AIMS: Hypoglycaemia unawareness is a common condition associated with increased risk of severe hypoglycaemia. The purpose of the authors' study was to develop a simple to use, home-based and non-invasive hypoglycaemia warning system based on electroencephalography (EEG), and to demonstrate its use in a single-case feasibility study. METHODS: A participant with type 1 diabetes forms a single-person case study where blood sugar levels and EEG were recorded. EEG was recorded using skin surface electrodes placed behind the ear located within the T3 region by the participant in the home. EEG was analysed retrospectively to develop an algorithm which would trigger a warning if EEG changes associated with hypoglycaemia onset were detected. RESULTS: All hypoglycaemia events were detected by the EEG hypoglycaemia warning algorithm. Warnings were triggered with blood glucose concentration levels at or below 4.2 mmol/l in this participant and no warnings were issued when in euglycaemia. CONCLUSION: The feasibility of a non-invasive EEG-based hypoglycaemia warning system for personal monitoring in the home has been demonstrated in a single case study. The results suggest that further studies are warranted to evaluate the system prospectively in a larger group of participants.
AIMS: Hypoglycaemia unawareness is a common condition associated with increased risk of severe hypoglycaemia. The purpose of the authors' study was to develop a simple to use, home-based and non-invasive hypoglycaemia warning system based on electroencephalography (EEG), and to demonstrate its use in a single-case feasibility study. METHODS: A participant with type 1 diabetes forms a single-person case study where blood sugar levels and EEG were recorded. EEG was recorded using skin surface electrodes placed behind the ear located within the T3 region by the participant in the home. EEG was analysed retrospectively to develop an algorithm which would trigger a warning if EEG changes associated with hypoglycaemia onset were detected. RESULTS: All hypoglycaemia events were detected by the EEG hypoglycaemia warning algorithm. Warnings were triggered with blood glucose concentration levels at or below 4.2 mmol/l in this participant and no warnings were issued when in euglycaemia. CONCLUSION: The feasibility of a non-invasive EEG-based hypoglycaemia warning system for personal monitoring in the home has been demonstrated in a single case study. The results suggest that further studies are warranted to evaluate the system prospectively in a larger group of participants.
Authors: Anne-Sophie Sejling; Troels W Kjær; Ulrik Pedersen-Bjergaard; Sarah S Diemar; Christian S S Frandsen; Linda Hilsted; Jens Faber; Jens J Holst; Lise Tarnow; Martin N Nielsen; Line S Remvig; Birger Thorsteinsson; Claus B Juhl Journal: Diabetes Date: 2014-12-08 Impact factor: 9.461
Authors: Murat Aksoy; Chiedu E Ufodiama; Anthony D Bateson; Stewart Martin; Aziz U R Asghar Journal: Exp Brain Res Date: 2021-08-04 Impact factor: 1.972