The HypoVoice Study

Diabetes Mellitus Clinical Trial

— HypoVoice  

Official title:

Vocal Biomarkers for the Detection and Prevention of Hypoglycemia (HypoVoice)

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05569876
• Other study ID #: HypoVoice
• Status: Completed
• Phase: N/A
• Start date: November 11, 2022
• Est. completion date: January 31, 2023

Study information

• Verified date: March 2023
• Source: University Hospital Inselspital, Berne
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

The HypoVoice study aims at identifying potential vocal biomarkers associated with hypoglycemia to pave the way towards a voice-based hypoglycemia detection approach.

Description:

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 7
• Est. completion date: January 31, 2023
• Est. primary completion date: January 31, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 60 Years

Eligibility

Inclusion Criteria:

• Written informed consent

• Type 1 Diabetes mellitus as defined by WHO for at least 6 months

• Aged 18 - 60 years

• HbA1c =9.0 %

• Functional insulin treatment with good knowledge of insulin self-management

• Native language German or Swiss German

• Use of continuous glucose monitoring (CGM) or flash glucose monitoring (FGM)

Exclusion Criteria:

• Incapacity to give informed consent

• Contraindications to insulin aspart (NovoRapid®)

• Total daily insulin dose >2 IU/kg/day

• Pregnancy, breast-feeding or lack of safe contraception

• Active heart, lung, liver, gastrointestinal, renal or psychiatric disease

• Pacemaker or implantable cardioverter defibrillator (ICD)

• Epilepsy or history of seizure

• Chronic neurological or ear-nose-and-throat (ENT) disease influencing voice or history of voice disorder

• Illiteracy or dyslexia

• Active smoking

• Active drug or alcohol abuse

• Medication known to interfere with voice or to induce listlessness (e.g. opioids, benzodiazepines, etc.)

Related Conditions & MeSH terms

• Diabetes Mellitus
• Hypoglycemia

Intervention

Other:
• Controlled hypoglycemic state
Voice sampling is performed in different glycemic states (euglycemia and hypoglycemia).

Locations

Country	Name	City	State
Switzerland	Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism	Bern

Sponsors (4)

Lead Sponsor	Collaborator
University Hospital Inselspital, Berne	CSEM Centre Suisse d'Electronique et de Microtechnique SA, Idiap Research Institute, Ludwig-Maximilians - University of Munich

Country where clinical trial is conducted

Switzerland, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Other	Change in hypoglycemic symptoms across the glycemic trajectory	Hypoglycemic symptoms will be assessed using the Edinburgh Hypoglycemia Scale (higher score means more symptoms).	4 hours
Other	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).	4 hours
Other	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).	4 hours
Primary	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	4 hours
Secondary	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	4 hours
Secondary	Voice parameters indicative of hypoglycemia	Explainable AI methods will be used to identify voice parameters indicative of hypoglycemia	4 hours
Secondary	Physiological parameters indicative of hypoglycemia	Explainable AI methods will be used to identify physiological parameters indicative of hypoglycemia	4 hours