automatically computer eliminating higher frequency compositions from said frequency spectrum for said internal body temperature values comprises automatically computer eliminating frequency compositions from said frequency spectrum for said internal body temperature values that have a frequency greater than those chosen from: one-half cycle/every thirty minutes frequency, one-half cycle/every hour frequency, one-half cycle/every two hours frequency, and one-half cycle/every three hours frequency. 
     
     
         49 . A process for analyzing transformed body temperature indications of a user to notify of an ovulation event as described in  claim 45  wherein said step of automatically computer analyzing a succession of adjacent transformed estimated effective daily zenith created values for said user active periods to determine a dip in said transformed estimated effective daily zenith created values for said user active periods further comprises the step of factoring in a likely time window since a last ovulation event for said user. 
     
     
         50 . A process for improved reliability notification of an ovulation event for a user comprising the steps of:
 obtaining periodic internal body indications for said user perhaps such as discrete user data, user determined activity or occurrence data, clinical data, test data, LH test data, or the like;   automatically accepting a data input to a computer based at least in part on said step of obtaining periodic internal body indications;   establishing in a computer at least one first ovulation prediction model automated ovulation computational transformation program with starting ovulation transformation parameters;   automatically applying said first ovulation prediction model automated ovulation computational transformation program with said starting ovulation transformation parameters, to at least some of said internal body indications to automatically create a first ovulation prediction model data transform;   generating a first ovulation prediction model completed ovulation prediction output based on a data transform of said first ovulation prediction model;   automatically varying said starting ovulation transformation parameters for said first ovulation prediction model automated ovulation computational transformation program to establish a second ovulation prediction model automated ovulation computational transformation program that differs from said first ovulation prediction model automated ovulation computational transformation program in the way that it predicts ovulation from data;   automatically applying said second ovulation prediction model automated ovulation computational transformation program with said automatically varied ovulation transformation parameters, to at least some of said internal body indications to automatically create a second ovulation prediction model data transform;   generating a different, second ovulation prediction model transformed completed ovulation prediction output based on a data transform of said second ovulation prediction model;   automatically comparing said first ovulation prediction model completed ovulation prediction output with said different, second ovulation prediction model transformed completed ovulation prediction output;   automatically determining whether said first ovulation prediction model completed ovulation prediction output or said different, second ovulation prediction model transformed completed ovulation prediction output is likely to provide a desired selection criterion indication of the likely existence of an ovulation event;   providing an ovulation indication based on said step of automatically determining whether said first ovulation prediction model completed ovulation prediction output or said different, second ovulation prediction model transformed completed ovulation prediction output is likely to provide said desired selection criterion indication of the likely existence of an ovulation event; and   storing automatically improved ovulation transformation parameters that are determined to provide said desired selection criterion indication of the likely existence of an ovulation event for future use to automatically self improve said ovulation prediction models.   
     
     
         51 . A process for improved reliability notification of an ovulation event for a user as described in  claim 50  wherein said step of obtaining periodic internal body indications comprises the step of periodically sensing internal body temperature values for said user. 
     
     
         52 . A process for improved reliability notification of an ovulation event for a user as described in  claim 50  wherein said step of automatically varying said starting ovulation transformation parameters for said first ovulation prediction model automated ovulation computational transformation program to establish a second ovulation prediction model automated ovulation computational transformation program that differs from said first ovulation prediction model automated ovulation computational transformation program in the way that it predicts ovulation from data comprises the step of automatically cumulatively varying previously applied ovulation transformation parameters for said automated ovulation computational transformation program to establish a varied automated ovulation computational transformation program. 
     
     
         53 . A process for improved reliability notification of an ovulation event for a user as described in  claim 50  and further comprising the step of providing a user-preference input to which said step of automatically determining whether said transformed ovulation prediction output or said varied transform ovulation prediction output is likely to provide said desired selection criterion indication of the likely existence of an ovulation event is responsive. 
     
