Indwelling Temperature Sensor for Ovulation Detection
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Solution Overview
Problem
Current methods for detecting ovulation are invasive, unreliable, and inconvenient, particularly for long-term monitoring, as they often require medical intervention and are prone to inaccuracies due to diurnal temperature fluctuations and irrelevant data, making it difficult to accurately predict ovulation timing.
Innovation Solution
A method involving multiple temperature readings taken over extended periods using an indwelling device, with faulty or irrelevant data identified and disregarded, and representative values analyzed to provide information on ovulation timing, using a remote computer file server for data processing and user notification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple temperature readings are taken over extended periods using an indwelling device, then measurement precision and reliability of ovulation detection are improved, but device complexity and ease of operation worsen
Solution Approach 1:
The indwelling temperature sensor automatically performs multiple temperature readings over extended periods without requiring manual intervention. The device self-regulates the monitoring process, taking readings at predetermined intervals and storing data locally, thereby improving measurement precision while minimizing the operational burden on users.
Solution Approach 2:
The patent replaces manual temperature measurement methods with an automated electronic sensing system. The indwelling sensor uses electronic temperature detection and data processing algorithms to automatically identify ovulation patterns, substituting mechanical/manual operations with automated electronic systems that enhance precision despite increased device complexity.
2Reliability
If multiple temperature readings are taken over extended periods, then reliability of ovulation detection is improved, but loss of time and productivity worsen
Solution Approach 1:
The system performs preliminary data collection and processing by automatically taking multiple temperature readings over extended periods and pre-processing the data to identify patterns. This preliminary action ensures reliable ovulation detection while reducing the time burden on users, as the heavy lifting of data collection and initial analysis is done automatically before clinical interpretation is needed.
Solution Approach 2:
The indwelling sensor maintains continuous temperature monitoring over extended periods, capturing the full thermal pattern associated with ovulation. This continuous useful action improves reliability by ensuring no critical temperature changes are missed, while the automated nature of the system minimizes the time users need to dedicate to monitoring.
3Measurement precision
If representative temperature values are analyzed over multiple extended periods, then prediction accuracy of fertile windows is improved, but device complexity and data processing requirements worsen
Solution Approach 1:
The system extracts only the essential temperature data points and patterns relevant to ovulation prediction from the extensive dataset collected over multiple extended periods. By focusing analysis on representative temperature values and key thermal patterns rather than processing every raw data point, the system improves prediction accuracy while managing data processing complexity through selective extraction of critical information.
Solution Approach 2:
The patent transforms raw temperature readings into meaningful parameters such as temperature trends, rate of change, and pattern recognition metrics. By changing the parameters from raw data to derived thermal characteristics, the system achieves more accurate fertile window prediction while reducing the computational complexity through dimensionality reduction and feature extraction.
4Ease of operation
If indwelling temperature measuring device is used for extended periods, then ease of operation is improved, but reliability worsens due to faulty or irrelevant data
Solution Approach 1:
The system incorporates feedback mechanisms that continuously monitor the quality and relevance of temperature data collected by the indwelling sensor. Algorithms analyze incoming data to identify faulty or irrelevant readings based on predetermined criteria, and provide feedback to adjust the monitoring parameters or flag problematic data points, thereby maintaining ease of operation while improving data reliability through automated quality control.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for accurate and convenient detection of ovulation, reducing the need for frequent medical interventions and improving the reliability of predicting fertile windows, enhancing fertility monitoring and contraception timing.
Implementation Method 1
taking multiple temperature readings from the female mammal during an extended period
Data Source
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AI summary
Methods of detecting and predicting ovulation and a period of fertility include determining a series of measures indicative of the basal body temperature of a female human user to identify a temperature change event. The method includes obtaining, within a first 24 hour period, a plurality of first readings of the temperature of the female human user at intervals over a first extended period of at least an hour. The plurality of first readings are then processed to determine at least one first representative temperature reading representative of the basal body temperature of the user for the first extended period and the at least one first representative temperature reading is stored. The method is repeated for at least second and third 24 hour periods and the representative temperature readings are provided for analysis to identify a temperature change event for the female human user.