EUROSTARS | I-Bracelet
I-Bracelet – An intelligent wearable medical device to monitor blood pressure
BLOOD PRESSURE MONITORING AND PREGNANCY: WHAT IS THE MATTER
During pregnancy, the mother’s blood pressure (BP) might tend to increase without any physiological reason. When this high blood pressure is combined with a high protein level in urine, the mother is affected by preeclampsia. This asymptomatic pathology usually starts in the second semester and affects 10% of pregnant women. To diagnose preeclampsia, doctors usually monitor the BP by two measurements of blood pressure during the second and the third semester. However, the BP measurements are not always likely to happen while the mother is experiencing a hypertensive episode. Thus, the pathology cannot be detected on time, and the mother is exposed to a higher risk of eclampsia. Eclampsia is the occurrence of seizure in pregnant women following by a period of confusion and/or coma. Eclampsia is a vital emergency for both the fetuses and the mother. It represents the second causes of maternal death during pregnancy.
Here, the gap in diagnostics is caused by the discontinuity of the blood pressure measurement, which brings the necessity to develop new technologies to ensure continuous monitoring of blood pressure.
Doctor measuring pressure to a pregnant woman using a classical sphygmomanometer
FIELD OF APPLICATIONS
DISEASES EARLY DETECTION
VITAL CONSTANT MONITORING
A PERMANENT BLOOD PRESSURE MONITORING TO DETECT PREECLAMPSIA?
One solution for a continuous monitoring of the blood pressure is to develop a bracelet that collects blood pressure data and treat it to detect preeclampsia pattern. In the framework of the i-bracelet project, we are currently developing a connected wristband equipped with a blood pressure sensor, to detect preeclampsia. This smart device warranties a continuous monitoring of the blood pressure, by connecting together the key elements of the diagnostic chain.
The core element of the bracelet is a pressure sensor, sensitive enough to detect blood pressure variations at the wrist of the patient. The electronic module of the bracelet sends the collected data to a smartphone using a Bluetooth connection.
Using artificial intelligence technology, based on neural network, a predictive algorithm will be set up. This algorithm will aim at early detect blood pressure pattern that might lead to the occurrence of pre-eclampsia. To this end, the neural network will be first trained with annotated clinical data, and then validated with a validation dataset of clinical data.
When a pathologic pattern will be detected, an alarm is sent to the doctor, who can contact the mother to start the complete diagnosis process.
PERMANENT BLOOD PRESSURE MONITORING, FUTURE IMPLICATIONS
The WHO asses that 31% of the deaths worldwide are caused by cardiovascular disorders and patients with cardiovascular pathologies require early detection and monitoring of their symptoms. Beyond pregnant women, the i-bracelet project addresses the challenge to continuously monitor the blood pressure for various types of pathologies. The artificial intelligence solutions that are developed inside i-Bracelet will be useful to monitor other parameters of the cardiovascular system, such as cardiac activity, beat per minute. The long-term application of i-Bracelet will set up in e-health, theranostics, and home care.
The I-Bracelet project is a Eurostars Program, supported by the Eureka Office of the European Commission. The consortium is composed of 5 partners, of which 2 French SME and 3 entities in Romania:
– Cherry Biotech is the coordinator and owns strong expertise to develop the sensor.
– Elvesys is the second French SME that provides a strong background in pressure measurements and integration of the product.
– InfoWorld is a Romanian company specialized in developing IT solutions for health.
– The Politehnica University of Bucharest and the IMT (National Institute for Research and Development in Microtechnologies) are two Romanian academic entities that provide highly competitive expertise in sensor integration and algorithm development.