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This study is designed to assist with the development of a first, truly non-invasive technology for blood glucose monitoring, which will have the potential to eliminate the need for painful finger pricking or expensive continuous blood glucose monitor use. The purpose of this study is to collect biometric data, such as bioimpedance (how well the body impedes electric current flow), from participants who are living with type 2 diabetes. A proof-of-concept prototype (non-invasive continuous glucose monitor; NI-CGM) will be used to collect this biometric data. The data will then be used to develop and refine a computer model that can be used to predict blood glucose levels (BGLs). Individuals with diabetes experience a great range of blood BGLs throughout their daily life and activities, therefore it is essential to gather biometric data corresponding to this large range to build a computer model, to ensure model reliability.
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The study will be conducted over a two-week period where the participants are required to wear the prototype, that will continuously collect the biometric data. Participants are required to use this device together with two existing commercially available blood glucose meters that are considered management routine for diabetes (an Abbott FreeStyle Libre and an Accu-Chek® Mobile), throughout the duration of the study. The majority of the study is carried out independently, by the participants, where they wear the prototype throughout their daily life and activities. The data collected from the non-invasive custom-built device and the existing blood glucose meters will be used to develop a computer model that will allow for blood glucose levels to be predicted, over time.
The study will not interfere with any of the participants' diabetes management plans provided to them, by their regular doctor, under regular care, such as medications, diet and current use of blood glucose monitoring.
It is hypothesised that the bioimoedance data collected using the non-invasive prototype device, in conjunction with existing devices used in diabetes management, will enable the development of a computer model that allows for blood glucose levels to be predicted in people with type 2 diabetes.
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14 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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