Hyperedge- . IoT, Embedded Systems, Artificial Intelligence,

Heart disease is the most common cause of death — not just in industrialized countries, but for the world as a whole. Many deaths caused by heart failure could be prevented if the patient received medical care sooner, but people are often unaware of impending heart failure until it actually occurs. However, there are physiological indicators that become detectable in advance of heart failure. This wearable “health belt” contains sensors that monitor for those indicators to give warning of imminent heart failure so patients can seek lifesaving medical attention.

This health belt has a variety of sensors to monitor key physiological indicators, including thoracic impedance, heart rate, electrocardiogram activity, and motion activity. None of those alone would reliably correspond to upcoming heart failure without many false positives and negatives, but together they provide a clear picture. The sensor array, which is wearable and resembles a cumberbund, communicates via Bluetooth with the user’s phone. When the signs of heart failure appear, their phone can either notify them to seek medical attention or notify a third party, like a family member or doctor.

Hyperedge- . IoT, Embedded Systems, Artificial Intelligence,

The team used an Arduino Uno board to construct their prototype health belt. It connects to several sensors: a peripheral module interface (PMOD) Impedance Analyzer (IA), an AD8232 ECG (electrocardiogram) sensor, a MAX30105 heart rate sensor, and an ADXL362 accelerometer. Power comes from a 9V battery and an HC06 module handles the Bluetooth communication. 

More testing is needed to determine the health belt’s efficacy, as the research team wasn’t able to gather data from people actually experiencing heart failure. But early testing with a subject mimicking similar body movement and breathing was promising.

Image credit: Iqbal, S.M.A., Mahgoub, I., Du, E. et al. Development of a wearable belt with integrated sensors for measuring multiple physiological parameters related to heart failure. Sci Rep 12, 20264 (2022). https://doi.org/10.1038/s41598-022-23680-1

Boards:Uno
Categories:Arduino

Read more about this on: Arduino Blog