A multiparameter model for non-invasive detection of hypoglycemia
AuthorElvebakk, Ole; Tronstad, Christian; Birkeland, Kåre I.; Jenssen, Trond Geir; Bjørgaas, Marit Ragnhild Rokne; Gulseth, Hanne Løvdal; Kalvøy, Håvard; Høgetveit, Jan Olav; Martinsen, Ørjan Grøttem
Approach: We have investigated the use of non-invasive sensors for detection of hypoglycemia based on a mathematical model which combines several sensor measurements to identify physiological responses to hypoglycemia. Data from randomized single-blinded euglycemic and hypoglycemic glucose clamps in 20 participants with T1D and impaired awareness of hypoglycemia was used in the analyses.
Main results: Using a sensor combination of sudomotor activity at three skin sites, ECG-derived heart rate and heart rate corrected QT interval, near-infrared and bioimpedance spectroscopy; physiological responses associated with hypoglycemia could be identified with an F1 score accuracy up to 88%.
Significance: We present a novel model for identification of non-invasively measurable physiological responses related to hypoglycemia, showing potential for detection of moderate hypoglycemia using a wearable sensor system.
Accepted manuscript version, licensed CC BY-NC-ND 4.0.