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Detecting Heart Failure Using Existing Sensors on Smartphones


According to the research described in a paper recently published in the journal JACC, an ongoing study is developing an app for diagnosing the potentially lethal condition caused by heart failure early by simply placing a smartphone on a patient’s chest.

The first stages of heart failure may present in the form of fatigue upon exertion or shortness of breath. Of course, these symptoms may be from other more innocuous causes. Currently, it often requires ultrasound heart scans, blood tests, or other special procedures to know whether they are caused by heart failure or not.

In a partnership with Helsinki and Stanford universities, 1,003 volunteer patients were tested via the app at all three institutions’ hospitals. 217 of those were already diagnosed with heart failure and the other 786 are healthy controls.

The scientists pinpointed the characteristics that were specific to the participants with heart failure by analyzing the app-obtained chest vibration readings. The app reached 89% accuracy in identifying individuals with the condition.

Previously, there were also other developed apps for detecting heart failure, such as Cordio HearO or Cardiio Rhythm.

Created by startup Cordio Medical, HearO uses artificial intelligence (AI) technology to detect changes in the voice over time. The AI algorithms detect voice changes that indicate fluid accumulation in the lungs before any symptoms surface. This condition develops when the heart muscle is too weak to pump all the blood the body needs, leading fluid to build up in the extremities and lungs. When notices change, the system alerts the patient’s doctor.

In trials, the app successfully predicted heart failure in 81 of the cases about three weeks before heart failure actually happened. This AI heart-failure-predicting app is also named FDA Breakthrough Device in the US and Europe.

Cardiio Rhythm was created by a team at the Chinese University of Hong Kong, it uses the phone’s camera to analyze subtle changes in a person’s facial skin color, which is related to an indicator of fluctuations in his heart rate. When tested on 85 patients, the result showed 25 of whom were found to have atrial fibrillation via readings obtained from a 12-lead electrocardiogram (ECG). The app detected the disorder with an accuracy rate of 92 percent.

Article Source: University of Turku
Image by valelopardo from Pixabay