Giving Compass' Take:

• An experimental device uses machine learning tools—and a bathroom scale—to monitor heart failure.

• How can donors help fund more research to help heart disease and heart monitoring? 

• Here's an article on how the US has made huge strides against heart disease. 

Researchers envision this scenario: The user steps onto a the scale and touches metal pads. The device records an electrocardiogram from their fingers and—more importantly—circulation pulsing that makes the body subtly bob up and down on the scale. Machine learning tools compute that heart failure symptoms have worsened.

In a new study, the researchers report proof-of-concept success in recording and processing data from 43 patients with heart failure. A future marketable version of the medical monitoring scale would ideally notify a doctor, who would call the patients to adjust medication at home, hopefully preventing a long hospital stay and needless suffering.

The pulsing and bobbing signal is called a ballistocardiogram (BCG), a measurement researchers took more commonly about 100 years ago but gave up on as imaging technology far surpassed it. The researchers are making it useful again with modern computation.

“Our work is the first time that BCGs have been used to classify the status of heart failure patients,” says Omer Inan, the study’s principal investigator and an associate professor in the Georgia Institute of Technology’s School of Electrical and Computer Engineering.

Read the full article on monitoring heart failure by John Toon at Futurity.