     
         54 . A process for improved reliability notification of an ovulation event for a user as described in  claim 50  wherein said step of automatically applying said first ovulation prediction model automated ovulation computational transformation program with said starting ovulation transformation parameters, to at least some of said internal body temperature values to automatically create a first ovulation prediction model data transform comprises the step of automatically creating a transformed estimated effective daily zenith created value. 
     
     
         55 . A process for improved reliability notification of an ovulation event for a user as described in  claim 50  wherein said step of automatically determining whether said first ovulation prediction model completed ovulation prediction output or said different, second ovulation prediction model transformed completed ovulation prediction output is likely to provide said desired selection criterion indication of the likely existence of an ovulation event comprises the step of automatically applying said first ovulation prediction model completed ovulation prediction output and said different, second ovulation prediction model transformed completed ovulation prediction output to a plurality of ovulation events. 
     
     
         56 . A process for improved notification of an ovulation event for a user comprising the steps of:
 obtaining periodic internal body indications for said user perhaps such as discrete user data, user determined activity or occurrence data, clinical data, test data, LH test data, or the like;   automatically transforming said internal body indications to a first transformation computation generated completed ovulation prediction output by a first ovulation prediction model;   automatically transforming said internal body indications to a second transformation computation generated completed ovulation prediction output by a second ovulation prediction model that differs from said first ovulation prediction model in the way that it predicts ovulation from data;   automatically comparing said first transformation computation generated completed ovulation prediction output by said first ovulation prediction model with said second transformation computation generated completed ovulation prediction output by said second ovulation prediction model that differs from said first ovulation prediction model in the way that it predicts ovulation from data;   automatically determining whether said first transformation computation generated completed ovulation prediction output by said first ovulation prediction model or said second transformation computation generated completed ovulation prediction output by said second ovulation prediction model that differs from said first ovulation prediction model in the way that it predicts ovulation from data is likely to provide a desired selection criterion indication of the likely existence of an ovulation event;   automatically utilizing whichever completed ovulation prediction output provides said desired selection criterion indication of a likely existence of an ovulation event; and   providing an ovulation indication based on said step of automatically utilizing whichever completed ovulation prediction output provides said desired selection criterion indication of a likely existence of an ovulation event.   
     
     
         57 . A process for improved notification of an ovulation event for a user as described in  claim 56  wherein said step of obtaining periodic internal body indications comprises the step of periodically sensing internal body temperature values for said user. 
     
     
         58 . A process for improved notification of an ovulation event for a user as described in  claim 56  and further comprising the step of providing an ovulation prediction criterion user-preference input to which said step of automatically determining whether said first transformation computation generated completed ovulation prediction output by said first ovulation prediction model or said second transformation computation generated completed ovulation prediction output by said second ovulation prediction model that differs from said first ovulation prediction model in the way that it predicts ovulation from data is likely to provide a desired selection criterion indication of the likely existence of an ovulation event is responsive. 
     
     
         59 . A process for improved notification of an ovulation event for a user comprising the steps of:
 obtaining periodic internal body indications for said user;   automatically transforming said internal body indications to a first transformation computation generated ovulation prediction output;   automatically transforming said internal body indications to a second transformation computation generated ovulation prediction output;   automatically comparing said first transformation computation generated ovulation prediction output with said second transformation computation generated ovulation prediction output;   automatically determining whether said first transformation computation generated ovulation prediction output or said second transformation computation generated ovulation prediction output is likely to provide a more user-preference aligned indication of the likely existence of an ovulation event;   providing an ovulation prediction criterion user-preference input to which said step of automatically determining whether said first transformation computation generated ovulation prediction output or said second transformation computation generated ovulation prediction output is likely to provide a more user-preference aligned indication of the likely existence of an ovulation event is responsive;   automatically utilizing whichever ovulation prediction output provides a more user-preference aligned indication of a likely existence of an ovulation event; and   providing an ovulation indication based on said step of automatically utilizing whichever ovulation prediction output provides a more user-preference aligned indication of a likely existence of an ovulation event.   
     
     
         60 . A process for improved notification of an ovulation event for a user as described in  claim 59  wherein said step of obtaining periodic internal body indications comprises the step of periodically sensing internal body temperature values for said user.