A remote heart monitoring device is only the latest innovation in telemedical technology and home healthcare.
Telemedicine—care delivered by phone or, more often, the Internet—promises to bring healthcare costs down and access to easier access to doctors for people in rural areas.
And an avalanche of mobile apps and software programs, for everything from testing water quality to diagnosing strep throat, kidney failure, and pneumonia, are available now. Patients can cheaply and easily gather scads of data about themselves in a practice broadly called mobile health, or mHealth for short.
Now, a neuroscience research team at the Medical College of Georgia (MCG) in Augusta, led by Dr. Joe Tsien, is looking to make a splash in both markets. Tsien and his colleagues have found a way to measure a person’s heart and breathing rates using any single-channel video camera, including a web or cell phone cam.
The key is a series of complex mathematical algorithms that help the camera sort mountains of visual data into useful, real-time information about the health of humans, medical research animals, and livestock.
“Heart and respiratory rates obviously tell us a lot about how an individual is doing,” Tsien said in a press release. “Normally, caregivers have to put their hands on a patient to assess these rates. However, our algorithms enable us to rapidly and accurately translate, for example, normally imperceptible movement of the skin in rhythm with our breathing into an accurate measure of respiration rate.”
When your heart beats, your vessels expand and contract to accommodate more or less blood. More light is absorbed and less reaches the camera lens the larger these blood vessels get.
Similarly, when you breathe, your body—especially your chest and shoulders—moves slightly, changing the way light is reflected off of you and picked up by the camera.
Using this information, the team’s algorithms can tell the difference between light interference from, say, a desk lamp, and light reflected off of your body.
The technique even works at night because the algorithms can also analyze near-infrared images and black-and-white pictures made in low light.
Tsien and his team measured the vitals of 15 live study subjects, including an infant. The researchers also hooked patients up to a standard electrocardiogram (ECG) and airflow sensor to check that their results were accurate.
The technique yielded a false positive result only three percent of the time, and a false negative less than one percent of the time.
To confirm their findings, the researchers tested the technology on zebrafish, mice, and pigs, as well as TV clips of Michael Phelps and Bill Clinton and a photo of the Mona Lisa, which it correctly recognized as an inanimate object.
A study describing the new technique was published this week in the journal PLOS ONE.
Dr. Nicholas Genes, an assistant professor of emergency medicine at the Icahn School of Medicine at Mount Sinai, says mHealth apps, like this similar technology from Philips, are “a lot of fun” and “very addictive.” The Philips app uses subtle changes in facial flushing to detect heart rate and tiny body movements to calculate breathing rate.
Genes says mobile devices likes these are largely a novelty for now, but that they do have the potential to save money and lives in remote areas. His colleague Dr. David McManus at the UMassMemorial Medical Center is developing an app to monitor atrial fibrillation, or irregular heartbeat.
“I think the ideal environment, at least in the short term, will be in resource-poor environments,” Genes told Healthline. “People have used [the heart monitoring app] on planes and in the developing world where you couldn’t get a big and expensive medical device. It serves a need, especially in many remote locations.”
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“The potential is there, but I think we still need to settle on a framework where these apps can be prescribed and used responsibly and the data analyzed by physicians,” Genes said. “Patients are generating a lot of data from their glucometers, etc. Right now there’s no great way for doctors to be reimbursed for looking at this data and they are a little skeptical of the quality of the data.”
Tsien is hopeful that his technique and others like it can provide accurate patient information that is usually gathered in more painstaking and expensive ways.
“This technology may save time and make it effortless,” Tsien told Healthline. “For example, information on patients’ heart or breathing rates can be conveniently collected as the patients check in, without having the nurses to wrap the traditional monitor around your arms, also reducing the potential cross-contamination.”
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