AI-based wearable sensors for continuous monitoring of diabetes and cardiovascular diseases

Informazioni relative al progetto

SensCare

ID dell’accordo di sovvenzione: 101113995

DOI

10.3030/101113995

Progetto chiuso

Data della firma CE 7 Giugno 2023

Data di avvio 1 Luglio 2023

Data di completamento 31 Marzo 2024

Finanziato da

• European innovation ecosystems

Costo totale

Nessun dato

Contributo UE

€ 75 000,00

Coordinato da

SENSAI TEKNOLOJI ANONIM SIRKETI
Türkiye

Periodic Reporting for period 1 - SensCare (AI-based wearable sensors for continuous monitoring of diabetes and cardiovascular diseases)

Periodo di rendicontazione: 2023-07-01 al 2024-03-31

Sintesi del contesto e degli obiettivi generali del progetto

Cardiovascular diseases (CVDs) are the leading cause of death in Europe, with a total of 3.9 million deaths yearly, accounting for 45% of all deaths. Diabetes is another widely spread disease affecting 60 million people in the EU (10% of the total population). Diabetes is the major cause of death in the age of 20-79. Also, Europe has the highest number of children with type-1 diabetes compared to other regions, with approximately 140,000 diagnosed children, and it has one of the highest prevalence rates of diabetes in children, with 21,600 new cases per year. Frequent glucose monitoring is critical for keeping blood glucose levels within a specific range to prevent potential cardiometabolic disease progression and pathophysiological changes. Current standard healthcare systems are passive and reactive, which deal with issues, incidents, and accidents after the opportunity to prevent damage to the patient has passed. With reactive healthcare, doctors provide treatment once patients contact them after developing noticeable symptoms. Actions are taken after things go wrong and sometimes after the opportunity to save the patient has passed. Besides, economically, reactive safety measures are costly in the long term. Moreover, this routine fails to prevent the onset of health conditions by prioritizing diagnostics and treatment.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

For SensCare, we analyzed cardiaovascular and diabetes data and potential body parts in which we can acquire data. Then based on the findings we designed and fabricated sensors for sensing of the parameters.

The sensor offers a two-pronged approach, analyzing both arterial pulse for cardiovascular health assessment and sweat glucose concentration for diabetic monitoring.

The foundation of the sensor utilizes a thin and flexible material, such as polyimide, for conformability and precise detection of arterial strain. A key component is the integration of a spiral microfluidic channel. This design maximizes the measurement path within a limited area, resulting in high sensitivity to subtle changes in arterial diameter during pulse events. Piezoresistive materials embedded within the channel convert these strains into measurable electrical signals.

For sweat collection and glucose monitoring, the microfluidic channel extends to incorporate a dedicated chamber. This chamber passively collects sweat through capillary action. The collected sweat then interacts with enzyme-modified electrodes positioned at the channel's end. These electrodes react specifically with glucose in the sweat, generating an electrical current proportional to the glucose concentration. Near Field Communication (NFC) technology can be employed to eliminate the need for a battery. In this scenario, the sensor harvests energy wirelessly from a smartphone for data transmission.

Biocompatible materials and the development of data processing algorithms for both pulse and glucose analysis are crucial aspects for successful sensor implementation. Finally, optimizing the design for a compact and comfortable form factor ensures seamless integration into daily routines. This multifunctional sensor offers a promising approach for convenient wrist-worn monitoring of both cardiovascular health and blood sugar levels.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

For strain sensing, the sensor consists of a stretchable silicone layer and a conductive paste screen printed on top. The conductive layer is known as a stretchable conductor manufactured by Dupont company. We developed a screen printing technique to pattern a spiral device. Then we attached the device on a moving platform and conducted stretch tests. This allowed us to see the resistance change per strain applied. The wrist has relatively low strain values around 2-5% depending on skin thickness and modulus. There is also possibility of using the sensor around the chest area. The experiment results showed that given the substrate layer and the conductive paste can attach satisfactorily. When we apply a strain of 15%, we didn’t see any adhesion or peel off problem. Then we connected the sensor to a multimeter in which we measure the resistance values. For a strain value of 15% the resistance changed almost 80%. It shows that the sensor was sensitive enough and these results suggest that the sensory can be used for monitoring expansions of arteries around the wrist. Our future goal includes miniaturizing the sensor even more and conduct in vivo experiments.

For sensing glucose from sweat, we developed a wearable patch. compact and flexible design allows for comfortable wear on various body parts during everyday activities. For battery-free operation and easy data transfer, it uses NFC technology to communicate with your smartphone. The sensor itself is a marvel of miniaturization, containing an antenna, NFC chip, sweat analyzer, and microfluidic channels all stacked together (see Figure 2). Here's how it works: your smartphone sends a signal, the sensor harvests energy wirelessly, analyzes your sweat with the help of microchannels, and then transmits the data back to your phone for display. We conducted selectivity test with multiple molecules. The sensor did not respond to common molecules found in sweat such as ascorbic acid, urea, glycine, and sucrose. On the other hand it generated different levels of current for different glucose concentrations. Therefore the results show capacity of the device to be used as a glucose sensor. Our future work include testing of this device with optimized electro-chemical surface recipe so that we have smooth increase when glucose concentration increases.