A development of IoT based basal body temperature (BBT) device with ovulation and pregnancy prediction system using fuzzy logic method

Fertility Awareness Method (FAM) is a natural family planning method that is based on body signs, commonly basal body temperature (BBT) changes during each menstrual cycle in response to hormonal changes in a woman's body. There are several products on the BBT devices that can help in charting,...

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Bibliographic Details
Main Author: Mohd Yazed, Muhammad Syukri
Format: Thesis
Language:English
English
English
Published: 2019
Subjects:
Online Access:http://eprints.uthm.edu.my/1237/1/24p%20MUHAMMAD%20SHUKRI%20MOHD%20YAZED.pdf
http://eprints.uthm.edu.my/1237/2/MUHAMMAD%20SHUKRI%20MOHD%20YAZED%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/1237/3/MUHAMMAD%20SHUKRI%20MOHD%20YAZED%20WATERMARK.pdf
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Summary:Fertility Awareness Method (FAM) is a natural family planning method that is based on body signs, commonly basal body temperature (BBT) changes during each menstrual cycle in response to hormonal changes in a woman's body. There are several products on the BBT devices that can help in charting, monitoring, and tracking the fertility automatically. However, most of them are less used for a consultation purpose because of time-consuming to meet the physician. Besides, the products are lack of clinical studies being reported on the algorithm used to derive the information needed for fertility monitoring. Therefore, this research has developed a prototype named TempIoT1.0 which is a BBT device that's equipped with a smart fertility prediction using fuzzy logic intelligence computational method that can predict ovulation and pregnancy. This prototyped has been integrated with an Internet-of-Things (IoT) for automatic BBT charting and monitoring and accessible data sharing for consultation through an Android application. The smart fertility prediction system has been verified on 60 datasets of the BBT cycles that give an accuracy of 78.3% and 95% for ovulation and pregnancy prediction, respectively. Through performance evaluation of TempIoT1.0 with Omron and iBasal on a healthy subject, comparable results in terms of BBT data pattern with a correlation of 0.984 and 0.972, respectively were observed. TempIoT1.0 is comparably able to predict the occurrence of the ovulation with 67% similarity in the prediction of the ovulation phase and 100% similarity in the prediction of pregnancy. In conclusion, TempIoT1.0 could enhance women’s understandings of their own unique menstrual cycle in a deeper level towards a better healthcare and to the best of found knowledge, this will be among the leading IoT device for the automatic BBT charting and monitoring with a smart fertility prediction system.