User Friendly Vaginal Sensor System

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.

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.

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.

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.