WO2025253234 - NON-INVASIVE BLOOD GLUCOSE MONITORING DEVICE AND SYSTEM
National phase entry is expected:
Publication Number
WO/2025/253234
Publication Date
11.12.2025
International Application No.
PCT/IB2025/055493
International Filing Date
28.05.2025
Title **
[English]
NON-INVASIVE BLOOD GLUCOSE MONITORING DEVICE AND SYSTEM
[French]
DISPOSITIF ET SYSTÈME DE SURVEILLANCE NON INVASIVE DE LA GLYCÉMIE
Applicants **
COER SYSTEMS GMBH
Inventors
PONON, Nikhil KARUNAKARAN
Priority Data
102024000012931
05.06.2024
IT
Application details
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International Searching Authority |
EPO
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| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
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| Type of Assignment |
The Standard Agent's Assignment
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| Applicant's Legal Status |
Legal Entity
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| Entry into National Phase under |
Chapter I
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| Patent Delivery |
Send the Letters Patent by Courier
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| Translation |
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* The data is based on automatic recognition. Please verify and amend if necessary.
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2693 | |
| EPO | Filing, Examination, Granting | 16342 | |
| Japan | Filing, Examination, Granting | 2607 | |
| South Korea | Filing, Examination, Granting | 2903 | |
| USA | Filing, Examination, Granting | 6540 |
Total:
31,085
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Abstract[English]
A system and method for non-invasive blood glucose level determination and proactive management are disclosed. A sensing device comprises a capacitance-to-digital converter (CDC) sensor, featuring an active shield electrode and single-ended mode operation, to measure capacitance variations indicative of net body charge modulation by systemic physiological activity correlated with blood glucose. The device also includes at least one skin conductance sensor. A processor determines blood glucose levels from combined CDC and skin conductance data, optionally using machine learning. Further, a proactive artificial intelligence (AI) system, employing supervised and reinforcement learning models, analyzes real-time and historical data to predict blood glucose trajectories and the likelihood of future dysregulation. Crucially, the AI dynamically generates a personalized schedule of recommended actions (e.g., relating to diet, exercise, or medication timing) for managing the subject's blood glucose, providing alerts and the action plan to enhance diabetes self-management.[French]
L'invention concerne un système et un procédé non invasifs de détermination et de gestion proactive du taux de glycémie. Un dispositif de détection comprend un capteur de convertisseur capacité-numérique (CDC), comprenant une électrode de blindage active et permettant un fonctionnement en mode asymétrique, destiné à mesurer des variations de capacité indiquant une modulation de la charge corporelle nette par une activité physiologique systémique corrélée à la glycémie. Le dispositif comprend également au moins un capteur de conductance cutanée. Un processeur détermine des taux de glycémie à partir de données combinées de CDC et de conductance cutanée, éventuellement à l'aide de l'apprentissage automatique. En outre, un système d'intelligence artificielle (IA) proactive, utilisant des modèles d'apprentissage supervisés et de renforcement, analyse des données en temps réel et historiques pour prédire des trajectoires de glycémie et la probabilité d'apparition d'une dérégulation future. En particulier, l'IA génère dynamiquement un calendrier personnalisé d'actions recommandées (par exemple, concernant le régime alimentaire, l'exercice ou l'heure de prise de médicaments) destinés à réguler la glycémie du sujet, fournissant ainsi des alertes et un plan d'action pour améliorer l'auto-gestion du diabète.