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New app tracks health of heart and lung patients

lungs

A new smartphone app that monitors patients suffering from chronic cardiopulmonary diseases by analysing the way they walk can warn doctors at the first sign of trouble.

Using the health-tracking app, MoveSense, developed by researchers at the University of Illinois at Urbana-Champaign, a patient’s oxygen saturation level can be passively monitored with medical accuracy.

Oxygen saturation is a standard measure of health status.

Unlike other methods of measuring oxygen saturation levels, which detect sharp drops causing desaturation, MoveSense continuously monitors saturation, making the resultant patterns possible to model accurately – and the patient is only required to carry a smartphone while walking.

The ability to accurately measure oxygen saturation without the use of a pulse oximeter is something that has never been achieved, until now.

“The oximeter, a non-invasive medical device usually placed on the patient’s finger, measures the proportion of oxygen in the blood, combining status of the two major circulatory systems, the heart and the lung,” said Bruce Schatz, the head of medical information science at the College of Medicine at Urbana-Champaign, who led the study.

“The saturation level is an overall measure of the patient’s cardiopulmonary fitness,” said Schatz.

Schatz had previously shown that phone sensors can accurately measure walking patterns.

Doctors often use an assessment called the six-minute walk test for patients with heart and lung disease, such as congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) and asthma.

The test provides information regarding a patient’s functional capacity and response to therapy for a wide range of chronic cardiopulmonary conditions.

The Illinois team used MoveSense, in conjunction with their existing gait model, to administer six-minute walk tests to 20 patients with cardiopulmonary disease.

Patients wore pulse oximeters and carried smartphones running MoveSense software, which continuously recorded saturation and motion.

The researchers discovered oxygen saturation readings clustered patients into three pulmonary function categories – one with consistently high saturation, one with consistently low saturation, and a third where saturation varied and patients were clinically unstable.

In addition, they discovered that analysis of the saturation, combined with the gait data, could predict saturation category with 100 per cent accuracy.

This will allow medical professionals to monitor patients’ vital signs, predict their clinical stability, and act quickly should their condition decline, researchers said.

The study was published in the journal Telemedicine and e-Health.