Mountain View, California-based AliveCor, which makes an FDA-cleared mobile electrocardiogram (ECG) device and companion app collectively called Kardia Mobile, has released new features that make it easier to integrate weight, activity, and blood pressure readings via Apple Health or Google Fit.
The added features built on Kardia Mobile’s existing monitoring capabilities for atrial fibrillation, allowing users at risk for stroke to keep tabs on five indicators of cardiovascular disease: heart rhythm, blood pressure, weight, physical activity and resting heart rate. The FDA-cleared Kardia Mobile device takes the form of a smartphone case with two electrodes attached to the back. Users open the Kardia app, place their fingers on the electrodes, and describe out loud any symptoms they are having as the reading is taking place.
“We’re really moving beyond atrial fibrillation to total heart health,” AliveCor’s Chief Operating Officer Doug Biehn told MobiHealthNews in an interview. “With Kardia, you can get data on five risk factors for heart disease and stroke that are also modifiable, and it also creates communication between the user and the doctor that can give peace of mind for those with heart health concerns.”
AliveCor has been building up clinical evidence for the efficacy of its smartphone-connected Kardia ECG devices, with a trial planned with Columbia University, and is seeking FDA clearance for the Kardia Band, which is expected to be released in 2017. That device, which syncs with the Apple Watch, is already available in the UK and will be reimbursed by the UK's National Health Service (NHS).
This week the company also announced a collaboration with the Mayo Clinic to explore the use of Kardia to measure previously hidden health indicators in ECG readings. With the machine learning capabilities of AliveCor’s technology, the company will work with the Mayo Clinic to analyze 10 million of its user ECG recordings, looking for physiological symptoms that could impact the morphology of the reading and help identify other health conditions. For example, the ECG may reveal how health indicators that have implications for patients with abnormal blood potassium levels due to kidney failure.
Dr. Paul Friedman, a Mayo Clinic cardiologist who helped developed the intellectual property that went into the technology, said that the added insight from the ECG to quantify serum potassium brings a “significant enhancement to traditional morphology analysis.”
“It’s exciting to see the application of machine learning algorithms in ECG and its potential to quickly detect rhythm abnormalities in patients,” Friedman said in a statement.
The collaboration goes along with AliveCor’s plan to expand the use of its technology in multiple areas, not just heart disease.
"Working with Mayo Clinic, we are hopeful that soon physicians will be turning to ECG data for the care of many types of patients, not just those with typical cardiovascular issues," Dr. Dave Albert, AliveCor’s chief medical officer, said in a statement.