An interventional study of Controlled hypoglycemic state in Diabetes Mellitus and Hypoglycemia, sponsored by Insel Gruppe AG, University Hospital Bern. Completed at 1 site in Switzerland. Open to participants aged 18 Years to 60 Years. Per ClinicalTrials.gov, last updated 2023-03-10.
Sponsored by Insel Gruppe AG, University Hospital Bern · Not applicable, Interventional, and Other
The HypoVoice study aims at identifying potential vocal biomarkers associated with hypoglycemia to pave the way towards a voice-based hypoglycemia detection approach.
While hypoglycemia has been widely studied in medical research, studies assessing vocal changes associated with this state are limited. This study aims at collecting a data set labelled with the gold standard (blood glucose) to provide a solid basis for the identification of vocal biomarkers using machine learning. Additionally, physiological data are collected using wearable sensors to assess whether additional integration of vital signs (e.g. heart rate) enhances the performance of hypoglycemia detection.
640 studies on the registry are indexed under Hypoglycemia; 86 are open to participants now.
This study's enrollment of 7 is below the median of 29 across 471 interventional studies indexed under Hypoglycemia.
Browse Hypoglycemia studies →Insel Gruppe AG, University Hospital Bern is the lead sponsor of 724 studies on the registry; 177 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Exclusion Criteria:
Other: Controlled hypoglycemic state
Voice sampling is performed in different glycemic states (euglycemia and hypoglycemia).
Diagnostic accuracy of the HypoVoice approach to detect hypoglycemia based on voice data quantified as area under the receiver operating characteristic curve (AUROC)
Voice data will be collected in eu- and hypoglycemia
Time frame: 4 hours
Diagnostic accuracy of the HypoVoice approach to detect hypoglycemia based on voice and physiological data quantified as area under the receiver operating characteristic curve (AUROC)
Voice and physiological data will be collected in eu- and hypoglycemia
Time frame: 4 hours
Voice parameters indicative of hypoglycemia
Explainable AI methods will be used to identify voice parameters indicative of hypoglycemia
Time frame: 4 hours
Physiological parameters indicative of hypoglycemia
Explainable AI methods will be used to identify physiological parameters indicative of hypoglycemia
Time frame: 4 hours
Change in hypoglycemic symptoms across the glycemic trajectory
Hypoglycemic symptoms will be assessed using the Edinburgh Hypoglycemia Scale (higher score means more symptoms).
Time frame: 4 hours
Change in cognitive performance across the glycemic trajectory.
Cognitive performance will be assessed using the Digit Symbol Substitution Test (higher score means better cognitive performance).
Time frame: 4 hours
Change in cognitive performance across the glycemic trajectory.
Cognitive performance will be assessed using the Trail Making B Test (more time needed to complete the tests means worse cognitive performance).
Time frame: 4 hours
This study is completed, as verified in Mar 2023. You cannot join it, but the record below documents what was studied.
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Insel Gruppe AG, University Hospital Bern