Analyse daily individual data to improve secondary prevention of non-communicable disease and reduce healthcare costs
An apparently simple MedTech device able to analyse daily individual data has the potential to improve secondary prevention of non-communicable disease and reduce healthcare costs. By 2040, the number of diabetes sufferers is expected to rise to 642 million impacting negatively on the global health care expenditure for the condition, that will rise to one trillion US$ by 2045. Diabetes is one of the most widespread chronic conditions affecting the global population, however an early diagnosis can reduce the complications related to the disease as well as the economic burden on the healthcare system.
AICube developed an “augmented” electric toothbrush that monitors the level of glucose in the saliva. The outcomes are wirelessly processed through a Machine Learning algorithm. Therefore, the data from each user are evaluated together with the dataset of the main parameters already included in the database and continuously updated. Also the handset hosts an accelerometer for determining a tremor severity index for parkinsionian patients. The objective of AICube is to support early diagnosis of disorders to introduce early and effective treatments, and reduce associated complications. Actors like AICube are populating the MedTech industry is getting populated that is expected to reach a market value of about 660 billion US$ by 2028.