This paper presents the architecture and initial usability results of an advanced insulin bolus calculator for diabetes (ABC4D), which provides personalised insulin recommendations for people with diabetes by differentiating between various diabetes scenarios and automatically adjusting its parameters over time. The proposed platform comprises two main components: a smartphone-based patient platform allowing manual input of glucose and variables affecting blood glucose levels (e.g. meal carbohydrate content, exercise) and providing realtime insulin bolus recommendations; and a clinical revision platform to supervise the automatic adaptations of the bolus calculator parameters. The system implements a previously insilico validated bolus calculator algorithm based on Case-Based Reasoning (CBR), which uses information from similar past events (i.e. cases) to suggest improved personalised insulin bolus recommendations and automatically learns from new events. Usability of ABC4D was assessed by analysing the system usage at the end of a six-week pilot study (n=10). Further feedback on the use of ABC4D has been obtained from each participant at the end of the study from a usability questionnaire. On average, each participant requested 115 21 insulin recommendations, of which 103 28 (90%) were accepted. The clinical revision software proposed a total of 754 case revisions, where 723 (96%) adaptations were approved by a clinical expert and updated in the patient platform.
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