This paper presents a study into the use of wearable technologies by pregnant women with Type one diabetes (T1D). The World Health Organisation estimates the incidence of T1D globally to be more than 422 million. Wearable tech-nologies can potentially improve decisions around self-management by providing regular feedback on physiological processes. Informed decisions and choices to support self-management of this condition during pregnancy, ultimately enhance pregnancy outcomes. The wearable technologies under consideration include the FreeStyle LibreTM interstitial glucose monitor, Fitbit activity tracker, and blood pressure monitoring for home use. In addition to these devices partic-ipants in this research area will be required to maintain a food diary. Physical activity (PA) is recommended during pregnancy to maintain normal blood pressure (BP), physical health and as a preventative measure against deep venous thromboembolism (DVT). Self-reporting of food intake is known to be problematic and is often underestimated. To fa-cilitate assessment of portion sizes participants will be asked to use mobile phone cameras to visually record the type and quantity of food eaten. The collated data will be processed via statistical analysis and computational analysis before providing feedback using machine learning algorithms to inform decisions around the need for insulin or carbohydrate to maintain euglycaemia.
|Title of host publication||BIBE 2019; The Third International Conference on Biological Information and Biomedical Engineering|
|Number of pages||5|
|Publication status||Published - 18 Nov 2019|
|Event|| Third International Conference on Biological Information and Biomedical Engineering - Hangzhou, China|
Duration: 20 Jul 2019 → 22 Jul 2019
|Conference||Third International Conference on Biological Information and Biomedical Engineering|
|Period||20/07/19 → 22/07/19|